U.S. patent application number 13/070253 was filed with the patent office on 2012-09-27 for method and system of building store product finders.
This patent application is currently assigned to eBay Inc.. Invention is credited to Chaoou Huang, Daniel Tsun Kao, Sonya Rongsheng Liang, JinYu Lou, Qian Sun, Xiaobo Wu, Jian Xu, Yi Zhou.
Application Number | 20120246026 13/070253 |
Document ID | / |
Family ID | 46878127 |
Filed Date | 2012-09-27 |
United States Patent
Application |
20120246026 |
Kind Code |
A1 |
Xu; Jian ; et al. |
September 27, 2012 |
METHOD AND SYSTEM OF BUILDING STORE PRODUCT FINDERS
Abstract
One embodiment provides a system for building store product
finders. The system may include: a product search engine configured
to find, from product storage, a plurality of product subcategories
that match at least one store product category of the plurality of
store product categories, and a dominant product subcategory
determining device configured to determine a dominant product
subcategory. The dominant product subcategory has the highest
product coverage among the plurality of product subcategories. The
system may also include: a filter selecting device configured to
select at least one product search filter from a list of product
search filters, and a filter installing device configured to
install the at least one product search filter in the store product
finder.
Inventors: |
Xu; Jian; (Shanghai, CN)
; Sun; Qian; (ShangHai, CN) ; Lou; JinYu;
(Shanghai, CN) ; Zhou; Yi; (Shanghai, CN) ;
Wu; Xiaobo; (ShangHai, CN) ; Huang; Chaoou;
(Shanghai, CN) ; Kao; Daniel Tsun; (San Jose,
CA) ; Liang; Sonya Rongsheng; (Cupertino,
CA) |
Assignee: |
eBay Inc.
San Jose
CA
|
Family ID: |
46878127 |
Appl. No.: |
13/070253 |
Filed: |
March 23, 2011 |
Current U.S.
Class: |
705/26.63 |
Current CPC
Class: |
G06Q 30/0641 20130101;
G06Q 30/06 20130101; G06Q 30/0627 20130101 |
Class at
Publication: |
705/26.63 |
International
Class: |
G06Q 30/00 20060101
G06Q030/00 |
Claims
1. A method of building a store product finder, comprising:
receiving a selection of a store product category associated with a
store product finder; finding a plurality of products that match
the store category, each product matching to at least one product
subcategory of the store product category, each product subcategory
having a product coverage; using one or more processors coupled to
a memory, automatically determining a dominant product subcategory
that has a highest product coverage among a plurality of product
subcategories, the product coverage of a subcategory being a ratio
of a sum of supplied products within the product subcategory to a
sum of supplied products within the store product category;
presenting a list of product search filters predefined for the
dominant product subcategory; and installing into the store product
finder at least one product search filter selected from the list of
product search filters.
2. (canceled)
3. The method of claim 2, wherein designing the store product
finder in the live preview environment includes: receiving a
selection of a layout of the store product finder; receiving a
selection of a placement of the store product finder; and receiving
a custom cascading style sheet content to customize the store
product finder.
4. The method of claim 1, further comprising saving the store
product finder in a store product finder storage.
5. The method of claim 1, further comprising publishing by a
publishing device the store product finder into production.
6. The method of claim 1, further comprising embedding the store
product finder into a webpage by an asynchronous JavaScript
call,
7. The method of claim 6, wherein the JavaScript call is sent via
appending a JavaScript tag to a source code file of the webpage,
wherein a URL of the JavaScript call includes an identification of
the store product finder, wherein a response to the JavaScript call
includes a customization information, and wherein the store product
finder is embedded into the webpage based on the customization
information.
8. A system, comprising: one or more processors coupled to a
memory; a store product finder storage to store a plurality of
store product finders, each store product finder being associated
with a store product category of a plurality of store product
categories; a product search engine configured to find, from the
product storage, a plurality of products matching at least one
product subcategory of the store product category, each product
subcategory having a product coverage; a dominant product
subcategory determining device configured to determine, by using at
least one processor of the one or more processors, a dominant
product subcategory that has a highest product coverage among a
plurality of product subcategories, the product coverage of a
subcategory being a ratio of a sum of supplied products within the
product subcategory to a sum of supplied products within the store
product category; a filter selection device configured to select at
least one product search filter from a list of product search
filters predefined for the dominant product subcategory; and a
filter installing device configured to install the at least one
product search filter into the store product finder.
9. (canceled)
10. The system of claim 8, further comprising a store product
category storage to store the plurality of store product
categories.
11. The system of claim 8, further comprising a display to present
the list of product search filters predefined for the dominant
product subcategory.
12. The system of claim 8, further comprising a dominant product
subcategory storage to save the store dominant product
subcategory.
13. The system of claim 8, further comprising a finder publishing
device configured to publish the store product finder into
production.
14. The system of claim 8, further comprising a live preview
environment adapted to design the store product finder by receiving
a selection of a layout of the store product finder, receiving a
selection of a placement of the store product finder, and receiving
input of a custom cascading style sheet (CSS) content to customize
the store product finder.
15. A non-transitory machine-readable storage medium comprising
instructions that, when executed by one or more processors of a
machine, cause the machine to perform a method comprising:
receiving a selection of a store product category to be associated
with a store product finder; finding a plurality of products each
matching at least one subcategory of the store product category,
each product subcategory having a product coverage; determining a
dominant product subcategory that has a highest product coverage
among a plurality of product subcategories, wherein the product
coverage of a subcategory is a ratio of a sum of supplied products
within the product subcategory to a sum of supplied products within
the store product category; presenting a list of product search
filters predefined for the dominant product subcategory; and
installing into the store product finder at least one product
search filter selected from the list of product search filters.
16. (canceled)
17. The non-transitory machine-readable storage medium of claim 15,
wherein the method further comprises assigning a title to the store
product finder.
18. The non-transitory machine-readable storage medium of claim 15,
wherein the method further comprises designing the store product
finder in a live preview environment including.
19. The non-transitory machine-readable storage medium of claim 18,
wherein designing the store product finder includes: receiving a
selection of a layout of the store product finder; receiving a
selection of a placement of the store product finder; and receiving
input of a custom cascading style sheet content to customize the
store product finder.
20. The non-transitory machine-readable storage medium of claim 15,
wherein the method further comprises saving the store product
finder in a store product finder storage.
21. The non-transitory machine-readable storage medium of claim 15,
wherein the method further comprises embedding the store product
finder into a webpage by an asynchronous JavaScript call.
22. The non-transitory machine-readable storage medium of claim 19,
wherein the JavaScript call is sent via appending a JavaScript tag
to a source code file of the webpage, wherein a URL of the
JavaScript call includes an identification of the store product
finder, wherein a response to the JavaScript call includes a
customization information, and wherein the store product finder is
embedded into the webpage based on the customization information.
Description
TECHNICAL FIELD
[0001] The present application relates generally to information
processing and particularly, but not by way of limitation, to
systems and methods for building store product finders over a
network.
BACKGROUND
[0002] With the development of computer and network related
technologies, more users (e.g., sellers and buyers) participate
electronic commerce (e-commerce) activities or events. For example,
sellers or buyers may attempt to sell or purchase products (or
items) via networks (e.g., the Internet). In many situations,
sellers however may not provide buyers with efficient or convenient
approaches to find products that meet the demands or interests of
the buyers.
BRIEF DESCRIPTION OF THE DRAWINGS
[0003] Some embodiments are illustrated by way of examples and not
limitation in the figures of the accompanying drawings in
which:
[0004] FIG. 1 is a network diagram illustrating an e-commerce
shopping system that has client-server architecture in accordance
with an embodiment.
[0005] FIG. 2 is a block diagram illustrating multiple store
product finder building modules or devices in accordance with an
embodiment.
[0006] FIG. 3 is a high level entity-relationship diagram
illustrating various tables maintained in a database in accordance
with an embodiment.
[0007] FIG. 4 is a flowchart illustrating a method of building
store product finders via a network in accordance with an
embodiment.
[0008] FIG. 5 is a block diagram illustrating a machine in the
example form of a computer system, within which a set of sequence
of instructions for causing the machine to perform any one of the
methodologies discussed herein may be executed.
DETAILED DESCRIPTION
[0009] Example methods and systems to build store product finders
via a network are described. In the following description, for
purposes of explanation, numerous specific details are set forth in
order to provide a thorough understanding of example embodiments.
It will be evident, however, to one skilled in the art that the
present application may be practiced without these specific
details.
[0010] In Consumer-to-consumer (C2C) e-commerce sites (like
eBay.RTM.), sellers may run their own on-line stores to sell their
products or items. However, it could be time consuming for buyers
to search in the on-line stores to find the products that meet
their interests or needs. In some embodiments, a store product
finder building system may be used by sellers to build store
product finders, which offer the buyers the ability to find
products (or items) that meet the demands or interests of the
buyers based on product aspects or characteristics. For example,
the store product finder building system may facilitate sellers who
specialize in selling a variety of products (e.g., shoes etc) to
build store product finders, which enable buyers to search in the
on-line store to find specific products (e.g., men's running shoes)
based on product aspects (e.g., shoes sizes, shoes colors, and
shoes brands etc) that the buyers want.
Platform Architecture
[0011] FIG. 1 is a network diagram depicting an e-commerce shopping
system 100 having a client-server architecture in accordance with
an embodiment. The e-commerce shopping system 100 may include a
commerce server system 110 and one or more client machines (e.g., a
PC computer) 120, which are inter-connected via a network (e.g.,
the Internet) 130.
[0012] The network-based commerce server system 110, provides
server-side functionality, via a network 130 (e.g., the Internet or
Wide Area Network (WAN)) to the one or more client machines 120. An
Application Program Interface (API) server 111 and a web server 112
are coupled to, and provide programmatic and web interfaces
respectively to, at least one application server 113.
[0013] The application server 113 may include at least a store
product finder building system 114, which may include multiple
store product finder building modules or devices 200 as shown in
FIG. 2. The store product finder building system 114 may facilitate
sellers to build or create store product finders. Buyers may use
the built store product finders created by the sellers using
embodiments of the application to find products that meet their
demands or interests. The application server 113 is, as shown,
coupled to one or more database servers 115 that facilitate access
to one or more databases 116.
[0014] A seller or a buyer may access one of the client machines
120, and then may interact with the commerce server system 110 via
the network 130. Either or both a web client 122 (e.g., a browser),
and a programmatic client 124 may execute on a respective client
machine 120 for example. The web client 122 may access the store
product finder building system 114 via a web interface supported by
the web server 112 for example. Similarly, the programmatic client
124 may access the various services and functions provided by the
store product finder building system 114 via a programmatic
interface provided by the API server 111 for example.
[0015] FIG. 1 also illustrates a third party application 162,
executing on a third party server machine 160, as having
programmatic access to the networked commerce server 110 via the
programmatic interface provided by the API server 111. The third
party application 162 may utilize information retrieved from the
networked commerce server system 110 and support features or
functions on a website hosted by the third party. The third party
server machine 160 may provide e-commerce shopping functions or
services that are supported by the relevant applications and/or
devices of the networked commerce server system 110. The third
party server machine 160 may also provide data resources, which may
be provided to and utilized by certain modules (or devices) in the
store product finder building system 114.
[0016] While the store product finder building system 114 in FIG. 1
forms part of the networked commerce server system 110, it will be
appreciated that, in alternative embodiments, the store product
finder building system 114 may form part of an e-commerce shopping
service that is separate and distinct from the networked
system.
[0017] While the e-commerce shopping system 100 shown in FIG. 1
employs client-server architecture, the present application is not
limited to such architecture, and could equally well find
application in a distributed, multi-tiered or a peer-to-peer
architecture system for example. The store product finder building
system 114 could also be implemented as standalone software
programs, hardware or devices, which do not necessarily have
networking capabilities.
Store Product Finder Building System
[0018] FIG. 2 is a block diagram illustrating multiple store
product finder building modules or devices 200 of the store product
finder building system 114 in accordance with one example
embodiment. The store product finder building modules or devices
200 may facilitate sellers to build store product finders, which
may be defined using data structures that are stored in a storage,
to offer buyers the ability to find products based on product
aspects or characteristics for example.
[0019] In some embodiments, the store product finders may be saved
in a store product finder storage (e.g., a "store product finder"
table 302 as shown in FIG. 3), which may be a database inside or
outside of the store product finder building system 114. A name or
title (e.g., "men's shoes finder") may be assigned to the store
product finder either in the store product finder building process
or when the building process is finished.
[0020] In some embodiments, the store product finder building
modules or devices 200 of the store product finder building system
114 may include, but are not limited to, a store product category
selector 202, a product search engine 204, a dominant product
subcategory determining device 206, a filter selection device 208,
a display 210, a product finder installing device 212, a product
finder publishing device 214, and a live preview environment
216.
[0021] In some embodiments, the store product category selector 202
may provide an interface for selecting a store product category
(e.g., "men's shoes category") from a list of store product
categories (e.g., "men's shoes category" and "women's shoes
category") that are stored in a store product category storage
(e.g., a "store product category" table 304 as shown in FIG.
3).
[0022] In some embodiments, the product search engine 204 may
search a product storage (e.g., a "product" table 306, as shown in
FIG. 3) to retrieve a list of product subcategories within the
selected store product category. The list of product subcategories
may be stored in the product storage. Each retrieved product
subcategory may have a product coverage that in some embodiments is
defined as (a sum of product items within the product
subcategory)/(a sum of entire product items within the selected
store product category). For example, a product category (e.g.,
"shoes") includes product subcategories, e.g., a product
subcategory A (e.g., "women shoes"), a product subcategory B (e.g.,
"men shoes") and etc. The product category ("shoes") includes 5
product items, for example, Item #1 "Nike women basketball shoes
10001", Item #2 "Nike women tennis shoes 10002", Item #3 "Nike
women running shoes 10003", Item #4 "Adidas men running shoes
10004", and Item #5 "shoes laces 10005". Therefore, 3 product items
(Item #1, Item #2 and Item #3) of the product category ("shoes")
belong to and are thus mapped to the product subcategory A
("women's shoes"), and 1 product item (Item #4) belong to and is
thus mapped to the product subcategory B ("men shoes"). In this
case, the product subcategory A ("women shoes") has a product
coverage as (3/5=60%), and the product subcategory B ("men shoes")
has a product coverage as (1/5=20%).
[0023] Further in some embodiments the product coverage may be
determined as a weighted sum of various factors. For example,
product coverage may be determined as:
Product Coverage=Product Score/Total Product Score
where:
Product Score=Item Count Mapped to
product*ItemCountWeight+ItemDemand Mapped to
product*ItemDemandWeight
Total Product Score=Item Count Mapped to all
products*ItemCountWeight+ItemDemand Mapped to all
products*ItemDemandWeight [0024] Item Count means the number of
items maps to the product. [0025] Item Count Weight and Item demand
weight is the weight value for the corresponding factors. In some
embodiments, the value of the weight ranges from 0-1, and the sum
of the various weights is 1.
[0026] The above factors include demand components. By choosing a
non-zero item demand weight, item demand factors can be included in
the product coverage calculation. Thus the product coverage can
include item demand information in order to increase sales. Item
demand can be determined in various ways. For example, in some
embodiments, the item demand components may be defined as
follows:
Item Demand=Normalized Recent Sales*Weight1+Normalized Item Watch
Count*Weight2+Normalized Product Saved Count*Weight3
[0027] where: [0028] Normalized Recent Sales is the value (ranges
from 0-1) to reflect recent sales status in a certain period (for
e.g. in the past 1 week). For example, 1 means sold most recently.
While 0.1 means sold few recently. [0029] Normalized Item Watch
Count: the items' watched count--the number of page views of this
item. The value may be normalized to 0-1. 1 means most watched
item. A small value means less watched item. [0030] Normalized
Product Saved Count: (ranges from 0-1) to reflect the popularity of
a product by calculating how many people saved this product (i.e.
add this product to their favorite products, which is an existing
functionality provided by eBay and other online merchants like
Amazon). The exact decision of various weights may be done via
business performance analysis. In some embodiments, the sum of the
weights may be normalized such that the sum of weights is 1.
[0031] The following examples illustrate the above concepts.
EXAMPLE 1
Product Coverage Based Purely on Item Count
[0032] ItemCountWeight=1 [0033] ItemDemandWeight=0
TABLE-US-00001 [0033] Item Detail Item Count Mapped Product Item#1
Man basketball 1 Men's Shoes shoes Item#2 Man tennis shoes 1 Men's
Shoes Item#3 Man football 1 Men's Shoes shoes Item#4 Adidas Women 1
Women's Shoes running shoes Item#5 Adidas Women 1 Women's clothes
Clothes Total 5
Product Coverage
TABLE-US-00002 [0034] Product Product Score Coverage Men's Shoes 3
* 1 60% Women's Shoes 1 * 1 20% Women's Clothes 1 * 1 20% Total
Product Score 3 * 1 + 1 * 1 + 1 * 1 = 5
EXAMPLE 2
Product Coverage Based on Item Count and Item Demand
[0035] This example illustrates a non-zero item demand weight and
adds item demand factors into product coverage calculation. Thus
the product coverage can include item demand info in order to
increase sales. [0036] For the purposes of this example, Item Count
weight has been chosen as 0.5 and Item Demand weight as 0.5. This
choice of weight takes both factors equally. As noted above, the
weights may vary from this example; the exact decision of various
weights is normally done via business performance analysis.
TABLE-US-00003 [0036] Item Detail Item Count Mapped Product Item#1
Man basketball 1 Men's Shoes shoes Item#2 Man tennis shoes 1 Men's
Shoes Item#3 Man football 1 Men's Shoes shoes Item#4 Adidas Women 1
Women's Shoes running shoes Item#5 Adidas Women 1 Women's clothes
Clothes Total 5 , in this example Item demand weight1 = 0.25,
Weight2 = 0.25, weight3 = 0.5.
[0037] This means that the Normalized product saved count is given
more weight. Again, the actual weight may be determined by business
performance analysis. The weights used here are for illustration
purpose.
TABLE-US-00004 [0037] Normalized Normalized Product Normalized Item
Watch Saved Weighted Item Recent Sales Count Count Demand Score
Item#1 1 1 0.8 0.9 Item#2 1 1 0.8 0.9 Item#3 0.5 0.6 0.2 0.375
Item#4 0.5 0.6 0.1 0.325 Item#5 0.1 0.2 0.1 0.125 Total 2.625
[0038] Product Coverage
TABLE-US-00005 Product Score Product Coverage Men's Shoes 3 * 1 +
0.9 + 0.9 + 53.8% 0.375 = 5.175 Women's 1 * 1 + 0.325 = 2.325 24.2%
Shoes Women's 1 * 1 + 0.125 = 2.125 22.0% Clothes Total Product
9.625 100% Score
[0039] Those of skill in the art having the benefit of the
disclosure will appreciate that alternative formulations for
product coverage may be used and are within the scope of the
inventive subject matter. For example, a formula based on value or
price of subcategories and the product category could be used. As
an example, allormalized Item Price may be a normalized price score
(0-1) for an item. The higher score means the item has a lower
price.
[0040] In some embodiments, the dominant product subcategory
determining device 206 may determine a dominant (or winning)
product subcategory that has the highest product coverage among
product subcategories within the store product category. Each
dominant product subcategory may be stored in a dominant product
subcategory storage (e.g., a "dominant product subcategory" table
308 as shown in FIG. 3).
[0041] In some embodiments, a display 208 (e.g., a computer
monitor) may present a list of product search filters that have
been predefined (or built) for the determined dominant product.
[0042] In some embodiments, a filter selection device 210 may
provide an interface allowing a user (e.g., a seller of the on-line
store) to select one or more product search filters from the list
of product search filters. The selected product search filters may
be stored in a product filter storage (e.g., a "product search
filter" table 310 as shown in FIG. 3).
[0043] In some embodiments, a product filter installing device 212
may install the selected product search filters into a store
product finder. The selected product search filters are thus
associated or linked to the store product finder, so as to
facilitate buyers to search and find products that meet their
requirements or demands based on the product aspects or
characteristics.
[0044] In some embodiments, a product finder publishing device 214
may publish the built store product finders into production. The
publishing may move the store product finders from a live preview
environment to a production environment so that buyers may see the
store product finders. In some embodiments, in a live preview
environment 216 (e.g., an interface displayed on a display device),
a seller of the on-line store may design the built store product
finder. Before publishing, only store owners may see the store
product finders in the live preview environment. For example, the
seller may select a layout of the store product finder in the live
preview environment 216. The seller may also select a placement of
the store product finder in the live preview environment 216. In
the live preview environment 216, a seller may also input custom
cascading style sheet (CSS) content to customize the built store
product finder for example.
[0045] In some embodiments, the store product finder building
modules or devices 200 may be hosted on a dedicated server machine
or on shared server machines that are communicatively coupled to
enable communications between these server machines.
[0046] In some embodiments, the store product finder building
modules or devices 200 themselves are communicatively coupled
(e.g., via appropriate interfaces) to each other and to various
data sources, so as to allow information to be passed between these
modules or devices or so as to allow these modules or devices to
share and access common data.
[0047] In some embodiments, the store product finder building
modules or devices 200 may be coupled to a bus, network or shared
memory for example and thus may communicate with each other. These
store product finder building modules or devices 200 may
furthermore obtain access to one or more databases 116 via the
database server 115 (as shown in FIG. 1).
[0048] In some embodiments, the store product finder building
modules (or devices) 200 may be implemented in software, hardware,
or as a combination of software and hardware. These multiple
modules or devices 200 may provide a number of functions and/or
services to users (e.g., sellers or buyers) of the network-based
commerce server system 110.
Data Structures
[0049] FIG. 3 is a high-level entity-relationship diagram,
illustrating various tables 300 that may be maintained within the
databases 116 as shown in FIG. 1, and that support and are utilized
by the multiple store product finder building modules or devices
200 as shown in FIG. 2. The various tables 300 may include, but are
not limited to, a "store product finder" table 302, a "store
product category" table 304, a "product" table 306, a "dominant
product" table 308, and a "product search filter" table 310.
[0050] Each "store product finder" table 302 may contain records
for each store product finder, which has been built by a seller of
an on-line product store to offer buyers with the ability to search
and find products based on product aspects or characteristics for
example. Each "store product finder" table 302 may include fields,
but not limited to, a store product finder identifier, a store
product finder name, and a store product category identifier of a
store product category that is associated with the store product
finder.
[0051] Each "store product category" table 304 may contain records
for each store product category that is associated with one or more
store product finders for example. Each "store product category"
table 304 may include fields, but not limited to, a store product
category identifier, and a store product category name.
[0052] Each "product subcategory" table 306 may contain records for
each product subcategory offered to sell by the online product
store for example. Each "product subcategory" table 306 may include
fields, but not limited to, a product subcategory identifier, a
product subcategory name, and a product category identifier of a
product category to which the product subcategory belongs.
[0053] Each "dominant product subcategory" table 308 may contain
records for each dominant product subcategory offered to sell by
the online product store for example. Each "dominant product
subcategory" table 308 may include fields, but not limited to, a
dominant product subcategory identifier, a dominant product
subcategory name, and a store product category identifier of a
store product category to which the dominant product subcategory
belongs.
[0054] Each "product search filter" table 310 may contain records
for each product search filter, which has been predefined for the
dominant product subcategory. Each "product search filter" table
310 may include fields, but not limited to, a product filter
identifier, a product filter name, a dominant product subcategory
identifier, and a store product finder identifier to which the
product search filter is linked. For example, a user (e.g., a
seller of the online store) may select one or more product search
filters to be linked or associated with a particular store product
finder.
Methods of Building Store Product Finders
[0055] FIG. 4 is a flowchart illustrating a method 400 of building
store product finders via a network in accordance with an
embodiment of the present application.
[0056] At operation 402, a name or title (e.g., "men's shoes
finder") may be assigned to a store product finder, which may be
saved in a store product finder storage (e.g., a "store product
finder" table 302 as shown in FIG. 3).
[0057] At operation 404, a store product category selector 202 may
select a store product category (e.g., "shoes category") from a
list of store product categories (e.g., "shoes category" and
"clothes category"), which may be stored in a store product
category storage (e.g., a "store product category" table 304 as
shown in FIG. 3). Store product categories may be maintained by
store owners. The selection may be received through a user
interface or it may be received through programmatically through an
application program interface.
[0058] At operation 406, a product search engine 204 may find a
plurality of product subcategories (e.g., "men shoes", and "women
shoes", etc) that belongs to or matches the selected store product
category (e.g., "shoes category"). The search may be based on the
selection of the store product category by a user (e.g., a seller
or a buyer).
[0059] At operation 408, a dominant product subcategory determining
device 206 may determine a dominant product subcategory, which is
defined as a product subcategory that has the highest product
coverage among the plurality of product subcategories (e.g., "men
shoes", "women shoes", etc). The product coverage of a product
subcategory is defined as (a sum of product items within the
product subcategory)/(a sum of product items within the selected
store product category).
[0060] For example, if the "women shoes " product subcategory has
60% product coverage, the "men shoes" product subcategory has 20%
product coverage, and the rest of the products in the category have
20% product coverage, the "women shoes " product subcategory is
determined as the dominant or wining product subcategory to be
associated with the selected store product category (e.g., "shoes
category").
[0061] At operation 410, a display 208 may present a list of
product search filters, which have been predefined for the dominant
product subcategory and have been saved in a product search filter
storage (e.g., a product search filter table 310 as shown in FIG.
3). For example, each dominant product subcategory (e.g., "women
shoes") may have product search filters (e.g., "size (6, 8, 10)",
"color (white, black, red)", "brand" etc) that have been predefined
for the dominant product subcategory.
[0062] At operation 412, a filter selection device 210 may
facilitate a user (e.g., a seller of the online store) to select
one or more product search filters from the list of product search
filters. For example, the seller of the online store may select,
from the list of product search filters, one or more product search
filters (e.g., "size (6, 8, 10)" and "color (white, black, red)")
as the product search filters to be linked to the store product
finder (e.g., "women shoes finder").
[0063] At operation 414, a product filter installing device 210 may
install the selected product search filters (e.g., "size (6, 8,
10)" and "color (white, black, red)") into the store product finder
(e.g., "women's shoes finder"). In some embodiments, the selected
product search filters may be installed into the store product
finder by linking the filters to the store product finder.
[0064] In some embodiments, a store product finder publishing
device 212 may publish the built store product finder into
production to make it available for the public to use.
[0065] An example situation illustrating the use of the store
finder is as follows. A buyer may visit an e-commerce store with
store product finders created using the systems and methods
described above. When the buyer clicks a store product category
(e.g., "men's shoes category"), one or more built store product
finders (e.g., "men's shoes finder") may appear on a webpage of the
online store. Then, the buyer may select one or more product search
filters (e.g., "size (6, 8, 10)" and "color (white, black, red)")
to search for the products (e.g., men's shoes) that meets his/her
interests or demands based on the product aspects or
characteristics (e.g., the size and the color).
[0066] At operation 416, the built store product finder may be
designed in a live preview environment 216 as shown in FIG. 2. A
user (e.g., a seller or buyer of the online store) may select a
layout and/or a placement of the store product finder. For example,
the user may input custom cascading style sheet (CSS) content to
customize the store product finder.
[0067] At operation 418, the store product finder may be embedded
into a webpage by for example an asynchronous JavaScript call. In
some embodiments, the JavaScript call may be sent by appending a
JavaScript tag to a source code file of the webpage. In some
embodiments, a URL of the JavaScript call may include an
identification of the store product finder. A response to the
JavaScript call may include customization information. In some
embodiments, the store product finders may be embedded into the
webpage based on the customization information.
An Example Computer System
[0068] FIG. 5 is a block diagram illustrating a machine in the
example form of a computer system 500, within which a set of
sequence of instructions for causing the machine to perform any one
of the methodologies discussed herein may be executed. In
alternative embodiments, the machine may be a server computer, a
client computer, 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, switch or bridge, or
any machine capable of executing a set of instructions 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 of instructions to perform any one or more of the
methodologies discussed herein.
[0069] The example computer system 500 includes a processor 502
(e.g., a central processing unit (CPU) a graphics processing unit
(GPU) or both), a main memory 504 and a static memory 506, which
communicate with each other via a bus 508. The computer system 500
may further include a video display unit 510 (e.g., a liquid
crystal display (LCD) or a cathode ray tube (CRT)). The computer
system 500 also includes an alphanumeric input device 512 (e.g., a
keyboard), a cursor control device 514 (e.g., a mouse), a disk
drive unit 516, a signal generation device 518 (e.g., a speaker)
and a network interface device 520.
[0070] The disk drive unit 516 includes a machine-readable medium
522 on which is stored one or more sets of instructions (e.g.,
software 524) embodying any one or more of the methodologies or
functions described herein. The software 524 may also reside,
completely or at least partially, within the main memory 504 and/or
within the processor 502 during execution thereof by the computer
system 500, the main memory 504 and the processor 502 also
constituting machine-readable media.
[0071] The software 524 may further be transmitted or received over
a network 526 via the network interface device 520. While the
machine-readable medium 522 is shown in an example embodiment to be
a single medium, the term "machine-readable medium" should be taken
to include a single medium or multiple media (e.g., a centralized
or distributed database, and/or associated caches and servers) that
store the one or more sets of instructions. The term
"machine-readable medium" shall also be taken to include any medium
that is capable of storing, encoding or carrying a set of
instructions for execution by the machine and that cause the
machine to perform any one or more of the methodologies of the
present invention. The term "machine-readable medium" shall
accordingly be taken to include, but not be limited to, solid-state
memories, optical and magnetic media, and carrier wave signals.
[0072] Thus, methods and systems for providing e-commerce shopping
guidance to a customer via networks have been described. Although
the present application has been described with reference to
specific embodiments, it will be evident that various modifications
and changes may be made to these embodiments without departing from
the broader spirit and scope of the invention. Accordingly, the
specification and drawings are to be regarded in an illustrative
rather than a restrictive sense.
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