U.S. patent application number 17/375531 was filed with the patent office on 2021-11-04 for techniques to improve a schedule with optimization.
This patent application is currently assigned to Capital One Services, LLC. The applicant listed for this patent is Capital One Services, LLC. Invention is credited to Fardin ABDI TAGHI ABAD, Reza FARIVAR, Jeremy Edward GOODSITT, Vincent PHAM, Anh TRUONG, Austin Grant WALTERS, Mark Louis WATSON.
Application Number | 20210342789 17/375531 |
Document ID | / |
Family ID | 1000005712648 |
Filed Date | 2021-11-04 |
United States Patent
Application |
20210342789 |
Kind Code |
A1 |
FARIVAR; Reza ; et
al. |
November 4, 2021 |
TECHNIQUES TO IMPROVE A SCHEDULE WITH OPTIMIZATION
Abstract
Techniques to improve a schedule using optimization are
described. Some described techniques improve the schedule using
optimization upon a user's travel booking operation and/or in
response to changes in the user's relationships. The techniques
include an apparatus, a method, and a computer-readable medium
configured to process relationship data associated with potential
candidates for a set of meetings in a schedule, relationship data
corresponding to interaction indicia with each potential candidate,
generate, from the relationship data, a connectivity network
comprising links with the potential candidates, each link of the
links corresponding to a relevance value between a user and a
specific potential candidate, and populate, via an optimization
unit, open meeting spaces in the schedule with meeting data based
upon the connectivity network and availability data of the
potential candidates, the schedule being configured to
substantially maximize relevancy of the set of meetings. Other
embodiments are described and claimed.
Inventors: |
FARIVAR; Reza; (Champaign,
IL) ; PHAM; Vincent; (Champaign, IL) ;
WALTERS; Austin Grant; (Savoy, IL) ; GOODSITT; Jeremy
Edward; (Champaign, IL) ; ABDI TAGHI ABAD;
Fardin; (Champaign, IL) ; WATSON; Mark Louis;
(Sedona, AZ) ; TRUONG; Anh; (Champaign,
IL) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Capital One Services, LLC |
McLean |
VA |
US |
|
|
Assignee: |
Capital One Services, LLC
McLean
VA
|
Family ID: |
1000005712648 |
Appl. No.: |
17/375531 |
Filed: |
July 14, 2021 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
16254030 |
Jan 22, 2019 |
11087290 |
|
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17375531 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G06Q 10/02 20130101;
G06Q 50/01 20130101; G06Q 10/06313 20130101; G06Q 10/1095
20130101 |
International
Class: |
G06Q 10/10 20060101
G06Q010/10; G06Q 10/06 20060101 G06Q010/06; G06Q 10/02 20060101
G06Q010/02; G06Q 50/00 20060101 G06Q050/00 |
Claims
1. An apparatus, comprising: computer memory; a processing circuit;
and logic stored in the computer memory and executed on the
processing circuit, the logic operative to cause the processing
circuit to: process interaction data communicated between devices
over at least one of an internal network, an external network, or a
combination thereof, the interaction data comprising interaction
indications for one or more potential candidates to schedule one or
more meetings in a schedule, the interaction indications comprising
indirect interactions for the one or more of the potential
candidates having more than one degree of separation from a user
and direct interactions for the one or more of the potential
candidates having one degree of separation from the user; generate
relationship data associated with the potential candidates for the
one or more meetings in the schedule from the interaction
indications; generate, from the relationship data, a connectivity
network comprising links with the potential candidates, each link
of the links corresponding to a relevance value between the user
and a specific potential candidate, and wherein each relevance
value represents a relationship between the user and the specific
potential candidate; perform a combinatorial optimization technique
on the connectivity network and availability data of the potential
candidates to determine meeting data comprising an arrangement of
meetings increasing relevancy of the schedule, the availability
data being operative to reduce a search space for the arrangement
of meetings to open meeting spaces of the user; and communicate a
control directive to an application programming interface (API) of
an enterprise application based on the meeting data.
2. The apparatus of claim 1, wherein the control directive
comprises instructions to cause the enterprise application to
populate open meeting spaces in the schedule with the meeting
data.
3. The apparatus of claim 1, wherein the interaction indications
comprise social networking interactions communicated on a channel
of a cloud-based collaboration application.
4. The apparatus of claim 1, wherein the interaction indications
comprise social networking interactions communicated on an email
domain or an email thread.
5. The apparatus of claim 1, the processing circuit to mine at
least one input coupled with one or more of the devices or output
coupled with one or more of the devices to determine and process
the interaction data.
6. The apparatus of claim 1, wherein the availability data
indicates one or more time slots open for the one or more potential
candidates to determine the meeting data for the user.
7. The apparatus of claim 1, wherein the relevancy value for the
user and the specific potential candidate measures a topic/project
relevance between the user and the specific potential
candidate.
8. The apparatus of claim 1, wherein the relevancy value for the
user and the specific potential candidate measures a connectedness
relevance between the user and the specific potential
candidate.
9. The apparatus of claim 7, wherein the topic/project relevance
indicates a number of how many topics/projects the user and the
specific potential candidate have in common.
10. The apparatus of claim 8, wherein the connectedness relevance
indicates how often the user and the specific potential candidate
communicate.
11. A computer implemented method, comprising: receiving
communications communicated between devices over at least one of an
internal network, an external network, or a combination thereof,
the communications comprising interaction indications potential
candidates to determine a schedule of one or more meetings, the
interaction indications comprising indirect interactions and direct
interactions determining relationship data associated with the
potential candidates for the one or more meetings in the schedule
from the interaction indications; generating, from the relationship
data, a connectivity network comprising links with the potential
candidates, each link of the links corresponding to a relevance
value between the user and a specific potential candidate, and
wherein each relevance value represents a relationship between the
user and the specific potential candidate; performing a
combinatorial optimization technique on the connectivity network
and availability data of the potential candidates to determine
meeting data comprising an arrangement of meetings increasing
relevancy of the schedule, the availability data being operative to
reduce a search space for the arrangement of meetings to open
meeting spaces of the user; and sending a control directive to an
application programming interface (API) of an enterprise
application based on the meeting data.
12. The method of claim 11, comprising generating the control
directive based on a result of the combinatorial optimization
technique, wherein the control directive is configured to cause the
enterprise application to populate open meeting spaces in the
schedule with the meeting data.
13. The method of claim 11, wherein the interaction indications
comprise social networking interactions communicated on a channel
of a cloud-based collaboration application.
14. The method of claim 11, wherein the interaction indications
comprise social networking interactions communicated on an email
domain or an email thread.
15. The method of claim 11, comprising harvesting at least one
input or output coupled with one or more of the devices to
determine and process the interaction data.
16. The method of claim 11, wherein the availability data indicates
one or more time slots open for the one or more potential
candidates to determine the meeting data for the user.
17. The method of claim 11, wherein the relevancy value for the
user and the specific potential candidate measures a topic/project
relevance between the user and the specific potential
candidate.
18. The method of claim 11, wherein the relevancy value for the
user and the specific potential candidate measures a connectedness
relevance between the user and the specific potential
candidate.
19. The method of claim 17, wherein the topic/project relevance
indicates a number of how many topics/projects the user and the
specific potential candidate have in common.
20. The method of claim 18, wherein the connectedness relevance
indicates how often the user and the specific potential candidate
communicate.
Description
RELATED APPLICATIONS
[0001] This application is a continuation of U.S. patent
application Ser. No. 16/254,030, titled "TECHNIQUES TO IMPROVE A
SCHEDULE WITH OPTIMIZATION" filed on Jan. 22, 2019. The contents of
the aforementioned application are incorporated herein by reference
in their entirety.
BACKGROUND
[0002] In order for a business to operate properly, people must
communicate effectively and work together as a cohesive unit;
otherwise, most tasks will be incomplete and/or substandard. At
least for this reason, companies invest in and/or produce their own
technologies to increase employee productivity, for example, by way
of enterprise applications (e.g., collaboration and productivity
applications, such as word processing applications, e-mail
applications, spreadsheet applications, unified communications
systems and/or the like). Many enterprises today include associates
located at distributed offices throughout the US and/or the world.
Although collaboration tools have increased opportunities for
digital interaction between individuals, suitable tools don't exist
for facilitating in person interactions, which may be particularly
challenging for associates traveling between office locations.
These technologies provide several benefits of which better
information is one. People, often when traveling, lack information
about a new location, such as information about planned events at
the new location, associates located at the new location, etc.
Thus, opportunities for potentially valuable in-person
collaboration or networking may be overlooked or missed.
[0003] It is with respect to these and other considerations that
the present improvements have been needed.
SUMMARY
[0004] The following presents a simplified summary in order to
provide a basic understanding of some novel embodiments described
herein. This summary is not an extensive overview, and it is not
intended to identify key/critical elements or to delineate the
scope thereof. Its sole purpose is to present some concepts in a
simplified form as a prelude to the more detailed description that
is presented later.
[0005] Various embodiments are generally directed to techniques to
improve a schedule with optimization for local events or meetings
and/or collaboration opportunities with other individuals
determined to have a relevant relationship. Some embodiments are
particularly directed to techniques to improve a schedule with
optimization for situations when a person is in a new location,
such as during a travel booking operation. In one embodiment, for
example, an apparatus may comprise logic stored in the computer
memory and executed on the processing circuit. The logic may be
operative to cause the processing circuit to process relationship
data associated with potential candidates for a set of meetings in
a schedule where relationship data corresponds to interaction
indicia with each potential candidate. The logic may be further
operative to cause the processing circuit to generate, from the
relationship data, a connectivity network comprising links with the
potential candidates such that each link of the links corresponds
to a relevance value between a user and a specific potential
candidate. The logic may be operative to cause the processing
circuit to populate or suggest, via an optimization mechanism, open
meeting spaces in the schedule with meeting data based upon the
connectivity network and availability data of the potential
candidates. As a result, the schedule described herein is
configured to substantially increase networking and collaboration
opportunities and to maximize relevancy of the set of meetings.
Other embodiments are described and claimed.
[0006] To the accomplishment of the foregoing and related ends,
certain illustrative aspects are described herein in connection
with the following description and the annexed drawings. These
aspects are indicative of the various ways in which the principles
disclosed herein can be practiced and all aspects and equivalents
thereof are intended to be within the scope of the claimed subject
matter. Other advantages and novel features will become apparent
from the following detailed description when considered in
conjunction with the drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
[0007] FIG. 1 illustrates an embodiment of a system to improve a
schedule with optimization.
[0008] FIG. 2 illustrates an embodiment of a connectivity network
for the system of FIG. 1.
[0009] FIG. 3 illustrates an embodiment of an operating environment
for the system of FIG. 1.
[0010] FIG. 4 illustrates an embodiment of a schedule in accordance
with the system of FIG. 1.
[0011] FIG. 5 illustrates an embodiment of a first logic flow for
the system of FIG. 1.
[0012] FIG. 6 illustrates an embodiment of a second logic flow for
the system of FIG. 1.
[0013] FIG. 7 illustrates an embodiment of a third logic flow for
the system of FIG. 1.
[0014] FIG. 8 illustrates an embodiment of a computing
architecture.
[0015] FIG. 9 illustrates an embodiment of a communications
architecture.
DETAILED DESCRIPTION
[0016] Various embodiments are directed to improve a schedule with
optimization to further improve worker productivity, collaboration,
and networking. If a person (e.g., when traveling) enters a new
location, that person typically does not have enough information
about the new location, including events of meetings scheduled at
the new location, as well as identifying information of associated
sitting at the new location. This insufficiency indicates that the
person does not easily know of other relevant individuals with whom
to schedule meetups or other potentially relevant meetings or
events that may be of interest to the person. During the person's
stay at the new location, for example, the person may be limited to
a few meetings and an opportunity to build value and goodwill will
be lost. By evaluating at least some information about the person's
relationships/connections, at least some of the various embodiments
of the present disclosure provide a technical solution that
identifies a set of potential candidates at the new location with
whom to schedule meetups or hold meetings. The various embodiments
may proceed to improve the person's schedule by automatically
recommending potential meetups and/or populating that schedule's
open meeting spaces with actual meetings with relevant ones of the
set of potential candidates. Some embodiments of the present
disclosure perform such automatic recommendation or population upon
or in response to a travel booking operation via an airline travel
web application. The disclosed embodiments are also applicable to
identifying networking opportunities upon request for any
individual in a location, whether or the not the individual is
travelling.
[0017] It should be appreciated that the relevancy of the
above-mentioned potential candidates can be determined using any
number of metrics, and candidates can be ranked according to their
relevancy to the person booking travel. In one example embodiment,
a potential candidate's relevancy--expressed as a numerical
value--results from a heuristic function that receives, as input,
relationship data corresponding to interactions between the person
with the potential candidate. In another example embodiment, the
potential candidate's relevancy is measured according to the above
relationship data and project data corresponding to an
organization's pending projects. Hence, the potential candidate's
relevancy can be defined by the relationship data and, if needed,
further refined by the project data such that the potential
candidate's relevance value is adjusted according to the potential
candidate's relevance to a pending project. To illustrate by way of
example, in an organization where one potential candidate is an
executive, there may be very few interactions between that
candidate and a user; however, if the potential candidate must
authorize the user's plans for the pending project, then that
candidate's relevancy increases.
[0018] To achieve such an improvement, the various embodiments may
rely upon an optimization mechanism, a logic unit or circuit
capable of executing a combinatorial optimization technique, to
identify an optimal or near optimal arrangement of meetings for the
schedule. The optimal or near-optimal arrangement of meetings may
maximize or substantially maximize relevancy with respect to that
user. As mentioned herein, relevancy can be measured in any number
of ways and one example refines relevancy as a relationship between
a potential candidate and the person's project(s). Therefore, the
near-optimal arrangement of meetings in the schedule may be
configured to maximize (or substantially maximize) relevancy with
respect to the person's project(s). It should be noted that the
embodiments described in the present disclosure utilize various
data to enable the optimization mechanism by effectively reducing a
search space for the optimal or near-optimal arrangement of
meetings in the schedule. As a result, the embodiments can improve
affordability, scalability, modularity, extendibility, or
interoperability for an operator, device or network.
[0019] With general reference to notations and nomenclature used
herein, the detailed descriptions which follow may be presented in
terms of program procedures executed on a computer or network of
computers. These procedural descriptions and representations are
used by those skilled in the art to most effectively convey the
substance of their work to others skilled in the art.
[0020] A procedure is here, and generally, conceived to be a
self-consistent sequence of operations leading to a desired result.
These operations are those requiring physical manipulations of
physical quantities. Usually, though not necessarily, these
quantities take the form of electrical, magnetic or optical signals
capable of being stored, transferred, combined, compared, and
otherwise manipulated. It proves convenient at times, principally
for reasons of common usage, to refer to these signals as bits,
values, elements, symbols, characters, terms, numbers, or the like.
It should be noted, however, that all of these and similar terms
are to be associated with the appropriate physical quantities and
are merely convenient labels applied to those quantities.
[0021] Further, the manipulations performed are often referred to
in terms, such as adding or comparing, which are commonly
associated with mental operations performed by a human operator. No
such capability of a human operator is necessary, or desirable in
most cases, in any of the operations described herein which form
part of one or more embodiments. Rather, the operations are machine
operations. Useful machines for performing operations of various
embodiments include general purpose digital computers or similar
devices.
[0022] Various embodiments also relate to apparatus or systems for
performing these operations. This apparatus may be specially
constructed for the required purpose or it may comprise a
general-purpose computer as selectively activated or reconfigured
by a computer program stored in the computer. The procedures
presented herein are not inherently related to a particular
computer or other apparatus. Various general-purpose machines may
be used with programs written in accordance with the teachings
herein, or it may prove convenient to construct more specialized
apparatus to perform the required method steps. The required
structure for a variety of these machines will appear from the
description given.
[0023] Reference is now made to the drawings, wherein like
reference numerals are used to refer to like elements throughout.
In the following description, for purposes of explanation, numerous
specific details are set forth in order to provide a thorough
understanding thereof. It may be evident, however, that the novel
embodiments can be practiced without these specific details. In
other instances, well-known structures and devices are shown in
block diagram form in order to facilitate a description thereof.
The intention is to cover all modifications, equivalents, and
alternatives consistent with the claimed subject matter.
[0024] FIG. 1 illustrates a block diagram for a system 100. In one
embodiment, the system 100 may comprise a computer-implemented
system having an apparatus 120 comprising one or more elements.
Although the system 100 shown in FIG. 1 has a limited number of
elements in a certain topology, it may be appreciated that the
system 100 may include more or less elements in alternate
topologies as desired for a given implementation.
[0025] The system 100 may comprise the apparatus 120. The apparatus
120 may be generally arranged to process input 110 and generate
output 130 of which some of the output 130 may be configured for
display on a display device. The apparatus 120 may include a
processing circuit 140 and computer memory 150 on which logic 160
is stored and executed, respectively.
[0026] According to various embodiments, the logic 160 being
operative to cause the processing circuit 140 to process
relationship data 170 associated with potential candidates for a
set of meetings in a schedule where the relationship data 170
corresponds to interaction indicia with each potential candidate.
The logic 160 being further operative to cause the processing
circuit 140 to generate, from the relationship data 170, a
connectivity network that includes links with the potential
candidates such that each link of the links corresponds to a
relevance value between a user and a specific potential candidate.
The logic 160 being further operative to cause the processing
circuit 140 to populate, via an optimization mechanism 190, open
meeting spaces in the schedule with meeting data based upon the
connectivity network and availability data 180 of the potential
candidates, the schedule being configured to substantially maximize
relevancy of the set of meetings to the user.
[0027] In some embodiments, the availability data 180 may include
data indicating an open time slot in each candidate's calendar
and/or geographic location information of the candidate (which may
be determined based on a person's usual location and/or travel
information identified in the calendar). In some embodiments, the
availability data 180 may also include data indicating events
included in a candidate's calendar that may be relevant to a user,
so the availability data 180 need not be limited to "open" calendar
times. In some embodiments, the logic 160 being further operative
to cause the processing circuit to access project data and adjust
the connectivity network to account for relevancy to a particular
project or set of projects.
[0028] The optimization mechanism 190 generally includes
programmable logic and/or circuitry to execute an optimization
technique, such as a combinatorial optimization technique. The
optimization mechanism 190 may execute a modified combinational
optimization technique that processes graph data comprising the
connectivity network and the availability data 180 to determine an
optimal or near-optimal arrangement of meetings. The connectivity
network, being in graph data, may be processed with a reduced
resource consumption. Furthermore, relevance values in the
connectivity graph may represent heuristic values for the
optimization technique and mitigate or eliminate a need for
computing the heuristic values. The availability data 180 may
further reduce the resource consumption and limit a search space
for the optimal or near-optimal arrangement of meetings. In
general, the availability data 180 refers to data identifying open
and closed meeting spaces on schedules of the potential candidates
in addition to or exclusive of data identifying the open meeting
spaces in the schedule of the user.
[0029] The relationship data 170 generally refers to interactions
between the user of the apparatus 120 and the potential candidates
for meeting participants. These interactions may be external
interactions (i.e., with devices in an external network) or
internal interactions (i.e., with devices in an internal network).
Some of these interactions may be social networking interactions
through a social networking application, including email or
messaging applications, contact lists. The interactions may be
direct (e.g., direct communications) or indirect. By way of
example, these indirect interactions may be inferred from common
registration to a team channel or a topic channel, following of a
topic, membership to an email thread, communications through an
intermediate, forwarded emails, an email alias, and/or the like. In
some embodiments, these interactions may be harvested from
enterprise tools. As described herein, the logic 160 or other logic
in the apparatus 120 may mine the input 110 and the output 130 to
identify the above-mentioned interactions and generate the
relationship data 170. The logic 160 may process the relationship
data 170 corresponding to the above-mentioned interactions and
identify various indicia (e.g., attributes) of relevancy. The logic
160 may further process the relationship data 170 in accordance
with a relevance metric to determine relevancy of a potential
candidate to the user.
[0030] The relevance metric refers to some functionality capable of
measuring an aspect of relevance. It is appreciated that the
relevance metric, as described herein, may measure any aspect of
relevance; for example, one relevance metric may measure
topic/project relevance while another relevance metric may measure
connectedness relevance. Topic/project relevance may refer to a
measurement as to how many topic/projects the user and the
potential candidate share, whereas connectedness relevance may
refer to a measurement as to how often the user and the potential
candidate communicate/interact. The relevance metric described
herein may be applied to the relationship data 170 to determine how
relevant is a potential candidate to the user; the relevancy of
which can be defined in generality or in a specific respect. For
example, the relevance metric may determine how relevant is the
potential candidate to the user with respect to the user's work
life or the user's social life. The relevance metric may be used to
define relevancy for a specific aspect of the user's work life,
such as for a particular project.
[0031] In some embodiments, the optimization mechanism 190 provides
the optimal or near-optimal arrangement by framing--as an
optimization problem such as the bin-packing problem or the
knapsack problem--the automatic population of the schedule as
described herein for the logic 160. In the bin packing problem,
objects of different volumes must be packed into a finite number of
bins or containers each of volume (V) in a way that minimizes the
number of bins used. When the number of bins is restricted to one
(1) and each item is characterized by both a volume and a value,
the problem of maximizing the value of items that can fit in the
bin is known as the knapsack problem. In the knapsack problem,
given a set of items, each with a weight and a value, determine the
number of each item to include in a collection so that the total
weight is less than or equal to a given limit and the total value
is as large as possible. The automatic recommendation or population
of the open meeting spaces in the schedule with meeting data as
described herein can be enabled by considering the schedule to be a
bin and each item to be a potential meeting with a potential
candidate in the connectivity network.
[0032] An alternative embodiment of the optimization mechanism 190
considers each 30-minute open meeting space as a single bin, and a
set of half-hour open meeting spaces as a set of bins in a
bin-packing problem. Similarly, the list of available people that
are at the same physical location are possible items that may be
distributed across the bins. From this point on, any number of
well-known bin-packing solutions can be effectively used to
distribute the meeting items onto the meeting space bins. Examples
of these solutions include first-fit decreasing or best-fit
decreasing algorithms. Other solutions can be used for better
fitting/faster runtimes without changing the optimization mechanism
190.
[0033] Despite the fact that the bin packing problem/knapsack
problem has an NP-hard computational complexity, the
above-mentioned optimal or near-optimal arrangement can be
identified with certain techniques of which some employ suitable
approximation algorithms or heuristics. As one example technique,
the first fit algorithm provides a fast but often non-optimal
solution, involving placing each item into the first bin in which
it will fit. The algorithm can be made much more effective by first
sorting the list of elements into decreasing order (sometimes known
as the first-fit decreasing algorithm). It is known, however, that
there always exists at least one ordering of items that allows
first-fit to produce an optimal solution.
[0034] The design of suitable heuristics or approximation
algorithms for combinatorial optimization may require significant
specialized knowledge and trial-and-error. Other embodiments
exploit the fact that the same problem structure is maintained
between goal of finding the optimal arrangement and a known
combinatorial optimization problem. This provides an opportunity
for learning heuristic algorithms that exploit the structure of
such recurring problems. Embodiments described in the present
disclosure can be applied to a diverse range of optimization
problems with underlying structures in graph data. Some embodiments
may further improve the automatic population of the schedule by
invoking a machine learning technique to learn effective algorithms
and/or heuristics.
[0035] FIG. 2 illustrates an embodiment of a connectivity network
200 for the system 100. As shown in FIG. 2, the connectivity
network 200 has root node 202 representing a user with links 204 to
nodes 206 representing potential candidates for meetings. As
described herein, the system 100 evaluates relationship data (e.g.,
the relationship data 170 of FIG. 1) between the potential
candidates and the user in accordance with a relevance metric and
generates the connectivity network 200 such that a link 204.sub.I
to a node 206.sub.I corresponds with a value indicating relevancy
to the user of the person represented by the node 206.sub.I. The
relationship data generally includes external network interactions
(e.g., social network interactions between the user and the
potential candidates via social networking platform) and internal
network interactions (e.g., work-related interactions between the
user and the potential candidates as employees in a same
organization). The relationship data also identifies potential
candidates who may be more than one degree of separation away from
the user.
[0036] In some embodiments, the relationship data can be modeled
such that each type of interaction is an attribute with at least
one value and at least one weight. Each value/weight may be based
upon certain nuances; for example, an attribute's weight may be
based upon that type of interaction's importance with respect to
the other attributes. The system 100 may train a machine learning
model by assigning values to data points representing interactions
between the user and a potential candidate and compute a combined
value representing a relevance of the user's relationship with the
potential candidate.
[0037] The system 100 may infer the relationship data in a variety
of ways. In one embodiment, the system 100 may infer the
relationship data from enrollment into a specific group, such as a
group in a collaboration or communication tool. The user and one or
more potential candidates may share membership to a specific
channel of a cloud-based collaboration application and platform
(e.g., SLACK.RTM.). In another embodiment, the system 100 may infer
the relationship data from common membership in a same email
domain, a same email thread, and/or a same email alias; each having
a different weight assigned by the system 100. The system 100 may
assign weights based on an extent to which potential candidates
have directly communicated via email, commented on a same topic,
and/or the like. A weight may be adjusted, for example, based on
frequency of communication on a topic.
[0038] By performing a weighted analysis of the relationship data,
the system 100 generates relevance values between the user and the
potential candidates. These relevance values can be used to
construct the connectivity network 200. Each relevance value
generally characterizes a relationship between the user and a
potential candidate. With respect to FIG. 2, the present disclosure
expresses differences in relevance values as differences in length
of the links 204. To illustrate by way of example, if the user and
the potential candidate frequently communicate directly via email,
the system 100 invokes a metric to compute a relevance value
representing such frequent communications. If, on the other hand,
the user and the potential candidate rarely communicate via email,
the same metric may provide a considerably lower relevance value.
The metric may be applied to additional types of interactions and
is limited to measuring email communications. The metric may be
applied to measuring indirect network interactions for computing
relevance values, such as when the user and a potential candidate
have more than one degree of separation.
[0039] When the system 100 combines the connectivity network 200
with availability data (e.g., the availability data 180 of FIG. 1)
corresponding to both the potential candidates and the user, the
system 100 determines an optimal (or near-optimal) arrangement of
meetings for insertion into open meeting spaces of the user's
schedule. The arrangement of meetings may be considered optimal (or
near-optimal) if such an arrangement maximizes (or substantially
maximizes) relevancy to the user in some respect. Some example
embodiments implement the connectivity network 200 such that the
resulting user schedule is configured to maximize (or substantially
maximize) relevancy to the user with respect to their relationship
to each other. It is appreciated that the relationship data between
the user and the potential candidates can be evaluated using any
number of metrics.
[0040] The connectivity network 200 can be adapted to any model by
adjusting the relevance values. For example, embodiments of the
present disclosure utilize different sets of attributes and/or
different functions to compute multiple sets of relevance values of
which one set may be used for one purpose and another set may be
configured for another purpose.
[0041] FIG. 3 illustrates a block diagram of an embodiment of an
operating environment 300 for the system 100. The operating
environment 300 may be in the form of a centralized system
implementing some or all of the structure and/or operations for the
system 100 in a single computing entity, such as entirely within a
single device 320. As shown in FIG. 3, the operating environment
300 includes the device 320 connected to one or more internal
devices 310 and one or more external devices 350.
[0042] The device 320 may comprise any electronic device capable of
receiving, processing, and sending information for the system 100.
Examples of an electronic device may include without limitation an
ultra-mobile device, a mobile device, a personal digital assistant
(PDA), a mobile computing device, a smart phone, a telephone, a
digital telephone, a cellular telephone, ebook readers, a handset,
a one-way pager, a two-way pager, a messaging device, a computer, a
personal computer (PC), a desktop computer, a laptop computer, a
notebook computer, a netbook computer, a handheld computer, a
tablet computer, a server, a server array or server farm, a web
server, a network server, an Internet server, a work station, a
mini-computer, a main frame computer, a supercomputer, a network
appliance, a web appliance, a distributed computing system,
multiprocessor systems, processor-based systems, consumer
electronics, programmable consumer electronics, game devices,
television, digital television, set top box, wireless access point,
base station, subscriber station, mobile subscriber center, radio
network controller, router, hub, gateway, bridge, switch, machine,
or combination thereof. The embodiments are not limited in this
context.
[0043] The device 320 may execute processing operations or logic
for the system 100 using a processing component 330. The processing
component 330 may comprise various hardware elements, software
elements, or a combination of both. Examples of hardware elements
may include devices, logic devices, components, processors,
microprocessors, circuits, processor circuits, circuit elements
(e.g., transistors, resistors, capacitors, inductors, and so
forth), integrated circuits, application specific integrated
circuits (ASIC), programmable logic devices (PLD), digital signal
processors (DSP), field programmable gate array (FPGA),
Application-specific Standard Products (ASSPs), System-on-a-chip
systems (SOCs), Complex Programmable Logic Devices (CPLDs), memory
units, logic gates, registers, semiconductor device, chips,
microchips, chip sets, and so forth. Examples of software elements
may include software components, programs, applications, computer
programs, application programs, system programs, software
development programs, machine programs, operating system software,
middleware, firmware, software modules, routines, subroutines,
functions, methods, procedures, software interfaces, application
program interfaces (API), instruction sets, computing code,
computer code, code segments, computer code segments, words,
values, symbols, or any combination thereof. Determining whether an
embodiment is implemented using hardware elements and/or software
elements may vary in accordance with any number of factors, such as
desired computational rate, power levels, heat tolerances,
processing cycle budget, input data rates, output data rates,
memory resources, data bus speeds and other design or performance
constraints, as desired for a given implementation.
[0044] The device 320 may execute communications operations or
logic for the system 100 using communications component 340. The
communications component 340 may implement any well-known
communications techniques and protocols, such as techniques
suitable for use with packet-switched networks (e.g., public
networks such as the Internet, private networks such as an
enterprise intranet, and so forth), circuit-switched networks
(e.g., the public switched telephone network), or a combination of
packet-switched networks and circuit-switched networks (with
suitable gateways and translators). The communications component
340 may include various types of standard communication elements,
such as one or more communications interfaces, network interfaces,
network interface cards (NIC), radios, wireless
transmitters/receivers (transceivers), wired and/or wireless
communication media, physical connectors, and so forth. By way of
example, and not limitation, communication media 312, 342 include
wired communications media and wireless communications media. The
communication media 312, 342 can be distinguished from a storage
medium such as the computer memory 150 of FIG. 1. Examples of wired
communications media may include a wire, cable, metal leads,
printed circuit boards (PCB), backplanes, switch fabrics,
semiconductor material, twisted-pair wire, co-axial cable, fiber
optics, a propagated signal, and so forth. Examples of wireless
communications media may include acoustic, radio-frequency (RF)
spectrum, infrared and other wireless media.
[0045] The device 320 may communicate with other devices 310, 350
over a communications media 312, 342, respectively, using
communications signals 314, 344, respectively, via the
communications component 340. The devices 310, 350 are internal or
external to the device 320, respectively, as desired for a given
implementation. In general, the internal device(s) 310 and/or the
external device(s) 350 may be the same or similar to the device 320
or the apparatus 120 as described with reference to FIG. 1. For
instance, the internal device(s) 310 and/or the external device(s)
350 may each comprise a processing component 330 and a
communications component 340 which are the same or similar to the
processing component 330 and the communications component 340,
respectively.
[0046] In some embodiments, the logic 160 of FIG. 1 may generate
the relationship data 170 of FIG. 1 by examining
communications/interactions between the device 320 and the internal
device(s) 310 and/or the external device(s) 350. The logic 160 of
FIG. 1 may store information corresponding to these
communications/interactions and, from this information, may
identify attributes and attribute values using a relevance metric
as described herein. As an example, the device 320 and the internal
device(s) 310 form part of an internal network (e.g., a campus-wide
or company-wide enterprise network) through which the device 320
and/or the internal device(s) 310 exchange messages and data,
generate/collaborate on documents, and otherwise interact/connect
with each other. The device 320 and the external device(s) 350 form
part of an external network (e.g., a social network) through which
various applications exchange messages and data (e.g., videos,
photos, and/or the like), generate/collaborate on documents (e.g.,
creative works), and otherwise interact/connect with each other.
Often, the user, via the device 320, communicates with a same
person via both the external network and the internal network; the
person may have multiple devices with at least one internal device
310 and at least one external device 350. The relationship data, as
described herein, records these interactions/connections for
evaluation by some metric (i.e., a relevance metric).
[0047] One example relevance metric evaluates the relationship data
to determine how relevant, in general, a potential meeting
participant is to the user. The present disclosure envisions a
number of applicable metrics of which some are configured to
evaluate relevancy in at least one respect. The relevance metric is
configured to produce a relevance value indicating such relevancy.
The relevance metric can be adjusted or configured such that those
who are relevant to the user in a particular respect will have
higher relevance value than those who are not relevant in the
particular respect or who are relevant in other respects. For
example, the relevance metric may score external network
interactions/connections higher than internal network
interactions/connections to identify people who are relevant to the
user's home/social life; vice versa, the relevance metric may score
internal network interactions/connections higher than external
network interactions/connections to identify people who are
relevant to the user's work life. As another example, if the
relevance metric is configured to assign a value only to people who
communicate with the device 320 through the user's work email
address, the system 100 can easily determine which potential
candidates are relevant to the user's work and should be considered
for a meeting.
[0048] As described herein, some embodiments utilize project data
360--which may include a database of pending project information or
other information from which project participation can be inferred
including records of access privileges, organization hierarchical
information, and/or the like--to augment the relationship data in
determining relevancy of the potential candidate as a meeting
participant. Depending on the relevance metric, the system 100
adjusts the relevance values to incorporate into the relevance
calculation the project data 360. As an example, the relevance
metric may assign higher attribute values to or define new
attributes for interactions/connections pertaining to one of the
user's projects. As a result, the system 100 may compute a higher
relevance value for a potential candidate involved in one of the
user's projects than another potential candidate even through the
other potential candidate may communicate/interact with the user
more frequently.
[0049] FIG. 4 illustrates an embodiment of a schedule 400 for the
system 100. As shown in FIG. 4, the schedule 400 includes open
meeting slots into which the system 100 recommends or populates
with meetings for a user. FIG. 4 further illustrates corresponding
schedules 402 with open and closed meeting slots for potential
candidates for meeting participants. In both the schedule 400 and
the corresponding schedules 402, the open meeting slots express
availability data for either the user or the potential candidates
for meeting participants.
[0050] Regarding the corresponding schedules 402, the closed
meeting slots may express availability data for the potential
candidates, such as when a closed meeting slot is relevant to the
user. As described below, the closed meeting slot may indicate a
social event on company campus; that social event will provide a
rare opportunity for the user to get to know the potential
candidates without work getting in the way. As an example, the
closed meeting slot may indicate a group meeting that is relevant
towards completing the user's current project. The user may desire
to join this meeting by requesting an invitation. As another
example, the closed meeting slot may indicate an informational
seminar/presentation where colleagues from different parts of an
organization gather to learn and/or brainstorm. A list of closed
meeting slots may be inferred from the corresponding schedules 402
and/or from other sources (e.g., general open invitations or
lists).
[0051] Based upon the availability data for those potential
candidates and a connectivity network representing relationships
between the user and the potential candidates, the system 100 may
determine an arrangement of meetings such that the resulting
schedule 400 maximizes relevance to the user as described in the
present disclosure. Once the above arrangement of meeting is
determined, the system 100 inserts information into at least some
of the open meeting spaces of the schedule 400 and at least some of
the corresponding schedules 402, setting meeting data to establish
meetings (e.g., calendar events) between the user and at least some
of the potential candidates.
[0052] As a result, the schedule 400 being illustrated in FIG. 4
includes an arrangement of meetings set for eight (8) am to nine
(9) am, ten (10) am to eleven (11) am, and six (6) pm to nine (9)
pm on Monday and eight-thirty (8:30) am to nine-thirty (9:30) am on
Tuesday. A first meeting of the arrangement occurs from eight (8)
am to nine (9) am on Monday as a group meeting with the project
team. Scheduling the first meeting involves at least coordinating
contemporaneous open meeting spaces amongst multiple meeting
participant schedules from the corresponding schedules 402. A
second meeting of the arrangement, a face-to-face meeting with
Person A, occurs on Monday, Oct. 1, 2018, from ten (10) am to
eleven (11) am. A third meeting of the arrangement is a company
social event held from six (6) pm to nine (9) pm, Oct. 1, 2018. The
system 100 automatically adds the user to the social event (e.g.,
via an automatic reply e-mail message to an invitation). A fourth
meeting of the arrangement, a virtual or on-line meeting with
Person Z, occurs from eight-thirty (8:30) pm to nine-thirty (9:30)
am, Oct. 2, 2018.
[0053] The first, second, and fourth meetings are scheduled for
open meeting slots between the contemporaneous corresponding
schedules 402 and the user's schedule 400. The third meeting of the
arrangement is established for a closed meeting slot between the
contemporaneous corresponding schedules 402 and the user's schedule
400. Multiple connected persons may have the company social event
on their corresponding schedules 402. Alternatively, the company
social event may be listed as a campus event on everyone's
corresponding schedules 402.
[0054] In some embodiments, the system 100 allows for sending
recommendations to the user informing that user of potential
meetups, group meetings, social events, seminars, and/or the like.
The recommendation may include an invitation to the potential
meetups, group meetings, social events, seminars, and/or the like.
The user, after reviewing the recommendation, may select one or
more invitations to accept. Each invitation or the recommendation
could include information indicating the relevant factors used in
making the connection, for example, there is an opportunity to
connect with Jim Beam, which we think you might find interesting
because you both subscribe to the Whiskey Club messaging channel
and both have indicated affinity for Kentucky Bourbon. In addition
to or as an alternative, the invitation or recommendation may
indicate that both the user and the recommended meeting participant
are on a same Data Transformation email alias at the same company,
indicating that both may be working on similar solutions. In some
embodiments, the recommendation could include scripted code
operative to auto-generate a meeting invite to send to Jim Beam
with some pre-generated message content.
[0055] The system 100 may incorporate feedback into the
identification of potential candidates for meeting participants.
The above-mentioned recommendation may include a mechanism (e.g., a
selection box) that allows the user to provide feedback, such as to
remove people on the Whiskey Club messaging channel from
consideration as potential meeting participants. Other types of
feedback may be to select time slots to schedule a meeting or to
select certain potential candidates to consider over others. For
example, the user may enter (e.g., via a selection dialog box)
instructions directing the system 100 to prioritize people from the
Whiskey Club messaging channel as potential candidates for meeting;
to reflect such prioritization, the system 100 increases the
relevance values for those on the Whiskey Club messaging channel.
The user may also enter instructions directing the system 100 to
prioritize or restrict specific time slots for meetings such that
relevance values are increased for potential candidates who have
availability during the specific time slots; for example, the
system 100 may establish meetings for the user's schedule 400 only
between two (2) to four (4) pm. As another example, the user may
instruct the system 100 to schedule meetings with project managers
working on Artificial Intelligence-related projects; as a result,
the system 100 selects meeting participants from the corresponding
schedules 402 of those project managers.
[0056] While it is appreciated that additional meeting spaces could
have been populated with additional meeting data but that would
render non-optimal the resulting arrangement of meetings. As one
reason, the additional meeting data may be extraneous and/or
unnecessary and thus, would not help substantially maximize a
relevancy of the entire arrangement of meetings. Extraneous and/or
unnecessary meetings do not further a goal (e.g., a project) and
can waste resources for the meeting participants. In fact, an
extraneous or unnecessary meeting may provide only a nominal value
but incur an overall cost (e.g., in terms of time, expense, and
lost opportunity) that outweighs the nominal value in return.
Therefore, the system 100 may set a minimum threshold relevance
value for the optimal arrangement of meetings. Once a sum of
relevance values from the above four meetings reaches the minimum
threshold, the system 100 outputs the schedule 400.
[0057] Included herein is a set of flow charts representative of
exemplary methodologies for performing novel aspects of the
disclosed architecture. While, for purposes of simplicity of
explanation and by example, the one or more methodologies are shown
and described as a series of acts in the form of a flow chart or
flow diagram, it is to be understood and appreciated that the
methodologies are not limited by the order of acts, as some acts
may, in accordance therewith, occur in a different order and/or
concurrently with other acts from that shown and described herein.
For example, those skilled in the art will understand and
appreciate that a methodology could alternatively be represented as
a series of interrelated states or events, such as in a state
diagram.
[0058] Moreover, not all acts illustrated in a methodology may be
required for a novel implementation.
[0059] FIG. 5 illustrates one embodiment of a logic flow 500. The
logic flow 500 may be representative of some or all of the
operations executed by one or more embodiments described
herein.
[0060] In the illustrated embodiment shown in FIG. 5, the logic
flow 500 processes relationship data associated with potential
candidates for meeting participants and evaluates these potential
candidates in accordance with a relevance metric at block 502. The
relevance metric, generally, refers to a technique for measuring
various interaction indicia between a potential candidate and a
user into attributes (e.g., attribute values) and then, combining
the attributes into a value or score representing relevancy of that
potential candidate to the user (i.e., a relevance value). For
example, the logic flow 500 may identify, from relationship data
(e.g., the relationship data 170 of FIG. 1), attribute values and
score these relevance values in accordance with the relevance
metric. The logic flow 500 may adjust these values with project
data by determining attribute values for potential candidates for
meeting participants based upon same or similar projects and
aggregate the relevance values with the above attribute values into
aggregated relevance values.
[0061] The logic flow 500 may build a connectivity network based
upon relevancy at block 504. For example, the logic flow 500 may
generate the connectivity network 200 of FIG. 2 by linking the user
to each potential candidate and then, assign a relevance value to
each link. As illustrated in FIG. 2, the connectivity network 200
may use length to distinguish links of different relevance values.
In some embodiments, the connectivity network 200 need not be
graphical but may include a listing of potential candidates and one
or more relevance values.
[0062] The logic flow 500 may populate open meeting spaces in a
schedule with meeting data at block 506. For example, the logic
flow 500 may access the availability data 180 of FIG. 1 from the
user's schedule and corresponding schedules of the potential
candidates, combine the availability data and the connectivity
network, and, via an optimization mechanism executing a
combinatorial optimization technique, determine an optimal
arrangement of meetings to insert into the user's schedule in at
least some of the open meeting spaces. The present disclosure
describes some embodiments of the optimal (or near-optimal)
arrangement of meetings in the user's schedule as being configured
to maximize (or substantially maximize) the relevancy--as measured
through the relevance values--between the user and the set of the
potential candidates. The availability data generally refers to
time and date information of the open meeting spaces in both the
user's schedule and the corresponding schedules of the potential
candidates and is operative to reduce a search space of the optimal
arrangement to a management one, enabling the execution of the
optimization technique. The connectivity network, providing the
relevance values, further enables the optimization technique by
providing a management structure for the relevance values. The
connectivity network as described herein may improve the
optimization technique over other structures including other
networks or graph data. The embodiments are not limited to this
example.
[0063] FIG. 6 illustrates one embodiment of a logic flow 600. The
logic flow 600 may be representative of some or all of the
operations executed by one or more embodiments described
herein.
[0064] In the illustrated embodiment shown in FIG. 6, the logic
flow 600 may process internal network interactions at block 602.
For example, the logic flow 600 may process communications between
a user's device(s) and devices in at least one internal network.
The logic flow 600 may process external network interactions at
block 604. For example, the logic flow 600 may process
communications between the user's device(s) and devices in at least
one external network.
[0065] The logic flow 600 may build a connectivity network at block
606. For example, the logic flow 600 may build the connectivity
network 200 of FIG. 2 where each link represents a relevance value.
Using different metrics (e.g., relevance metrics) results in
different connectivity networks indicating different levels of
interaction between the user and the potential candidates. It is
appreciated that the logic flow 600 may build other connectivity
networks using various techniques such that the links may represent
other values. As described herein, the logic flow 600 may generate
the connectivity network to reflect topic relevance or
connectedness relevance between the user and the potential
candidates.
[0066] The logic flow 600 may adjust the connectivity network based
upon project data and/or other data at block 608. For example, the
logic flow 600 may adjust graph data underlying the connectivity
network 200 by modifying one or more of the values defining links
between the user and potential candidates. At least part of the
project data corresponds to one or more pending company projects by
the user and, as such, a potential candidate who also shares a
project is very relevant to the user. Accordingly, a link's value
indicating very few interactions between the user and the potential
candidate may increase and may also exceed other values defining
relationships with a significant amount of interactions. This may
be the case if the potential candidate is an executive and thus,
would have very few interactions with the user but would be
relevant to a pending project. In addition to the potential
candidate's importance in the company and/or to the project, the
logic flow 600 may increase the value for the potential candidate
in the connectivity network if the potential candidate is required
for a task. In addition, the logic flow 600 may adjust the
connectivity network in response to changes in the relationship
data between the user and the potential candidates. The embodiments
are not limited to this example.
[0067] FIG. 7 illustrates one embodiment of a logic flow 700. The
logic flow 700 may be representative of some or all of the
operations executed by one or more embodiments described
herein.
[0068] In the illustrated embodiment shown in FIG. 7, the logic
flow 700 ranks potential candidates and process availability data
of the potential candidates at block 702. For example, the logic
flow 700 may rely on relevance values to rank employees at a new
location and build a connectivity network (e.g., the connectivity
network 200 of FIG. 2) for a user. It is appreciated that the logic
flow 700 may execute at any time and may be effective during a
travel booking operation to the new location and/or in response to
changes in relationship data (e.g., the relationship data 170 of
FIG. 1). The travel booking operation would be any electronic
booking operation for travel to the new location, such as through a
commercial web site on the Internet.
[0069] The logic flow 700 may identify opportunities for meetings
at block 704. For example, the logic flow 700 may identify
opportunities for face-to-face meetings, virtual meetings, group
meetings, and/or the like by examining meeting data in the user's
schedule and corresponding schedules of the employees at the new
location. An open meeting space shared between the user's schedule
and at least one of the corresponding schedules may constitute such
an opportunity.
[0070] The logic flow 700 may identify events to join at block 706.
For example, the logic flow 700 may identify existing meetings or
social events at the new location to add to the user's schedule
while performing the travel booking operation to the new location.
If there is open space in the user's schedule for a particular
social event, for instance, the logic flow 700 inserts information
of the particular social event into the open space.
[0071] The logic flow 700 may execute an optimization mechanism to
generate a schedule at block 708. For example, the logic flow 700,
invoking the optimization mechanism 190 of FIG. 1, may execute a
combinatorial optimization technique to determine an optimal
arrangement of meetings to add to the user's schedule and/or the
corresponding schedules of the potential candidates. As described
herein, the combinatorial optimization technique is enabled by
inputs comprising availability data corresponding to the
above-mentioned open space in the user's schedule and/or the
corresponding schedules and values comprising the connectivity
network.
[0072] The logic flow 700 may establish meetings by modifying
corresponding schedule data of meeting participants at block 710.
For example, the logic flow 700 may establish these meetings for
potential candidates/device owners in an internal network where the
potential candidates/device owners utilize one or more enterprise
applications for meetings and to communicate with each other. As
described herein, these enterprise applications include a calendar
application, an email application, collaboration tools, and/or the
like. At least one application establishes meetings and manages a
schedule for the user and, more importantly, provides an
Application Programming Interface (API). The logic flow 700 may
communicate a request or a control directive invoking a function of
the API to establish a meeting. The logic flow 700 may communicate
the request or the control directive to insert appropriate
information into a schedule of a meeting participant and such
meeting data effectively creates a meeting between the user and the
meeting participant.
[0073] The logic flow 700 may be executed based upon travel slots
being assigned in the user's schedule (e.g., calendar). Before the
user is scheduled for travel to a travel destination, the logic
flow 700 executes and ranks, according to relevance values,
potential meeting participants at the travel destination. In some
embodiments, the logic flow 700 may send a notification to inform a
potential meeting participant that the user is travelling to their
office location next week and has some availability at a particular
time slot (e.g., ten (10) am on Monday, Oct. 1, 2018). The
notification may be an email message with an HTML element
configured to connect the user with the potential meeting
participant. When the HTML element is activated (e.g., via a touch
command), the logic flow 700 instructs the user's calendar
application and the potential meeting participant's calendar
application to add a meeting at the particular time slot, for
example, by instructing each calendar application's API to insert
meeting data into either the user's schedule or the potential
meeting participant's schedule.
[0074] In some alternative embodiments, the logic flow 700 may be
executed for a user at a physical location to which potential
meeting participants are traveling. The logic flow 700 may rank the
potential meeting participants according to relevance values. In
addition to interaction indicia, the logic flow 700 may define
attributes and attribute values for configurable user preferences
and/or feedback. Via the logic flow 700, for example, the user may
configure (e.g., in a profile) the system 100 to try to schedule
meetings with data scientists or design people when they happen to
be coming to the user's home office location--regardless of whether
or not the user previously interacted with any of them. The
embodiments are not limited to this example.
[0075] FIG. 8 illustrates an embodiment of an exemplary computing
architecture 800 suitable for implementing various embodiments as
previously described. In one embodiment, the computing architecture
800 may comprise or be implemented as part of an electronic device.
Examples of an electronic device may include those described with
reference to FIG. 8, among others. The embodiments are not limited
in this context.
[0076] As used in this application, the terms "system" and
"component" are intended to refer to a computer-related entity,
either hardware, a combination of hardware and software, software,
or software in execution, examples of which are provided by the
exemplary computing architecture 800. For example, a component can
be, but is not limited to being, a process running on a processor,
a processor, a hard disk drive, multiple storage drives (of optical
and/or magnetic storage medium), an object, an executable, a thread
of execution, a program, and/or a computer. By way of illustration,
both an application running on a server and the server can be a
component. One or more components can reside within a process
and/or thread of execution, and a component can be localized on one
computer and/or distributed between two or more computers. Further,
components may be communicatively coupled to each other by various
types of communications media to coordinate operations. The
coordination may involve the uni-directional or bi-directional
exchange of information. For instance, the components may
communicate information in the form of signals communicated over
the communications media. The information can be implemented as
signals allocated to various signal lines. In such allocations,
each message is a signal. Further embodiments, however, may
alternatively employ data messages. Such data messages may be sent
across various connections. Exemplary connections include parallel
interfaces, serial interfaces, and bus interfaces.
[0077] The computing architecture 800 includes various common
computing elements, such as one or more processors, multi-core
processors, co-processors, memory units, chipsets, controllers,
peripherals, interfaces, oscillators, timing devices, video cards,
audio cards, multimedia input/output (I/O) components, power
supplies, and so forth. The embodiments, however, are not limited
to implementation by the computing architecture 800.
[0078] As shown in FIG. 8, the computing architecture 800 comprises
a processing unit 804, a system memory 806 and a system bus 808.
The processing unit 804 can be any of various commercially
available processors, including without limitation an AMD.RTM.
Athlon.RTM., Duron.RTM. and Opteron.RTM. processors; ARM.RTM.
application, embedded and secure processors; IBM.RTM. and
Motorola.RTM. DragonBall.RTM. and PowerPC.RTM. processors; IBM and
Sony.RTM. Cell processors; Intel.RTM. Celeron.RTM., Core (2)
Duo.RTM., Itanium.RTM., Pentium.RTM., Xeon.RTM., and XScale.RTM.
processors; and similar processors. Dual microprocessors,
multi-core processors, and other multi-processor architectures may
also be employed as the processing unit 804.
[0079] The system bus 808 provides an interface for system
components including, but not limited to, the system memory 806 to
the processing unit 804. The system bus 808 can be any of several
types of bus structure that may further interconnect to a memory
bus (with or without a memory controller), a peripheral bus, and a
local bus using any of a variety of commercially available bus
architectures. Interface adapters may connect to the system bus 808
via a slot architecture. Example slot architectures may include
without limitation Accelerated Graphics Port (AGP), Card Bus,
(Extended) Industry Standard Architecture ((E)ISA), Micro Channel
Architecture (MCA), NuBus, Peripheral Component Interconnect
(Extended) (PCI(X)), PCI Express, Personal Computer Memory Card
International Association (PCMCIA), and the like.
[0080] The computing architecture 800 may comprise or implement
various articles of manufacture. An article of manufacture may
comprise a computer-readable storage medium to store logic.
Examples of a computer-readable storage medium may include any
tangible media capable of storing electronic data, including
volatile memory or non-volatile memory, removable or non-removable
memory, erasable or non-erasable memory, writeable or re-writeable
memory, and so forth. Examples of logic may include executable
computer program instructions implemented using any suitable type
of code, such as source code, compiled code, interpreted code,
executable code, static code, dynamic code, object-oriented code,
visual code, and the like. Embodiments may also be at least partly
implemented as instructions contained in or on a non-transitory
computer-readable medium, which may be read and executed by one or
more processors to enable performance of the operations described
herein.
[0081] The system memory 806 may include various types of
computer-readable storage media in the form of one or more higher
speed memory units, such as read-only memory (ROM), random-access
memory (RAM), dynamic RAM (DRAM), Double-Data-Rate DRAM (DDRAM),
synchronous DRAM (SDRAM), static RAM (SRAM), programmable ROM
(PROM), erasable programmable ROM (EPROM), electrically erasable
programmable ROM (EEPROM), flash memory, polymer memory such as
ferroelectric polymer memory, ovonic memory, phase change or
ferroelectric memory, silicon-oxide-nitride-oxide-silicon (SONOS)
memory, magnetic or optical cards, an array of devices such as
Redundant Array of Independent Disks (RAID) drives, solid state
memory devices (e.g., USB memory, solid state drives (SSD) and any
other type of storage media suitable for storing information. In
the illustrated embodiment shown in FIG. 8, the system memory 806
can include non-volatile memory 810 and/or volatile memory 812. A
basic input/output system (BIOS) can be stored in the non-volatile
memory 810.
[0082] The computer 802 may include various types of
computer-readable storage media in the form of one or more lower
speed memory units, including an internal (or external) hard disk
drive (HDD) 814, a magnetic floppy disk drive (FDD) 816 to read
from or write to a removable magnetic disk 818, and an optical disk
drive 820 to read from or write to a removable optical disk 822
(e.g., a CD-ROM or DVD). The HDD 814, FDD 816 and optical disk
drive 820 can be connected to the system bus 808 by a HDD interface
824, an FDD interface 826 and an optical drive interface 828,
respectively. The HDD interface 824 for external drive
implementations can include at least one or both of Universal
Serial Bus (USB) and IEEE 1394 interface technologies.
[0083] The drives and associated computer-readable media provide
volatile and/or nonvolatile storage of data, data structures,
computer-executable instructions, and so forth. For example, a
number of program modules can be stored in the drives and memory
units 810, 812, including an operating system 830, one or more
application programs 832, other program modules 834, and program
data 836. In one embodiment, the one or more application programs
832, other program modules 834, and program data 836 can include,
for example, the various applications and/or components of the
system 100.
[0084] A user can enter commands and information into the computer
802 through one or more wire/wireless input devices, for example, a
keyboard 838 and a pointing device, such as a mouse 840. Other
input devices may include microphones, infra-red (IR) remote
controls, radio-frequency (RF) remote controls, game pads, stylus
pens, card readers, dongles, finger print readers, gloves, graphics
tablets, joysticks, keyboards, retina readers, touch screens (e.g.,
capacitive, resistive, etc.), trackballs, trackpads, sensors,
styluses, and the like. These and other input devices are often
connected to the processing unit 804 through an input device
interface 842 that is coupled to the system bus 808, but can be
connected by other interfaces such as a parallel port, IEEE 1394
serial port, a game port, a USB port, an IR interface, and so
forth.
[0085] A monitor 844 or other type of display device is also
connected to the system bus 808 via an interface, such as a video
adaptor 846. The monitor 844 may be internal or external to the
computer 802. In addition to the monitor 844, a computer typically
includes other peripheral output devices, such as speakers,
printers, and so forth.
[0086] The computer 802 may operate in a networked environment
using logical connections via wire and/or wireless communications
to one or more remote computers, such as a remote computer 848. The
remote computer 848 can be a workstation, a server computer, a
router, a personal computer, portable computer,
microprocessor-based entertainment appliance, a peer device or
other common network node, and typically includes many or all of
the elements described relative to the computer 802, although, for
purposes of brevity, only a memory/storage device 850 is
illustrated. The logical connections depicted include wire/wireless
connectivity to a local area network (LAN) 852 and/or larger
networks, for example, a wide area network (WAN) 854. Such LAN and
WAN networking environments are commonplace in offices and
companies, and facilitate enterprise-wide computer networks, such
as intranets, all of which may connect to a global communications
network, for example, the Internet.
[0087] When used in a LAN networking environment, the computer 802
is connected to the LAN 852 through a wire and/or wireless
communication network interface or adaptor 856. The adaptor 856 can
facilitate wire and/or wireless communications to the LAN 852,
which may also include a wireless access point disposed thereon for
communicating with the wireless functionality of the adaptor
856.
[0088] When used in a WAN networking environment, the computer 802
can include a modem 858, or is connected to a communications server
on the WAN 854, or has other means for establishing communications
over the WAN 854, such as by way of the Internet. The modem 858,
which can be internal or external and a wire and/or wireless
device, connects to the system bus 808 via the input device
interface 842. In a networked environment, program modules depicted
relative to the computer 802, or portions thereof, can be stored in
the remote memory/storage device 850. It will be appreciated that
the network connections shown are exemplary and other means of
establishing a communications link between the computers can be
used.
[0089] The computer 802 is operable to communicate with wire and
wireless devices or entities using the IEEE 802 family of
standards, such as wireless devices operatively disposed in
wireless communication (e.g., IEEE 802.11 over-the-air modulation
techniques). This includes at least Wi-Fi (or Wireless Fidelity),
WiMax, and Bluetooth.TM. wireless technologies, among others. Thus,
the communication can be a predefined structure as with a
conventional network or simply an ad hoc communication between at
least two devices. Wi-Fi networks use radio technologies called
IEEE 802.11x (a, b, g, n, etc.) to provide secure, reliable, fast
wireless connectivity. A Wi-Fi network can be used to connect
computers to each other, to the Internet, and to wire networks
(which use IEEE 802.3-related media and functions).
[0090] FIG. 9 illustrates a block diagram of an exemplary
communications architecture 900 suitable for implementing various
embodiments as previously described. The communications
architecture 900 includes various common communications elements,
such as a transmitter, receiver, transceiver, radio, network
interface, baseband processor, antenna, amplifiers, filters, power
supplies, and so forth. The embodiments, however, are not limited
to implementation by the communications architecture 900.
[0091] As shown in FIG. 9, the communications architecture 900
comprises includes one or more clients 902 and servers 904. The
clients 902 may implement the client device 910. The servers 904
may implement the server device 950. The clients 902 and the
servers 904 are operatively connected to one or more respective
client data stores 908 and server data stores 910 that can be
employed to store information local to the respective clients 902
and servers 904, such as cookies and/or associated contextual
information.
[0092] The clients 902 and the servers 904 may communicate
information between each other using a communication framework 906.
The communications framework 906 may implement any well-known
communications techniques and protocols. The communications
framework 906 may be implemented as a packet-switched network
(e.g., public networks such as the Internet, private networks such
as an enterprise intranet, and so forth), a circuit-switched
network (e.g., the public switched telephone network), or a
combination of a packet-switched network and a circuit-switched
network (with suitable gateways and translators).
[0093] The communications framework 906 may implement various
network interfaces arranged to accept, communicate, and connect to
a communications network. A network interface may be regarded as a
specialized form of an input output interface. Network interfaces
may employ connection protocols including without limitation direct
connect, Ethernet (e.g., thick, thin, twisted pair 10/100/1000 Base
T, and the like), token ring, wireless network interfaces, cellular
network interfaces, IEEE 802.11a-x network interfaces, IEEE 802.16
network interfaces, IEEE 802.20 network interfaces, and the like.
Further, multiple network interfaces may be used to engage with
various communications network types. For example, multiple network
interfaces may be employed to allow for the communication over
broadcast, multicast, and unicast networks. Should processing
requirements dictate a greater amount speed and capacity,
distributed network controller architectures may similarly be
employed to pool, load balance, and otherwise increase the
communicative bandwidth required by clients 902 and the servers
904. A communications network may be any one and the combination of
wired and/or wireless networks including without limitation a
direct interconnection, a secured custom connection, a private
network (e.g., an enterprise intranet), a public network (e.g., the
Internet), a Personal Area Network (PAN), a Local Area Network
(LAN), a Metropolitan Area Network (MAN), an Operating Missions as
Nodes on the Internet (OMNI), a Wide Area Network (WAN), a wireless
network, a cellular network, and other communications networks.
[0094] Some embodiments may be described using the expression "one
embodiment" or "an embodiment" along with their derivatives. These
terms mean that a particular feature, structure, or characteristic
described in connection with the embodiment is included in at least
one embodiment. The appearances of the phrase "in one embodiment"
in various places in the specification are not necessarily all
referring to the same embodiment. Further, some embodiments may be
described using the expression "coupled" and "connected" along with
their derivatives. These terms are not necessarily intended as
synonyms for each other. For example, some embodiments may be
described using the terms "connected" and/or "coupled" to indicate
that two or more elements are in direct physical or electrical
contact with each other. The term "coupled," however, may also mean
that two or more elements are not in direct contact with each
other, but yet still co-operate or interact with each other.
[0095] It is emphasized that the Abstract of the Disclosure is
provided to allow a reader to quickly ascertain the nature of the
technical disclosure. It is submitted with the understanding that
it will not be used to interpret or limit the scope or meaning of
the claims. In addition, in the foregoing Detailed Description, it
can be seen that various features are grouped together in a single
embodiment for the purpose of streamlining the disclosure. This
method of disclosure is not to be interpreted as reflecting an
intention that the claimed embodiments require more features than
are expressly recited in each claim. Rather, as the following
claims reflect, inventive subject matter lies in less than all
features of a single disclosed embodiment. Thus the following
claims are hereby incorporated into the Detailed Description, with
each claim standing on its own as a separate embodiment. In the
appended claims, the terms "including" and "in which" are used as
the plain-English equivalents of the respective terms "comprising"
and "wherein," respectively. Moreover, the terms "first," "second,"
"third," and so forth, are used merely as labels, and are not
intended to impose numerical requirements on their objects.
[0096] What has been described above includes examples of the
disclosed architecture. It is, of course, not possible to describe
every conceivable combination of components and/or methodologies,
but one of ordinary skill in the art may recognize that many
further combinations and permutations are possible. Accordingly,
the novel architecture is intended to embrace all such alterations,
modifications and variations that fall within the spirit and scope
of the appended claims.
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