U.S. patent application number 12/854836 was filed with the patent office on 2011-02-17 for method and apparatus for expert verification.
This patent application is currently assigned to JustAnswer Corp.. Invention is credited to Andrew Paul Kurtzig, Emily Allison Su-Ian Reber Porter.
Application Number | 20110041173 12/854836 |
Document ID | / |
Family ID | 43586466 |
Filed Date | 2011-02-17 |
United States Patent
Application |
20110041173 |
Kind Code |
A1 |
Kurtzig; Andrew Paul ; et
al. |
February 17, 2011 |
METHOD AND APPARATUS FOR EXPERT VERIFICATION
Abstract
In exemplary embodiments, an apparatus and method for verifying
experts on a consultation system is provided. Identity and
credential information is received at a web server from a potential
expert. A selection of a category that the potential expert wants
to be admitted is also received. The identity information and at
least a portion of the credential information may be verified. The
potential expert is accepted as an expert based in part on a result
of the verifying of the identity and credential information. Once
accepted, an account associated with the potential expert is
activated to allow the potential expert to become an expert and to
allow the expert to provide answers on the consultation system when
the potential expert is accepted.
Inventors: |
Kurtzig; Andrew Paul; (San
Francisco, CA) ; Porter; Emily Allison Su-Ian Reber;
(San Francisco, CA) |
Correspondence
Address: |
SCHWEGMAN, LUNDBERG & WOESSNER, P.A.
P.O. BOX 2938
MINNEAPOLIS
MN
55402
US
|
Assignee: |
JustAnswer Corp.
San Francisco
CA
|
Family ID: |
43586466 |
Appl. No.: |
12/854836 |
Filed: |
August 11, 2010 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
61233046 |
Aug 11, 2009 |
|
|
|
Current U.S.
Class: |
726/7 |
Current CPC
Class: |
G06Q 30/0283 20130101;
G06Q 10/101 20130101; G06Q 50/01 20130101; G06Q 30/0207 20130101;
G06Q 40/12 20131203; H04M 3/51 20130101; G06Q 10/10 20130101; G06Q
30/0206 20130101; G06Q 30/0185 20130101 |
Class at
Publication: |
726/7 |
International
Class: |
H04L 9/32 20060101
H04L009/32; G06F 21/00 20060101 G06F021/00 |
Claims
1. A method of verifying experts on an online consultation system,
the method comprising: receiving identity information and
credential information at a web server from a device associated
with a potential expert; verifying the identity information and at
least a portion of the credential information received from the
potential expert; determining whether to accept the potential
expert as an expert based in part on a result of the verifying of
the identity and credential information; and activating, using one
or more processors, an account associated with the potential expert
on the web server to allow the potential expert to become an expert
and to allow the expert to provide answers on the consultation
system when the potential expert is accepted.
2. The method of claim 1 further comprising providing a test to the
potential expert and evaluating a result of the test.
3. The method of claim 2 wherein the receiving and verifying of the
credential information occurs based on the identity being verified
and the result of the test being positive.
4. The method of claim 1, further comprising determining whether
there is a need for a new expert in a selected category.
5. The method of claim 1, further comprising determining whether
the potential expert meets minimum requirements in a selected
category.
6. The method of claim 5, wherein the minimum requirements are
based on characteristics of other experts in the selected
category.
7. The method of claim 1, wherein the verifying of the identity
information comprises providing the potential expert with one or
more identity test questions.
8. The method of claim 1, wherein the verifying of the identity
information comprises using a third party identity verification
system and wherein the verifying of the credential information
comprises using a third party credential verification system.
9. The method of claim 1, wherein the potential expert is a member
of a plurality of geographically disparate experts and potential
experts.
10. The method of claim 1, further comprising evaluating the expert
based on feedback from one or more of users, peers, affiliates, or
other third-parties.
11. The method of claim 10 further comprising determining whether
to deactivate and remove the expert from the consultation system
based on the evaluating.
12. An apparatus, comprising: an accounts engine to receive
identity information and credential information at a web server
from a potential expert; at least one verification module to verify
the identity information and at least a portion of the credential
information received from the potential expert; and an acceptance
module to determine whether to accept the potential expert as an
expert based on a result from at the least one verification module
and to activate, using one or more processors, an account
associated with the potential expert to become an expert and to
allow the expert to provide answers on the consultation system when
the potential expert is accepted.
13. The apparatus of claim 12 further comprising a testing module
to provide a test to the potential expert and to evaluate a result
of the test.
14. The apparatus of claim 12, wherein the acceptance module is
further to determine whether there is a need for a new expert in a
selected category.
15. The apparatus of claim 12, wherein the acceptance module is
further to determine whether the potential expert meets minimum
requirements in a selected category, the minimum requirements being
based on characteristics of other experts in the selected
category.
16. The apparatus of claim 12, wherein the at least one
verification module further provides the potential expert with one
or more identity test questions to verify the identity of the
potential expert.
17. The apparatus of claim 12, further comprising a quality control
engine to evaluate the expert based on feedback from one or more of
users, peers, affiliates, or other third-parties.
18. The apparatus of claim 17, wherein the quality control engine
is further to determine whether to deactivate and remove the expert
from the consultation system based on the evaluation
19. A non-transitory machine-readable storage medium having
embodied thereon instructions which when executed by at least one
processor, causes a machine to perform operations comprising:
receiving identity information and credential information at a web
server from a potential expert; verifying the identity information
and at least a portion of the credential information received from
the potential expert; determining whether to accept the potential
expert as an expert based on a result of the verifying of the
identity and credential information; and activating an account
associated with the potential expert on the web server to allow the
potential expert to become an expert and to allow the expert to
provide answers on the consultation system when the potential
expert is accepted.
20. The non-transitory machine-readable storage medium of claim 19,
wherein the method further comprises determining one or more
categories for the expert based on the credential information
received from the potential expert.
Description
RELATED APPLICATIONS
[0001] The present application claims of the priority benefit of
U.S. Provisional Patent Application Ser. No. 61/233,046 filed on
Aug. 11, 2009 and entitled "Method and Apparatus for Expert Quality
Control," which is incorporated herein by reference. The present
application is also related to U.S. patent application Ser. No.
______ filed on Aug. 11, 2010 and entitled "Method and Apparatus
for Expert Quality Control," U.S. patent application Ser. No.
______ filed on Aug. 11, 2010 and entitled "Method and Apparatus
for Creation of New Channels in a Consultation System," and U.S.
patent application Ser. No. ______ filed on Aug. 11, 2010 and
entitled "Method and Apparatus for Determining Pricing Options in a
Consultation System," which are all incorporated herein by
reference.
FIELD
[0002] The present application relates generally to the field of
computer technology and, in specific exemplary embodiments, to
methods and systems for expert verification.
BACKGROUND
[0003] Presently, many online websites allow for exchange of
information. Some of these websites provide a question and answer
type capability whereby a user may post a question and one or more
other users may provide a reply. Often time, any user on the
Internet may be able to post the reply. While some of these users
may have some qualification or expertise in a particular area,
there is no requirement that the user have particular
qualifications in order to post a response to a question or that
the user has his or her qualifications verified.
BRIEF DESCRIPTION OF DRAWINGS
[0004] Various ones of the appended drawings merely illustrate
exemplary embodiments of the present invention and cannot be
considered as limiting its scope.
[0005] FIG. 1 is a diagram of an exemplary environment in which
embodiments of the present invention may be practiced.
[0006] FIG. 2 is a block diagram of an exemplary consultation
system.
[0007] FIG. 3 is a block diagram of an exemplary web server.
[0008] FIG. 4 is a block diagram of an exemplary verification
engine.
[0009] FIG. 5 is a block diagram of an exemplary quality control
engine.
[0010] FIG. 6 is a flowchart of an exemplary method for accepting
an expert.
[0011] FIG. 7 is a flowchart of an exemplary method for expert
quality control.
[0012] FIG. 8 is a screenshot of an example of a portion of an
expert registration landing page.
[0013] FIG. 9 is a screenshot of an example of a portion of a
category selection page.
[0014] FIG. 10 is a screenshot of an example of a portion of an ID
verification page.
[0015] FIG. 11 is a screenshot of an example of a portion of a
credential verification page.
[0016] FIG. 12 is a simplified block diagram of a digital device
within which a set of instructions, for causing the machine to
perform any one or more of the methodologies discussed herein, may
be executed.
DETAILED DESCRIPTION
[0017] The description that follows includes illustrative systems,
methods, techniques, instruction sequences, and computing machine
program products that embody the present invention. In the
following description, for purposes of explanation, numerous
specific details are set forth in order to provide an understanding
of various embodiments of the inventive subject matter. It will be
evident, however, to those skilled in the art that embodiments of
the inventive subject matter may be practiced without these
specific details. In general, well-known instruction instances,
protocols, structures and techniques have not been shown in
detail.
[0018] As used herein, the term "or" may be construed in either an
inclusive or exclusive sense. Similarly, the term "exemplary" is
construed merely to mean an example of something or an exemplar and
not necessarily a preferred or ideal means of accomplishing a goal.
Additionally, although various exemplary embodiments discussed
below focus on verification of experts, the embodiments are given
merely for clarity and disclosure. Alternative embodiments may
employ other systems and methods and are considered as being within
the scope of the present invention.
[0019] Embodiments of the present invention provide systems and
methods for expert verification. In exemplary embodiments,
potential experts go through an application and registration
process in order to be accepted and activated on a consultation
system. Application and registration information is received from
each potential expert. The application and registration information
may include identification information and credentials of the
potential expert. The application information may also include a
selection of at least one category to which the potential expert
wants to be admitted. The application and registration information
may cause a potential expert's application to be rejected (e.g., if
minimum requirements and standards are not met). If it does not
cause a rejection, the application and registration information may
be placed on hold, or verified, in part or in whole, to determine
whether to accept the potential expert and activate an associated
account; it also may be verified, in part or in whole, at a later
point in time, for example, to determine whether to expand the
categories into which the expert is admitted or to maintain as
active the associated account. The application and registration
information may also include various kinds of tests, such as
subject matter proficiency tests, site usage tests, customer
service skills tests, and other tests aimed to determine
qualifications, quality, and likely performance. Should the
potential expert be accepted based on the application and
registration process, the potential expert becomes an expert on the
consultation system and may be associated with one or more
categories as an expert in the categories.
[0020] Once accepted and activated, the experts may provide answers
to users and receive feedback in various forms from users and
peers. Feedback on performance of an expert on the consultation
system is received for the expert. The feedback may be from users
of the consultation system, other experts on the consultation
system, or third-parties with relevant expertise and may comprise
direct and indirect feedback. The direct feedback may comprise one
or more of rating the expert, rating the answers of the expert,
receiving a complaint for the expert, receiving a survey on the
expert or the answers of the expert, and receiving a compliment for
the expert. Indirect feedback comprises one or more of accepting a
response provided by the expert, requesting a refund after
receiving a response provided by the expert, paying a bonus to the
expert, and opting into or out of future responses or
communications from the expert (e.g., follow-up communications,
marking communications from an expert as spam). The expert feedback
may comprise a report on the expert whereby the report directed to
one or more of the correctness or completeness of a response
provided by the expert, the professionalism of the expert, and a
violation of site policy committed by the expert. The expert
feedback may further comprise a survey performed on the expert.
Adjustment factors are recorded for the expert. The adjustment
factors comprise public and non-public actions associated with the
expert. The expert is then evaluated using the feedback and the
adjustment factors. The evaluation may result in a score or ranking
for the expert. Based on the score or ranking, the consultation
system may perform various actions (e.g., granting and revoking
privileges or access to certain questions, sending feedback and
other information, suspending or deleting the accounts of experts
with low scores). The score or rank may also be used to determine
one or more of a payment amount, commission, bonus, and revenue
share percentage for the expert. Thus, the performance of each
expert may be reviewed using various forms of feedback in order to
provide expert quality control (e.g., management of the quality of
experts and answers) on the consultation system. Based on the
scores, the consultation system may perform various actions (e.g.,
ranking, granting and revoking privileges or access to certain
questions, sending feedback and other information, suspending or
disabling the accounts of experts with low scores).
[0021] FIG. 1 shows an exemplary environment 100 in which
embodiments of the present invention may be practiced. The
exemplary environment 100 comprises a consultation system 102
coupled via a communications network 104 to one or more user
clients 106 and expert clients 108. The communication network 104
may comprise one or more local area networks or wide area networks
such as, for example, the Internet and telephone systems.
[0022] In exemplary embodiments, the consultation system 102
provides a forum where users may post or pose questions for which
experts may provide answers. The consultation system 102 may
provide the forum via a website. In some embodiments, at least
portions of the forum (e.g., asking of questions or receiving of
responses) may occur via the website, mobile phone, text messaging,
telephone, video, VoIP, other websites, or other computer software
applications. Because the consultation system 102 is network based
(e.g., Internet, public switched telephone network (PSTN), cellular
network), the users using the consultation system 102 and experts
providing answers may be geographically dispersed (e.g., may be
located anywhere in the world). As a result an expert may provide
answers to a user thousands of miles away. Additionally, the
consultation system 102 allows a large number of users and experts
to exchange information at the same time and at any time.
[0023] By using embodiments of the present invention, a user
posting a question may easily obtain a tailored answer.
Accordingly, one or more of the methodologies discussed herein may
obviate a need for additional searching for answers, which may have
the technical effect of reducing computing resources used by one or
more devices within the system. Examples of such computing
resources include, without limitation, processor cycles, network
traffic, memory usage, storage space, and power consumption.
[0024] In various embodiments, a user may pose a question and one
or more experts may provide answers. In various embodiments, the
question may be matched with a category of experts, more specific
set of experts, or even individual experts, sometimes on a rotating
basis by user selection, a keyword based algorithm, a quality based
algorithm (or score or rating), or other sorting mechanism that may
include considerations such as, for example, likely location, time
zone. A back-and-forth communication can occur. The user may accept
an answer provided by one or more of the experts. In an alternative
embodiment, the user may be deemed to have accepted the answer if
the user does not reject it. By accepting the answer, the user
validates the expert's answer which, in turn, may boost a score or
rating associated with the expert. The user may also pay the expert
for any accepted answers and may add a bonus. The user may also
leave positive, neutral or negative feedback regarding the expert.
More details regarding the consultation system 102 and its example
functions will be discussed in connection with FIG. 2 below.
[0025] The exemplary user client 106 is a device associated with a
user accessing the consultation system 102 (e.g., via a website,
telephone number, text message identifier, or other contact means
associated with the consultation system 102). The user may comprise
any individual who has a question or is interested in finding
answers to previously asked questions. The user client 106
comprises a computing device (e.g., laptop, PDA, cellular phone)
which has communication network access ability. For example, the
user client 106 may be a desktop computer initiating a browser for
access to information on the communication network 104. The user
client 106 may also be associated with other devices for
communication such as a telephone.
[0026] In exemplary embodiments, the expert client 108 is a device
associated with an expert. The expert, by definition, may be any
person that has, or entity whose members have, knowledge and
appropriate qualifications relating to a particular subject matter.
Some examples of expert subject matters include health (e.g.,
dental), medical (e.g., eye or pediatrics), legal (e.g.,
employment, intellectual property, or personal injury law), car,
tax, computer, electronics, parenting, relationships, and so forth.
Almost any subject matter that may be of interest to a user for
which an expert has knowledge and appropriate qualifications may be
contemplated. The expert may, but does not necessarily need to,
have a license, certification or degree in a particular subject
matter. For example, a car expert may have practical experience
working the past 20 years at a car repair shop. In some
embodiments, the expert may be a user (e.g., expert can post a
question).
[0027] The expert client 108 may comprise a computing device (e.g.,
laptop, PDA, cellular phone) which has communication network access
ability. For example, the expert client 108 may be a desktop
computer initiating a browser to exchange information via the
communication network 104 with the consultation system 102. The
expert client 108 may also be associated with other devices for
communication such as a telephone.
[0028] In accordance with one embodiment, an affiliate system 110
may be provided in the exemplary environment 100. The affiliate
system 110 may comprise an affiliate website or other portal which
may include some of the components of the consultation system 102
or direct their users to the consultation system 102. The affiliate
system 110 may also be associated with other devices for
communication such as a telephone. For example, the affiliate
system 110 may provide a website for a car group. A link or
question box may be provided on the affiliate website to allow
members of the car group to ask questions. Answers in response to
the questions may be provided, in part, from the consultation
system 102, or the member asking the question may be directed to
the consultation system 102 for the answer. The members may, in
some cases, only have access to certain categories or experts. In
one embodiment, a RSS feed may be used to feed data from the
consultation system 102 to the affiliate system 110. The users of
the affiliate system 110 may be tagged with the affiliate depending
on if and how the users are registered with the consultation system
102. It should be noted that the affiliate system 110 may comprise
any type or category of affiliate sites. In some cases, the
affiliate system 110 may involve questions being answered by the
affiliate or persons involved with the affiliate.
[0029] The environment 100 of FIG. 1 is exemplary. Alternative
embodiments may comprise any number of consultation systems 102,
user clients 106, expert clients 108, and affiliate systems 110
coupled together via any type of one or more communication networks
104, and still be within the scope of exemplary embodiments of the
present invention. For example, while only one consultation system
102 is shown in the environment 100, alternative embodiments may
comprise more than one consultation system 102. For instance, the
consultation systems 102 may be regionally established.
[0030] Referring now to FIG. 2, the consultation system 102 is
shown in more detail. In exemplary embodiments, the consultation
system 102 may comprise a load balancer 202 which distributes work
between two or more web servers 204 in order to optimize resource
utilization and minimize response time. In some embodiments, a
firewall 201 may be provided prior to the load balancer 202.
[0031] In exemplary embodiments, the web servers 204 are
responsible for accepting communications from the user client 106
(e.g., request or question) and expert client 108 (e.g., response)
and serving the response including data content. In some instances,
the request and response may be in HTTP or HTTPS which will result
in HTML documents and linked objects (e.g., images) being provided
to the user and expert clients 106 and 108. The communications may
include, for example, questions from the users, answers from the
experts, acceptance from the user, payment information, account
update information videos, documents, photographs and voice The web
server 204 will be discussed in more detail in connection with FIG.
3.
[0032] Information used by the web server 204 to generate responses
may be obtained from one or more database servers 206 and a file
server 208. The exemplary database servers 206 store data or are
coupled with data repositories storing data used by the
consultation system 102. Examples of data include user information
(e.g., username, email address, credit card or other payment
information), expert information (e.g., name, licenses,
certifications, education and work history), previously asked
questions and corresponding answers, and transaction information
(e.g., payment, accepts, etc.). Essentially any data may be stored
in, or accessed by, the database servers 206 including every user
and expert interaction with the consultation system 102. Examples
of interactions include how many questions the user has asked,
which experts provided answers to the questions, and whether the
user accepted the answers and paid the expert.
[0033] Content on the database servers 206 (or accessed by the
database servers 206) may be organized into tables, and the tables
may be linked together. For example, there may be one table for
every question that has been previously asked, another table for
posts (e.g., answers) to each question, and other tables for users
and experts. In one example of the present invention, over 430
tables or spreadsheets are linked together.
[0034] In some embodiments, the database servers 206 may include
logic to access the data stored in the tables. The logic may
comprise a plurality of queries (e.g., thousands of queries) that
are pre-written to access the data. For example, one query may be
directed to determining every question that a particular user has
asked. In this example, a user table may be searched based on this
query to determine the user's unique user name or identity. Once
the user name is determined, a question table may be accessed to
find all questions ever asked by a user having the particular user
name.
[0035] It should be noted that the functions of the database server
206 may be embodied within the web server 204. For example, the
database servers 206 may be replaced by database storage devices or
repositories located at the web servers 204. Therefore, any
reference to the database server 206 and database storage device
are interchangeable. Alternatively, some or all of the query logic
may be embodied within the web server 204.
[0036] In exemplary embodiments, a plurality of database servers
206 is provided. The plurality of database servers 206 may share
data and thus be identical (or close to being identical). By having
identical database servers 206, load balancing and database backup
may be provided. For example, if two database servers 206 are
embodied in the consultation system 102, then half of the data
accesses or queries may be directed to one database server 206 and
the other half to the second database server 206.
[0037] The file server 208 stores or accesses files such as, for
example, pictures, videos, voice files, PDF documents, Word
documents, and PowerPoint presentations. When a particular file is
requested or required in order to generate a response, the web
server 204 may query the file server 208 for the file.
Alternatively, the files may be stored at the database server 206
or other database storage devices, for example.
[0038] An application server 210 may also be provided in the
consultation system 102. The application server 210 may provide
applications and functions that are centralized to the consultation
system 102. For example, the application server 210 may perform
credit card processing with a bank that is coupled to the
consultation system 102 via a network (e.g., the communication
network 104).
[0039] It should be appreciated that in alternative embodiments,
the consultation system 102 may include fewer or more components
than shown in FIG. 2. For example, the consultation system 102 may
comprise any number of web servers 204, database servers 206, file
server 208, and application server 210. In another example, the
file server 208 and application server 210 may be removed from the
consultation system 102 and their functions performed by other
servers in the consultation system 102. It will also be appreciated
that the various servers may be embodied within each other and/or
the consultation system 102 may be embodied within a single server.
For example, the database server 206 may be embodied, as a storage
device within the web server 204. It is also noted that the various
servers of the consultation system 102 may be geographically
dispersed within the exemplary environment 100.
[0040] Referring now to FIG. 3, one of the exemplary web servers
204 is shown in more detail. As discussed, the web servers 204
share in the workload in order to provide optimized performance. As
such, each of the web servers 204 will include similar engines and
modules. In the exemplary embodiment of FIG, 3, the web server 204
comprises a graphical interface engine 302, an accounts engine 304,
a consultation analysis engine 306, an expert verification engine
308, a quality control engine 310, and a payment engine 312
communicatively coupled together.
[0041] The exemplary graphical interface engine 302 generates
graphical representations provided via the web page. In exemplary
embodiments, the graphical interface engine 302 builds a page
(e.g., made up of HTML, Javascript, CSS, sound, video, images, and
other multimedia) that is presented to the user client 106 or
expert client 108. The page comprises static text (e.g., "Welcome
to JustAnswer.") and dynamic data (e.g., "Hello, hulagirl. You
joined 3 months ago; have asked 17 questions; have accepted 12
answers."). The dynamic data may be obtained, at least in part,
from the database servers 206. In exemplary embodiments, the
dynamic data may be retrieved using querying logic associated with
the web server 204, the database server 206, or a combination of
both, as discussed above.
[0042] The exemplary accounts engine 304 sets up and maintains user
accounts with the consultation system 102. Initially, the accounts
engine 304 may provide a registration page via the graphical
interface engine 302 for an individual (e.g., a user or expert) to
fill out. The information collected via the registration page may
be stored in the database server 206. Examples of information
include username, email address, and billing and payment
information. With respect to experts, the accounts engine may also
collect information regarding the identity of the expert,
information on credentials (e.g., license and certification
numbers, degrees including university attended and years of
attendance, employment history), and other data relating to the
expert and the expert's application. Accounts for users may be
automatically established and activated based on certain actions
taken by the user, such as asking a question, agreeing to the terms
of the consultation system, or providing payment. However, experts,
in accordance with exemplary embodiments, proceed through an
acceptance and verification process. If accepted, an expert account
may then be established and activated by the accounts engine 304.
The verification process will be discussed in more detail
below.
[0043] The consultation analysis engine 306 manages answers in
response to questions which have been posted to the consultation
system 102. In exemplary embodiments, the consultation analysis
engine 306 will receive questions along with indications of a
category or subject matter each question is directed to from users.
In various embodiments, a user may utilize a question page to enter
a question which the user wants an expert to answer. The question
page may provide a field for entering the question, relevant
information relating to the question (e.g. make and model of a
car), as well as a selection box for selecting a subject matter
expert under which the question should be posted to. In exemplary
embodiments, other pages may be presented to the user before or
after the question is submitted to experts, to obtain further data
from or provide data to the user. For example, a question regarding
how to change the battery in a specific type of car may be
categorized as a car question or a question for that specific type
of car. In some embodiments, the question will then be posted to a
car care portion (e.g., car care web pages) of the consultation
system 102. The question is also recorded into a corresponding
table in the database server 206 (e.g., in a question table) and
the user name of the user may also be entered into a corresponding
table (e.g., user table). In some instances, the question may be
outputted back to the user so that the user may confirm the
question or edit the question if needed. The user may also provide
an amount that the user is willing to pay for an accepted answer,
in some embodiments, as an amount selected by the user from
different options offered to the user.
[0044] Once the question is posted on the consultation system 102,
experts may provide answers in response to the question. The
questions may be posted or otherwise communicated to a general or
subject matter specific question list of recent questions that have
been posted by users, a more specific group of experts, or certain
experts one-at-a-time. In various embodiments, the question list
may be sorted by certain types of information such as time of
posting, the amount the user is willing to pay (e.g., value), the
user's history of accepting previous answers, information regarding
the subject matter of the question, or whether replies have been
previously posted. Experts may periodically review the question
list or other communications alerting them to questions to
determine if there are any questions that the expert would like to
answer. The expert may base their determination, in part, on the
complexity of the question, their expertise, the amount the user is
willing to pay for an answer, or the user's history of accepting
previous answers. In various embodiments, the user is able to place
a deposit and name a price for an answer when posting the question
or place the deposit after an expert has answered.
[0045] Should the expert decide to answer a question or request
further information, depending on factors including location of the
user and expert on the consultation system, the most convenient or
preferred method of communication of the user or expert, or the
original method of the user asking the question, an indication is
provided to the user that there is an answer being offered or a
request for further information, sometimes in the form of the
answer or request itself. The indication may also comprise an
e-mail, text message, or pop-up notification to the user. In some
cases, the user may place a deposit (e.g., the amount agreed upon
to be paid if an answer is accepted) after being given the
opportunity to view a profile of the expert offering the answer or
a portion of the answer.
[0046] The answer is provided to the user. The answer may be
displayed on a web page (e.g., an answer page), provided via a chat
session, provided via a voice or text message, provided via video,
provided by a software application, provided by other social media
means (e.g., social networking sites where the user has a personal
profile or page), or provided by telephone, mobile phone, or VoIP.
Upon review of answers posted in response to a question, the user
decides if any of the answers are acceptable to the user. The user
may accept one or more answers that are posted. In exemplary
embodiments, the user will pay the expert posting any accepted
answers. If a particular answer is exceptional, in exemplary
embodiments, the user may also provide a bonus to the expert
providing the exceptional answer. When the user accepts an answer,
monies from the deposits may also be paid to a host of the question
and answers platform (e.g., host of the consultation system
102).
[0047] In various embodiments, different pricing options may be
used for determining what a user may pay for getting an answer to a
question or what an expert may be paid for providing an answer. In
one embodiment, the pricing options may vary for each category or
subcategory based on a variety of factors. These factors may
include, for example, question length, time of day, day of week,
location, or the ability of a user to pay. Additionally, discounts
may be offered (e.g., two for one, ask one question get second for
50% off, free for pro bono users). In other embodiments, pricing
may be selected and paid for by third-parties (e.g. employers of
the users). In yet other embodiments, a user may subscribe to a
subscription plan (e.g., unlimited questions each month for a
particular fee or up to 10 questions each month for another fee).
In other embodiments, a user or expert may be allowed to adjust the
price prior to, during, or after the interaction between the user
and the expert.
[0048] Acceptance and non-acceptance actions are tracked by the
consultation analysis engine 306. For example, every user's
accept-to-question ratio may be tracked and may be published to
experts. Thus, if the ratio is low, experts may not answer the
user's questions in the future. Furthermore, the user's question
posting privileges may be suspended or the user may be removed from
the consultation system 102 if the ratio is low or falls below a
ratio threshold. The tracked acceptance and non-acceptance
information is stored to the database server 206, and may be used
to evaluate the quality of the experts as is discussed herein.
[0049] The user may also provide comments and feedback after
viewing or accepting one or more answers. The feedback may be
provided as, for example, a written comment, star rating, numerical
scale rating, or any other form of rating. The feedback is stored
to the database server 206, and may be used in the quality control
processing. User satisfaction surveys may also be sent to collect
data on the user's experience with the site, the expert, or the
answer the user received.
[0050] According to some embodiments, if the question has been
previously answered, a query of the database server 206 may be
performed. The answers to previously asked questions may be stored
in corresponding answer tables in the database server 206. These
embodiments may occur when, for example, a user searches (e.g.,
using Google) for previous questions and answers. Multiple
instances of access to the same questions and/or answers may be
provided via a cache. Some or all users may also be allowed to
search some or all previous questions or answers via a search tool
on the website, or some or all previous questions or answers may be
displayed to users at the discretion of the host, affiliate, or
expert of the consultation system.
[0051] The exemplary expert verification engine 308 performs
verification and acceptance of experts. In accordance with
exemplary embodiments, the expert verification engine 308 verifies
information provided by the potential experts (or experts) or
receives verification data used to verify the experts' identities
or credentials. The verification may occur prior to allowing the
expert to join the consultation system 102. Alternatively, the
verification may occur any time after the expert has joined the
consultation system 102. The verification engine 308 will be
discussed in more detail in connection with FIG. 4 below. More than
one verification may be performed for each expert, by requirement
or by the expert's choice.
[0052] In exemplary embodiments, the quality control engine 310
evaluates experts in order to promote the high quality of experts
in the consultation system 102. The evaluation may comprise scoring
or ranking experts based on various elements. For example, the
quality control engine 310 may access and review feedback
associated with each expert and score each expert accordingly. The
quality control engine 310 may also review other factors which may
increase or decrease an expert's score or ranking The quality
control engine 310 will be discussed further in connection with
FIG. 5.
[0053] The exemplary payment engine 312 manages the payment of
fees. In accordance with exemplary embodiments, users pay experts
for accepted answers to their questions, for example, by way of
payments per questions, payments per answers, payments per time
frame, or payments on subscription basis. In some instances, the
user may provide a deposit in order to view answers prior to
accepting the answers. The payment engine 312 may maintain a record
of all these transactions. Additionally, the payment engine 312 may
work with the application server 210, if provided, to process
payments (e.g., credit card processing, PayPal processing).
[0054] Referring now to FIG. 4, the exemplary expert verification
engine 308 is shown in more detail. The expert verification engine
308 verifies information provided by the potential experts (or
experts) or receives verification data that verifies the experts'
identities or credentials. The consultation system 102 may, in some
embodiments, only accept experts once verified. In exemplary
embodiments, the expert verification engine 308 comprises an
identity verification module 402, a credential verification module
404, a testing module 406, and an acceptance module 408
communicatively coupled together. Alternative embodiments may
comprise other modules as needed depending on the type of
information to be verified (e.g., background or reference check
module).
[0055] The identity verification module 402 manages verification of
identity information provided by the potential expert (or expert).
For example, the potential expert may provide one or more of a
name, address, date of birth, full or partial or indicator of a
social security number, and/or passport number. In some
embodiments, the identity verification module 402 may access
external databases (e.g., credit bureau databases or other third
party ID verification systems) to check the entered information. In
some embodiments, the identify verification information may be XML
fed to a third party system. Additionally, the third party system
or the consultation system 102 may provide identity test questions
(e.g., in the form of multiple choices) or other checks to help
confirm the identity of the applicant (e.g., potential expert).
Such questions may include, for example, a year the applicant moved
into their property and initials of a person with whom the
applicant shares his current address. Essentially, any question
that is known by the applicant (and relatively few others) may be
used. Additionally or alternatively, some of this information may
be verified manually (e.g., a copy of the driver's license,
professional license, or passport is reviewed, or credit card name
check is performed) and the identity verification module 402
receives the manual verification data and uses the manual
verification data to verify the identity. If the identity of the
applicant is not confirmed initially, the applicant may be given an
opportunity to correct and resubmit the information, other
processes involving the third party ID verification systems may be
used, other internal manual ID verification processes may be used,
or the applicant may be rejected.
[0056] The exemplary credential verification module 404 manages
verification of credential information provided by the potential
expert (or expert). Credential information may include, for
example, licenses, certifications, employment history, and
educational degrees. In some embodiments, the credential
verification module 404 determines whether to send the credential
information, as well as which credential information to send, to
one or more credential verification systems. The determination may
be based in part on whether the applicant meets the minimum
requirements and standards of the consultation system 102 or
category based on their credential information. The potential
expert may have an opportunity to review these minimum requirements
prior to applying. The minimum requirements may be based on, for
example, characteristics of other experts in the category (e.g.,
work experience, licenses, certifications). Thus, for example, the
entered credential information may be compared to characteristics
of other successful experts on the consultation system 102. The
determination may further be based on the applicant's performance
on a test presented by the testing module 406, whether the ID
verification is successful, and whether there is a need for that
type of expert (or more of that type of expert). For example, there
may be a limit placed on a number of experts allowed within a
particular category, which may change over time. The credential
verification module 404 may access external databases (e.g.,
credential verification systems such as a state bar association
database or university database) to verify the credential
information either directly or through a third-party verification
system. The credential information may also be verified manually
(e.g., an agent associated with the consultation system 102 may
call a university), and the manual verification data is received by
the credential verification module 404 and uses the manual
verification data to verify the credentials.
[0057] The testing module 406 may be used to provide subject
specific tests to potential experts in order to evaluate their
competence in a subject matter with which each potential expert
wants to be associated. The subject specific tests may be a
multiple choice quiz and/or a writing test, and may also be given
to existing experts as well as potential experts. These subject
specific tests may be scored either automatically or manually. A
test threshold may be utilized whereby if the potential expert
scores below a threshold, the potential expert will not be accepted
by the consultation system 102, and if the potential expert scores
above the test threshold, then the potential expert is more likely
to be accepted by the consultation system 102. The testing module
406 may also provide site user tests to potential and existing
experts in order to evaluate their knowledge of how to use the
site. The results of test given to existing experts may be used to
suspend or remove experts that perform poorly on the test, or
experts may be allowed to take the test several times until they
attain a 100% passing score. Other tests may also be provided by
the testing module 406, for example, customer service skills or
psychometric tests.
[0058] The acceptance module 408 determines whether to accept a
potential expert and activate or, in the case of an existing expert
expand an associated account. In some embodiments, if the identity
and at least a portion of the credential information is verified,
then the acceptance module 408 may accept the potential expert and
activate the account. In some embodiments, the potential expert may
also need to pass a threshold on a subject matter, writing, site
user and/or other test to be accepted. In some embodiments, the
acceptance module 408 may also determine whether to accept a
potential expert and activate an associated account based on the
ratio of asked and answered questions on the site and/or
measurement of time before questions are being answered. Activation
of the account allows the expert to begin posting answers on the
consultation system 102 as well as to receive payment for their
accepted answers.
[0059] Referring now to FIG. 5, the exemplary quality control
engine 310 is shown in more detail. The quality control engine 310
evaluates experts in order to maintain quality in the consultation
system 102. The evaluation may comprise scoring or ranking experts.
The quality control engine 310 may comprise a user feedback module
502, a peer feedback module 504, an adjustment module 506, and an
evaluation module 508 communicatively coupled together. Further
quality control modules may be provided as needed to incorporate
other factors which may be used to score or rank experts, such as
expert and answer characteristics and statistics, and third-party
sources of information and feedback.
[0060] The user feedback module 502 manages feedback based on
users' experiences with experts. The user feedback may include
direct feedback such as, for example, written comments provided by
users, a positive/neutral/negative scoring, complaints,
compliments, and user surveys. Indirect feedback may also be
included in the user feedback. Examples of indirect feedback
include how often users accept an expert's answer, give bonuses to
experts, request refunds, choose to receive answers from or not
receive answers from the expert (e.g., does not want to receive any
responses from the expert in the future), directly or indirectly
rate an expert's viewable profile or background, and how often
users return to ask another question after receiving an answer from
the expert.
[0061] The peer feedback module 504 manages feedback provided by
other experts on the consultation system 102. For example, a first
expert may file a positive or negative report on a second expert or
the second expert's answer. The report may indicate whether the
first expert agrees with the posted answer of the second expert,
the reason for the agreement or disagreement, or a new model
answer. The report may indicate the type of problem being reported
(e.g., whether the report is being submitted due to a problem with
the correctness or completeness of an answer, an unprofessional
remark or tone, or potential violations of the law or applicable
agreements). In some embodiments, additional peer review may be
solicited and/or provided regarding the report filed by the first
expert. In some embodiments, the first and second experts may have
an opportunity to correspond with one another, for example, by the
second expert agreeing with the first expert's report or filing a
refutation of the report, and by the first expert responding or
agreeing to withdraw the report. Peer feedback may also include
experts scoring randomly, systematically, or manually selected
anonymized or non-anonymized answers posted on the consultation
system 102. Expert quality surveys may be periodically conducted in
certain categories regarding the best or worst experts in terms of
quality and peer-to-peer interactions. In some embodiments, the
experts solicited for their additional peer review may be selected
at random, based on their own characteristics, by vote of their
peers, or by a system of points or other measurements obtained
through the peer feedback module 504. In some embodiments, the
experts may be allowed to identify any other experts as the best or
worst experts in terms of quality and peer-to-peer interactions. In
some embodiments, third-party non-users of the site, for example,
affiliate persons or entities, professors of the same subject
matter as the category of answers or experts, or others may also
provide input into reviews or rankings of the characteristics of
answers or experts.
[0062] The exemplary adjustment module 506 manages other factors
which may adjust the score or rank of the experts. These factors
may include public, miscellaneous actions associated with the
consultation system 102. The actions may include, for example,
number of years on the consultation system 102, awards and titles
(e.g., mentor, moderator, arbitrator) received on the consultation
system 102, uniqueness of posts, time between user question and
expert response, number of links in posts, and data associated with
the post. The data associated with the post may include analysis of
the number of words in a post, number of answers posted before an
acceptance of a post is received, and spelling and grammar in
posts, for example. Other factors may also include number of years
in the expert's profession and number of licenses, certifications,
or other credentials obtained by the expert.
[0063] Miscellaneous actions may also include non-public actions
(e.g., actions which may not be evident to users). For example, the
expert may take more shares of non-paying or new users, thus taking
a bigger monetary risk. The expert may also move questions posted
in a wrong category to a correct category. In another example, the
expert may assist with media, marketing, and public relations
efforts (e.g., speaking to the press). The expert may also be more
or less professional and polite in her interactions with other
experts on the site, and more or less act in accordance with the
mission and values of the consultation system. Almost any type of
factor that can affect the scoring or ranking of experts may be
utilized, and the above provided factors are only examples.
[0064] The exemplary evaluation module 508 evaluates the experts
and outputs a useable result. The evaluation may be based on user
feedback, peer feedback, adjustment factors, other factors, or any
combination of these. In some embodiments, the evaluation module
508 may generate two results: a public result and an internal
result. The public result may be viewable by the public or at least
other experts, and may be driven more by user and peer feedback.
The internal result may not be viewable by the public, but may be
used by the consultation system 102 for internal functions. For
example, the internal result may be used to warn or remove the
lowest scoring experts in the category (e.g., based on providing
poor responses, not interacting professionally or politely with
others, or violating site policies). In another example, the
internal result may be used to determine an amount that an expert
may be paid for posting accepted answers (e.g., the better the
score, the better the pay amount). In exemplary embodiments, the
internal result may be driven more by factors associated with the
adjustment module 506 or other factors. The results may be provided
graphically or numerically, in summary fashion or specifically, and
in relation to other experts or other categories or not.
[0065] In some embodiments, conditions may be automatically or
manually set to limit functions of experts. For example, a new
expert in a category may not be allowed to post a response after a
senior expert (e.g., expert having been on the consultation system
102 longer) has already posted a response. Additionally, peer
review reporting privileges of a new expert may be withheld until
the new expert reaches a certain threshold of questions answered,
responses accepted, or time on the consultation system 102.
Alternatively, peer review reporting privileges of non-new experts
may be revoked if the non-new expert files too many reports that
have been disagreed with by other experts. In another example,
experts may be limited to only a set number of questions per day
that they can respond to in order to encourage quality of answers
as opposed to quantity of answers.
[0066] FIG. 6 is a flowchart of an exemplary method 600 for
accepting an expert. The expert, by definition, may be any person
that has knowledge on, and the appropriate qualifications to answer
questions relating to, a particular subject matter. Exemplary
embodiments of the present invention allow accepted experts to post
answers to questions or otherwise provide answers to users of the
consultation system 102. In order to be accepted, application and
registration information is initially received from a potential
expert by the accounts engine 304 at operation 602. The
registration information may include name, contact information,
other identifying information, education, licenses, certifications,
and experiences. The potential expert may also indicate what
category or categories to which the potential expert wants to be
admitted. Alternatively, the accounts engine 304 may determine and
suggest one or more categories best suited for the expert based on
credential information (e.g., education, licenses, certifications).
For example, the credential information may be compared with the
minimum requirements for categories to determine the categories
best suited for the expert. In one embodiment, the potential expert
may create a profile based on the entered registration information.
Examples of expert registration pages are shown in FIG. 8-FIG.
11.
[0067] The potential expert may be provided a subject matter test,
writing test, site user test, customer service skills test, or
other type of test by the testing module 406. The tests may be
multiple choice, written, oral, or any combination thereof. In some
embodiments, the potential expert may be associated with a general
category or a category that does not have a subject matter test. In
these embodiments, a test may not be necessary. It should be noted
that testing may be optional. If the potential expert does not pass
the test, then a notice is provided to the potential expert. In
some cases, the potential expert may be given a certain number of
chances to pass the test, or may be allowed to take the test at a
later date.
[0068] If the potential expert passes the test at operation 604, or
in some embodiments, simply after the potential expert takes the
test at operation 604, then at operation 606, the identity of the
potential expert is verified. In exemplary embodiments, the
identity verification module 402 manages the verification of the
identity. The verification may involve receiving copies of
government-issued identification, licenses, or passports or
accessing various databases to check provided identity information.
The verification may be based, in part, on personal information of
the potential expert such as name, address, or date of birth. In
some embodiments, the verification is performed by a third party ID
verification system.
[0069] Credentials are verified at operation 608. The credential
verification module 404 manages the verification of credentials
including licenses, certifications, educational degrees, awards,
patents, publications, and work experiences. In some embodiments,
the potential expert provides credential information after their
identity is verified or after the test is passed. The credential
verification module 406 may access or receive information from
external databases (e.g., government or university databases) to
verify credentials, or forward the information to a third party
verification system for external verification.
[0070] At operation 610, a determination is made as to whether to
accept the potential expert. Determination at operation 610 may be
performed by the acceptance module 408. The determination may be
based on test results, qualifications, the application, identity
verification, verification of one or more credentials, or any
combination thereof. In some embodiments, one or more thresholds
may be established which needs to be exceeded in order for the
potential expert to be accepted. For example, various combinations
of test scores and number/type of verified credentials thresholds
may be established, and a potential expert must exceed at least one
of these thresholds to be accepted. If accepted, an account is
activated or expanded for the expert at operation 612. If the
potential expert does not exceed the threshold, then the potential
expert is not accepted or given expanded access to questions and a
rejection notification may be provided at operation 614.
[0071] FIG. 7 is a flowchart of an exemplary method 700 for expert
quality control in the consultation system 102. The expert quality
control may comprise scoring or ranking experts based on various
feedback and factors. The scoring or ranking may be shown to users,
shown to the expert involved, shown to other experts with or
without attribution to the scored or ranked expert, and used
internally by the consultation system. The results of the scoring
or ranking may then be used to determine the quality of the experts
associated with the consultation system 102 or other pieces of the
consultation system including the application and verification
process and pricing.
[0072] At operation 702, user feedback is received for each expert
posting answers on the consultation system 102 in response to a
question provided by a user. The user feedback may include direct
feedback such as, for example, written comments provided by users,
a positive/neutral/negative scoring, complaints, compliments, and
user surveys. Indirect feedback may also be included in the user
feedback. Examples of indirect feedback include how often users
accept an expert's answer, give bonuses to experts, request
refunds, opt-out of answers from the expert, and positively rated
profiles, and how often users return to ask another question after
receiving an answer from the expert. The profile rating is based on
a viewable profile of the expert.
[0073] Peer feedback from other experts on the consultation system
102 is received at operation 704. For example, a first expert may
file a positive or negative report (also referred to as a "peer
report") on a second expert or the second expert's answer. The peer
report may indicate whether the first expert agrees with the posted
answer of the second expert, the reason for the agreement or
disagreement, and a new model answer. The peer report may indicate
whether it is being submitted due to a problem with the correctness
or completeness of an answer, an unprofessional remark or tone, or
violations of the law or applicable agreements (e.g., potential
copyright infringement). In some embodiments, additional peer
review may be solicited and/or provided regarding the report filed
by the first expert. In some embodiments, the first and second
experts may have an opportunity to correspond to one another, for
example, by the second expert agreeing with the first expert's
report or filing a refutation of the report, and by the first
expert responding or agreeing to withdraw the peer report. Peer
feedback may also include experts scoring randomly or manually
selected anonymized or non-anonymized answers posted on the
consultation system 102.
[0074] In some embodiments, the peer report may be provided to the
expert being reported on. For example, a report page may be
accessible by the expert to view all peer reports submitted about
them. The peer reports may be organized, for example, by date,
question answered, answer, and type of report. For each peer
report, the expert may agree with the peer report or refute the
peer report. In addition, an author of a report may retract a
report after having reviewed a refutation of the report.
[0075] In some embodiments and for some types of reports, a
point/strike system may be implemented in peer review. For example,
when a peer report is received that pertains to an incorrect answer
given by an expert, the expert may (1) do nothing and receive three
strikes unless or until the expert decides to agree to or refute
the peer report; (2) agree with the peer report resulting in one
strike; or (3) oppose the peer report. In the third case, a panel
of reviewers (e.g., three reviewers) may then be selected to review
the peer report and disputed answer.
[0076] The panel may be randomly chosen from other experts based
on, for example, a number of points the experts have. In one
example, the potential reviewer may see a pop-up screen reciting
"Would you please review an Incorrect/Incomplete Answer report?"
The potential reviewer can select "Yes, right now," "Yes, within
the next 24 hours," or "No thanks". If "Yes, right now" is
selected, the peer report is displayed and the reviewer will have
30 minutes to provide their input on the peer report. If "Yes,
within the next 24 hours" is selected, an icon will appear on a
reviewer's header tool bar for the next 24 hours. When the icon is
clicked, the peer report is displayed, and the reviewer will have
30 minutes to rule on the peer report. If "No thanks" is selected,
the same pop-up will appear to another randomly selected potential
reviewer. If a reviewer does not provide input within 30 minutes
after opening the report to review, a message that their 30-minute
window has expired will appear, and their ability to provide their
input will go away. In one embodiment, the reviewer will have to
agree to an "oath" before reviewing the peer report that states
that their input is provided in good faith and solely based upon
the correctness and completeness of the answer.
[0077] In some embodiments, the reviewers may have two choices for
input. The reviewer can agree there is a problem with the
incorrect/incomplete answer, or the reviewer may decide there is no
substantial problem with the correctness/completeness of the
answer. The reviewers may also be asked to provide at least a one
sentence reason for their input.
[0078] Points and strikes may be awarded based on the outcome of
the panel review. For example, if two of the three reviewers find
the peer report fully warranted, then the reporter (e.g., the
expert that filed the peer report) may receive two points and the
author (e.g., the expert that provided the answer) may receive two
strikes. However if all three reviewers find the report fully
warranted, then the reporter may receive three points and the
author may receive three strikes. Alternatively, if the majority of
reviews find the report unwarranted, then the report is nullified.
Furthermore, if two of three reviewers find the report unwarranted,
the reporter may get deducted two points. If all three reviewers
find the report unwarranted, the reporter may get deducted three
points. Additionally, reviewers voting in the majority with the
panel may receive three points, while a reviewer voting in the
minority may be deducted one point. In other embodiment, if two of
three reviewers find that a report is rude or unprofessional, the
author of the report may be deducted two points. However, if all
three reviewers find the report is rude or unprofessional, the
author of the report may be deducted three points.
[0079] Accordingly, experts whose points add up to a negative
number after submitting or ruling on at least three peer reports
may be "benched" or barred from reporting or reviewing for a period
of time (e.g., 100 accepts or 1 month). In a further example,
experts whose points add up to a negative number after submitting
or ruling on at least nine peer reports may be benched from
reporting or reviewing for a longer period of time (e.g., 600
accepts or 6 months). While "benched" experts can continue to file
peer reports, the peer reports may not trigger any consequence or
process.
[0080] Additionally, any authors whose opposition to a peer report
is agreed with by the majority of reviewers three times or more may
be "safe" from the peer input system for a period of time (e.g.,
another 100 answers or 1 month).
[0081] It should be noted that the peer review method is described
in an exemplary embodiment. Other embodiments may use a different
number of panel members, provide a different response time limit,
use different or fewer or more report types, apply different
standards and methods for experts or other parties to review
reports, apply different versions of anonymity or lack of
anonymity, apply different selection criteria for answers or
experts to be reviewed or of experts or other parties to review the
reports, and apply a different point/strike scheme.
[0082] At operation 706, other factors which may adjust the score
or rank of the experts are recorded. These factors may include
miscellaneous actions associated with the consultation system 102
(e.g., number of years on the consultation system 102, awards and
titles received on the consultation system 102, uniqueness of
posts, number of links in posts, number of characters in posts, and
data associated with the post). The factors may also include number
of years in the expert's profession and number of licenses,
certifications, and other credentials obtained by the expert.
[0083] Miscellaneous actions may also include non-public actions
performed by the expert which may be beneficial to the consultation
system 102. For example, the expert may take more shares of
non-paying or new users, move questions posted in a wrong category
to a correct category, or assist with media, marketing, or public
relations outreach. Almost any type of factor that can affect the
scoring or ranking of experts may be recorded and/or tracked.
[0084] At operation 708, the quality control analysis is performed
and useable results outputted. The quality control analysis may be
based on user feedback, peer feedback (e.g., reports, points and
strikes), adjustment factors, other factors, or any combination of
these. In some embodiments, the evaluation module 508 may generate
two results: a public result (e.g., viewable by the public or at
least other experts) and an internal result (e.g., used by the
consultation system 102 to maintain quality). In exemplary
embodiments, the public result may be driven more by user and peer
feedback while the internal result may be driven more by factors
associated with the adjustment module 506.
[0085] At operation 710, the results of the quality control
analysis are used for expert quality determination and control. In
some embodiments, the public (or visible-to-other-experts) result
may be presented, for example, on a website associated with the
consultation system 102. For instance, a score or ranking may be
provided with an expert profile either graphically or numerically,
in summary fashion or specifically, and in relation to other
experts or other categories or not. Users may then view the score
or ranking in determining whether to accept an answer provided by
the expert. In other embodiments, the internal results may be used
to maintain quality on the consultation system 102 in a non-public
manner. For example, the consultation system 102 may limit the
number of experts in a category by using the internal result to
remove the lowest scoring experts in the category. In another
example, the internal result may be used to determine a base amount
or percentage of a user's payment that an expert may be paid for
posting accepted answers. In some embodiments, the results of the
quality control analysis may be used to assist the expert in
self-monitoring or self-improvement.
[0086] FIG. 8 is a screenshot of an example of a portion of the
expert registration landing page(s) of the consultation system 102.
The expert registration landing page(s) may be provided by the
graphical interface engine 302 to the expert client 108. As shown,
the expert registration landing page(s) provides information on the
application process and access to requirements for categories, as
well as the benefits of being an expert. In the present example,
the potential expert has selected a "legal experts" category. As a
result, requirements are displayed which indicate that the
potential expert be an attorney, barrister, or solicitor that is
licensed, active, and in good standing. Should the potential expert
decide to apply, in some embodiments, the potential user is taken
to pages where the potential expert can input personal information,
select a category, create a profile, take a test, verify their
identity, to describe why they want to be admitted as an expert in
the category, and provide credential information.
[0087] FIG. 9 illustrates an example of a portion of an expert
category selection page, which may or may not be included in the
application process. The potential expert may select more than one
category.
[0088] FIG. 10 is an example of a portion of an identity
verification page. The identity verification page provides, in some
embodiments, identity test questions (e.g., in the form of multiple
choices) to help confirm the identity of the applicant (e.g.,
potential expert). While certain questions are displayed in the
example page of FIG. 10, any question that is known by the
applicant (and relatively few others) may be used.
[0089] FIG. 11 is an example of a portion of a credential
verification page. On this example page, the potential expert
selects the category for which they are providing credentials (or
it may be pre-populated by the consultation system 102). The
potential expert may be asked to write a response to a question
about why he or she wants to be an expert. License and
certification details are also requested (not shown in displayed
portion of the credential verification page).
[0090] It should be noted that FIG. 8-FIG. 11 are examples and
alternative embodiments may request more, less, or other
information from the potential expert or present registration
questions, verification questions, or tests in a different
manner.
Modules, Components, and Logic
[0091] Certain embodiments described herein may be implemented as
logic or a number of modules, engines, components, or mechanisms. A
module, engine, logic, component, or mechanism (collectively
referred to as a "module") may be a tangible unit capable of
performing certain operations and configured or arranged in a
certain manner. In certain exemplary embodiments, one or more
computer systems (e.g., a standalone, client, or server computer
system) or one or more components of a computer system (e.g., a
processor or a group of processors) may be configured by software
(e.g., an application or application portion) or firmware (note
that software and firmware can generally be used interchangeably
herein as is known by a skilled artisan) as a module that operates
to perform certain operations described herein.
[0092] In various embodiments, a module may be implemented
mechanically or electronically. For example, a module may comprise
dedicated circuitry or logic that is permanently configured (e.g.,
within a special-purpose processor, application specific integrated
circuit (ASIC), or array) to perform certain operations. A module
may also comprise programmable logic or circuitry (e.g., as
encompassed within a general-purpose processor or other
programmable processor) that is temporarily configured by software
or firmware to perform certain operations. It will be appreciated
that a decision to implement a module mechanically, in the
dedicated and permanently configured circuitry or in temporarily
configured circuitry (e.g., configured by software) may be driven
by, for example, cost, time, energy-usage, and package size
considerations.
[0093] Accordingly, the term module should be understood to
encompass a tangible entity, be that an entity that is physically
constructed, permanently configured (e.g., hardwired), or
temporarily configured (e.g., programmed) to operate in a certain
manner or to perform certain operations described herein.
Considering embodiments in which modules or components are
temporarily configured (e.g., programmed), each of the modules or
components need not be configured or instantiated at any one
instance in time. For example, where the modules or components
comprise a general-purpose processor configured using software, the
general-purpose processor may be configured as respective different
modules at different times. Software may accordingly configure the
processor to constitute a particular module at one instance of time
and to constitute a different module at a different instance of
time.
[0094] Modules can provide information to, and receive information
from, other modules. Accordingly, the described modules may be
regarded as being communicatively coupled. Where multiples of such
modules exist contemporaneously, communications may be achieved
through signal transmission (e.g., over appropriate circuits and
buses) that connect the modules. In embodiments in which multiple
modules are configured or instantiated at different times,
communications between such modules may be achieved, for example,
through the storage and retrieval of information in memory
structures to which the multiple modules have access. For example,
one module may perform an operation and store the output of that
operation in a memory device to which it is communicatively
coupled. A further module may then, at a later time, access the
memory device to retrieve and process the stored output. Modules
may also initiate communications with input or output devices and
can operate on a resource (e.g., a collection of information).
Exemplary Machine Architecture and Machine-Readable Medium
[0095] With reference to FIG. 12, an exemplary embodiment extends
to a machine in the exemplary form of a computer system 1200 within
which instructions for causing the machine to perform any one or
more of the methodologies discussed herein may be executed. In
exemplary embodiments, the computer system 1200 may be any one or
more of the user client 106, the expert client 108, affiliate
system 110, and servers of the consultation system 102. In
alternative exemplary embodiments, the machine operates as a
standalone device or may be connected (e.g., networked) to other
machines. In a networked deployment, the machine may operate in the
capacity of a server or a client machine in server-client network
environment, or as a peer machine in a peer-to-peer (or
distributed) network environment. The machine may be a personal
computer (PC), a tablet PC, a set-top box (STB), a Personal Digital
Assistant (PDA), a cellular telephone, a web appliance, a network
router, a switch or bridge, or any machine capable of executing
instructions (sequential or otherwise) that specify actions to be
taken by that machine. Further, while only a single machine is
illustrated, the term "machine" shall also be taken to include any
collection of machines that individually or jointly execute a set
(or multiple sets) of instructions to perform any one or more of
the methodologies discussed herein.
[0096] The exemplary computer system 1200 may include a processor
1202 (e.g., a central processing unit (CPU), a graphics processing
unit (GPU) or both), a main memory 1204 and a static memory 1206,
which communicate with each other via a bus 1208. The computer
system 1200 may further include a video display unit 1210 (e.g., a
liquid crystal display (LCD) or a cathode ray tube (CRT)). In
exemplary embodiments, the computer system 1200 also includes one
or more of an alpha-numeric input device 1212 (e.g., a keyboard), a
user interface (UI) navigation device or cursor control device 1214
(e.g., a mouse), a disk drive unit 1216, a signal generation device
1218 (e.g., a speaker), and a network interface device 1220.
Machine-Readable Medium
[0097] The disk drive unit 1216 includes a machine-readable medium
1222 on which is stored one or more sets of instructions 1224 and
data structures (e.g., software instructions) embodying or used by
any one or more of the methodologies or functions described herein.
The instructions 1224 may also reside, completely or at least
partially, within the main memory 1204 or within the processor 1202
during execution thereof by the computer system 1200, the main
memory 1204 and the processor 1202 also constituting
machine-readable media.
[0098] While the machine-readable medium 1222 is shown in an
exemplary embodiment to be a single medium, the term
"machine-readable medium" may include a single medium or multiple
media (e.g., a centralized or distributed database, or associated
caches and servers) that store the one or more instructions. The
term "machine-readable medium" shall also be taken to include any
tangible medium that is capable of storing, encoding, or carrying
instructions for execution by the machine and that cause the
machine to perform any one or more of the methodologies of
embodiments of the present invention, or that is capable of
storing, encoding, or carrying data structures used by or
associated with such instructions. The term "machine-readable
medium" shall accordingly be taken to include, but not be limited
to, solid-state memories and optical and magnetic media. Specific
examples of machine-readable media include non-volatile memory,
including by way of exemplary semiconductor memory devices (e.g.,
Erasable Programmable Read-Only Memory (EPROM), Electrically
Erasable Programmable Read-Only Memory (EEPROM), and flash memory
devices); magnetic disks such as internal hard disks and removable
disks; magneto-optical disks; and CD-ROM and DVD-ROM disks. The
term "machine-readable medium" shall also be taken to include any
non-transitory storage medium.
Transmission Medium
[0099] The instructions 1224 may further be transmitted or received
over a communications network 1226 using a transmission medium via
the network interface device 1220 and utilizing any one of a number
of well-known transfer protocols (e.g., HTTP). Examples of
communication networks include a local area network (LAN), a wide
area network (WAN), the Internet, mobile telephone networks, Plain
Old Telephone (POTS) networks, and wireless data networks (e.g.,
WiFi and WiMax networks). The term "transmission medium" shall be
taken to include any intangible medium that is capable of storing,
encoding, or carrying instructions for execution by the machine,
and includes digital or analog communications signals or other
intangible medium to facilitate communication of such software.
[0100] Although an overview of the inventive subject matter has
been described with reference to specific exemplary embodiments,
various modifications and changes may be made to these embodiments
without departing from the broader spirit and scope of embodiments
of the present invention. Such embodiments of the inventive subject
matter may be referred to herein, individually or collectively, by
the term "invention" merely for convenience and without intending
to voluntarily limit the scope of this application to any single
invention or inventive concept if more than one is, in fact,
disclosed.
[0101] The embodiments illustrated herein are described in
sufficient detail to enable those skilled in the art to practice
the teachings disclosed. Other embodiments may be used and derived
therefrom, such that structural and logical substitutions and
changes may be made without departing from the scope of this
disclosure. The Detailed Description, therefore, is not to be taken
in a limiting sense, and the scope of various embodiments is
defined only by the appended claims, along with the full range of
equivalents to which such claims are entitled.
[0102] Moreover, plural instances may be provided for resources,
operations, or structures described herein as a single instance.
Additionally, boundaries between various resources, operations,
modules, engines, and data stores are somewhat arbitrary, and
particular operations are illustrated in a context of specific
illustrative configurations. Other allocations of functionality are
envisioned and may fall within a scope of various embodiments of
the present invention. In general, structures and functionality
presented as separate resources in the exemplary configurations may
be implemented as a combined structure or resource. Similarly,
structures and functionality presented as a single resource may be
implemented as separate resources.
[0103] These and other variations, modifications, additions, and
improvements fall within a scope of embodiments of the present
invention as represented by the appended claims. The specification
and drawings are, accordingly, to be regarded in an illustrative
rather than a restrictive sense.
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