US20150170248A1 - Product and content association - Google Patents

Product and content association Download PDF

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Publication number
US20150170248A1
US20150170248A1 US14/104,070 US201314104070A US2015170248A1 US 20150170248 A1 US20150170248 A1 US 20150170248A1 US 201314104070 A US201314104070 A US 201314104070A US 2015170248 A1 US2015170248 A1 US 2015170248A1
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United States
Prior art keywords
product
content
phrases
distribution
computing device
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Abandoned
Application number
US14/104,070
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English (en)
Inventor
Eui Chung
Bharath Sridharan
Seyed Alireza Forouzan Ebrahimi
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Transform Sr Brands LLC
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Sears Brands LLC
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
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Publication date
Assigned to SEARS BRANDS, L.L.C. reassignment SEARS BRANDS, L.L.C. ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: SRIDHARAN, BHARATH, Chung, Eui, EBRAHIMI, SEYED ALIREZA FOROUZAN
Priority to US14/104,070 priority Critical patent/US20150170248A1/en
Application filed by Sears Brands LLC filed Critical Sears Brands LLC
Priority to MX2014015348A priority patent/MX2014015348A/es
Priority to CA2874614A priority patent/CA2874614A1/en
Priority to EP14197661.3A priority patent/EP2884451A1/en
Publication of US20150170248A1 publication Critical patent/US20150170248A1/en
Assigned to JPP, LLC reassignment JPP, LLC SECURITY INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: SEARS BRANDS, L.L.C.
Assigned to CANTOR FITZGERALD SECURITIES, AS AGENT reassignment CANTOR FITZGERALD SECURITIES, AS AGENT SECURITY INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: TRANSFORM SR BRANDS LLC
Assigned to SEARS BRANDS, L.L.C. reassignment SEARS BRANDS, L.L.C. RELEASE BY SECURED PARTY (SEE DOCUMENT FOR DETAILS). Assignors: JPP, LLC
Assigned to CITIBANK, N.A. reassignment CITIBANK, N.A. SECURITY INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: TRANSFORM SR BRANDS LLC
Assigned to BANK OF AMERICA, N.A. reassignment BANK OF AMERICA, N.A. SECURITY INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: TRANSFORM SR BRANDS LLC
Assigned to TRANSFORM SR BRANDS LLC reassignment TRANSFORM SR BRANDS LLC ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: SEARS BRANDS, L.L.C.
Assigned to TRANSFORM SR BRANDS LLC reassignment TRANSFORM SR BRANDS LLC RELEASE BY SECURED PARTY (SEE DOCUMENT FOR DETAILS). Assignors: CANTOR FITZGERALD SECURITIES, AS AGENT
Assigned to CANTOR FITZGERALD SECURITIES reassignment CANTOR FITZGERALD SECURITIES SECURITY INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: TRANSFORM SR BRANDS LLC
Priority to US16/673,365 priority patent/US11127063B2/en
Assigned to TRANSFORM SR BRANDS LLC reassignment TRANSFORM SR BRANDS LLC ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: SEARS BRANDS, L.L.C.
Assigned to TRANSFORM SR BRANDS LLC reassignment TRANSFORM SR BRANDS LLC RELEASE BY SECURED PARTY (SEE DOCUMENT FOR DETAILS). Assignors: CANTOR FITZGERALD SECURITIES
Assigned to TRANSFORM SR BRANDS LLC reassignment TRANSFORM SR BRANDS LLC RELEASE BY SECURED PARTY (SEE DOCUMENT FOR DETAILS). Assignors: BANK OF AMERICA, N.A.
Assigned to TRANSFORM SR BRANDS LLC reassignment TRANSFORM SR BRANDS LLC RELEASE BY SECURED PARTY (SEE DOCUMENT FOR DETAILS). Assignors: CITIBANK, N.A., AS AGENT
Priority to US17/471,274 priority patent/US11610246B2/en
Priority to US18/113,551 priority patent/US11836778B2/en
Priority to US18/496,360 priority patent/US20240054545A1/en
Abandoned legal-status Critical Current

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G06Q30/0601—Electronic shopping [e-shopping]
    • G06Q30/0623—Item investigation
    • G06Q30/0625—Directed, with specific intent or strategy
    • G06Q30/0627—Directed, with specific intent or strategy using item specifications
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/24—Querying
    • G06F16/245—Query processing
    • G06F16/2457—Query processing with adaptation to user needs
    • G06F16/24578—Query processing with adaptation to user needs using ranking
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90—Details of database functions independent of the retrieved data types
    • G06F16/95—Retrieval from the web
    • G06F16/951—Indexing; Web crawling techniques
    • G06F17/3053—
    • G06F17/30864—
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce
    • G06Q30/06—Buying, selling or leasing transactions
    • G06Q30/0601—Electronic shopping [e-shopping]

Definitions

  • Various embodiments relate to electronic commerce (e-commerce), and more particularly, to providing information for products sold in an e-commerce environment.
  • e-commerce electronic commerce
  • Electronic commerce (e-commerce) websites are an increasingly popular venue for consumers to research and purchase products without physically visiting a conventional brick-and-mortar retail store.
  • An e-commerce website may provide a vast array of products and/or services which customers may purchase from the website.
  • the e-commerce website may maintain and present to its customers various types of information about each offered product and/or service such as, for example, technical specifications, pictures, video demonstrations, customer reviews, etc.
  • a vast amount of information for any given product or service may be generally found on the Internet.
  • various websites regularly feature in-depth product reviews, product commentaries, product comparisons, purchasing advice for product categories, product demonstrations, etc. that may aid a customer in making a purchasing decision.
  • many customers may not have the time, desire, and/or ability to find the most relevant information for products of interest.
  • an e-commerce website that is able to readily provide such information, may provide a service that may both drive sales as well as increase customer loyalty.
  • FIG. 1 shows an e-commerce environment comprising a computing device and an e-commerce system in accordance with an embodiment of the present invention.
  • FIG. 2 shows an embodiment of a computing device for use in the e-commerce environment of FIG. 1 .
  • FIG. 3 shows user profiles and a product catalog maintained by an e-commerce system of FIG. 1 .
  • FIG. 4 shows an embodiment of a product listing provided by the e-commerce system of FIG. 1 .
  • FIG. 5 shows a flowchart for an embodiment of an example process that may be used by the e-commerce system of FIG. 1 to associate content with a product.
  • FIG. 6 shows a flowchart for an embodiment of another example process that may be used by the e-commerce system of FIG. 1 to associate content with a product.
  • aspects of the present invention are related to associating relevant content to products offered by an e-commerce site. More specifically, certain embodiments of the present invention relate to apparatus, hardware and/or software systems, and associated methods that analyze content from a plurality of content providers and associate products of an e-commerce site with relevant content based on such analysis.
  • the e-commerce environment 10 may include a computing device 20 connected to an e-commerce system 30 via a computer network 40 .
  • the network 40 may include a number of private and/or public networks such as, for example, wireless and/or wired LAN networks, cellular networks, and the Internet that collectively provide a communication path and/or paths between the computing device 20 and the e-commerce system 30 .
  • the computing device 20 may include a desktop, a laptop, a tablet, a smart phone, and/or some other type of computing device which enables a user to communicate with the e-commerce system 30 via the network 40 .
  • the e-commerce system 30 may include one or more web servers, database servers, routers, load balancers, and/or other computing and/or networking devices that operate to provide an e-commerce experience for users that connect to the e-commerce system 30 via the computing device 20 and the network 40 .
  • the e-commerce system 30 may further include a content aggregator 33 and one or more electronic databases 37 configured to store data used by the content aggregator 33 such as product catalog 300 , product associations 320 , and customer profiles 330 .
  • the content aggregator 33 may include one or more firmware and/or software instructions, routines, modules, etc. that the e-commerce system 30 may execute in order to extract content from one or more content providers and associate the extracted content with appropriate products and/or services provided by the e-commerce system 30 . Further details regarding the content aggregator 33 are presented below with respect to FIGS. 5 and 6 .
  • FIG. 1 depicts a simplified embodiment of the e-commerce environment 10 which may be implemented in numerous different manners using a wide range of different computing devices, platforms, networks, etc. Moreover, while aspects of the e-commerce environment 10 may be implemented using a client/server architecture, aspects of the e-commerce may be implemented using a peer-to-peer architecture or another networking architecture.
  • the e-commerce system 30 may include one or more computing devices.
  • FIG. 2 depicts an embodiment of a computing device 50 suitable for the computing device 20 and/or the e-commerce system 30 .
  • the computing device 50 may include a processor 51 , a memory 53 , a mass storage device 55 , a network interface 57 , and various input/output (I/O) devices 59 .
  • the processor 51 may be configured to execute instructions, manipulate data and generally control operation of other components of the computing device 50 as a result of its execution.
  • the processor 51 may include a general purpose processor such as an x86 processor or an ARM processor which are available from various vendors. However, the processor 51 may also be implemented using an application specific processor and/or other logic circuitry.
  • the memory 53 may store instructions and/or data to be executed and/or otherwise accessed by the processor 51 .
  • the memory 53 may be completely and/or partially integrated with the processor 51 .
  • the mass storage device 55 may store software and/or firmware instructions which may be loaded in memory 53 and executed by processor 51 .
  • the mass storage device 55 may further store various types of data which the processor 51 may access, modify, and/otherwise manipulate in response to executing instructions from memory 53 .
  • the mass storage device 55 may comprise one or more redundant array of independent disks (RAID) devices, traditional hard disk drives (HDD), solid-state device (SSD) drives, flash memory devices, read only memory (ROM) devices, etc.
  • RAID redundant array of independent disks
  • HDD hard disk drives
  • SSD solid-state device
  • flash memory devices read only memory devices, etc.
  • the network interface 57 may enable the computing device 50 to communicate with other computing devices directly and/or via network 40 .
  • the network interface 57 may permit the processor 51 to obtain content from content providers via network 40 .
  • the networking interface 57 may include a wired networking interface such as an Ethernet (IEEE 802.3) interface, a wireless networking interface such as a WiFi (IEEE 802.11) interface, a radio or mobile interface such as a cellular interface (GSM, CDMA, LTE, etc), and/or some other type of networking interface capable of providing a communications link between the computing device 50 and network 40 and/or another computing device.
  • the I/O devices 59 may generally provide devices which enable a user to interact with the computing device 50 by either receiving information from the computing device 50 and/or providing information to the computing device 50 .
  • the I/O devices 59 may include display screens, keyboards, mice, touch screens, microphones, audio speakers, etc.
  • computing device 50 While the above provides general aspects of a computing device 50 , those skilled in the art readily appreciate that there may be significant variation in actual implementations of a computing device. For example, a smart phone implementation of a computing device may use vastly different components and may have a vastly different architecture than a database server implementation of a computing device. However, despite such differences, computing devices generally include processors that execute software and/or firmware instructions in order to implement various functionality. As such, aspects of the present application may find utility across a vast array of different computing devices and the intention is not to limit the scope of the present application to a specific computing device and/or computing platform beyond any such limits that may be found in the appended claims.
  • the e-commerce system 30 may enable customers, which may be guests or members of the e-commerce system 30 , to browse and/or otherwise locate products.
  • the e-commerce system 30 may further enable such customers to purchase products and/or services offered for sale.
  • the e-commerce system 30 may maintain an electronic database or catalog 300 which may be stored on an associated mass storage device 55 .
  • the catalog 300 may include listings 310 for each product and/or service available for purchase.
  • Each listing 310 may include various information or attributes regarding the respective product and/or service, such as a unique product identifier (e.g., stock-keeping unit “SKU”), a product description, product image(s), manufacture information, available quantity, price, product features, etc.
  • a unique product identifier e.g., stock-keeping unit “SKU”
  • a product description e.g., product image(s)
  • manufacture information e.g., available quantity, price, product features, etc.
  • the e-commerce system 30 may enable guests to purchase products and/or services without registering and/or otherwise signing-up for a membership, the e-commerce system 30 may provide additional and/or enhanced functionality to those users that become a member.
  • a customer profile 330 may include personal information 331 , purchase history data 335 , and other customer activity data 337 .
  • the personal information 331 may include such items as name, mailing address, email address, phone number, billing information, clothing sizes, birthdates of friends and family, etc.
  • the purchase history data 335 may include information regarding products previously purchased by the customer from the e-commerce system 30 .
  • the customer history data 335 may further include products previously purchased from affiliated online and brick-and-mortar vendors.
  • the other customer activity data 337 may include information regarding prior customer activities such as products for which the customer has previously searched, products for which the customer has previously viewed, products for which the customer has provide comments, products for which the customer has rated, products for which the customer has written reviews, etc. and/or purchased from the e-commerce system 30 .
  • the other customer activity data 337 may further include similar activities associated with affiliated online and brick-and-mortar vendors.
  • the e-commerce system 30 may cause a computing device 10 to display a product listing 310 as shown in FIG. 4 .
  • the e-commerce system 30 may provide such a product listing 310 in response to a member browsing products by type, price, kind, etc., viewing a list of products obtained from a product search, and/or other techniques supported by the e-commerce system 30 for locating products of interest.
  • the product listing 310 may include one or more representative images 350 of the product as well as a product description 360 .
  • the product listing 310 may further include one or more hyperlinks and/or other references 370 to additional information associated with the product and/or service.
  • the content aggregator 33 may analyze content provided by many different content providers such as websites, blogs, etc., identify which content is relevant to a particular product, and associate the relevant content to the product.
  • the content aggregator 33 may obtain or otherwise collect content from various content providers on the Internet.
  • the content aggregator 33 may subscribe to various RSS (Rich Site Summary) or (Really Simply Syndication) feeds in order to receive RSS documents from such RSS feeds.
  • a content provider such as a website may provide RSS feeds to publish RSS documents for frequently updated information of the website such as, for example, blog entries, news headlines, audio, and video.
  • the RSS documents received by the content aggregator 33 may include full text or summarized text of the updated content and may further include metadata for the updated content such as publishing date and author's name.
  • the content aggregator 33 may automatically receive RSS documents from publishers without requiring the content aggregator 33 to poll or otherwise periodically check the content of the corresponding content provider.
  • the content aggregator 33 may obtain further content by polling websites of interests for relevant content. To this end, the content aggregator 33 may maintain a list of websites to periodically check for new content. The content aggregator 33 may then crawl or traverse such websites for content in a manner similar to webcrawlers used by web search engines.
  • the content aggregator 33 may assign categories to content obtained at 510 .
  • the content aggregator 33 may assign a category or categories to each received RSS document based on its URL (Universal Resource Locator), title of the content, main text of the content, etc.
  • the content aggregator 33 may maintain a list of categories for the products of the product catalog 300 and categorize such RSS documents accordingly.
  • the content aggregator 33 at 520 may analyze the content to extract relevant phrases.
  • the content aggregator 33 may extract the main text of the obtained content using various classification algorithms, shallow text processing, metadata parsing, etc.
  • the content aggregator 33 may further use the Stanford Named Entity Recognizer (SNER), the OpenNLP library, and/or other natural language processing techniques to extract relevant phrases from the obtained content.
  • SNER Stanford Named Entity Recognizer
  • the content aggregator 33 may use SNER to label sequences of words in the content which are the names of things, such as person, organizations, company names, and/or locations.
  • the content aggregator 33 may further use the OpenNLP natural language processor to perform tokenization, sentence segmentation, part-of-speech tagging, named entity extraction, chunking, and parsing of the obtained content.
  • the content aggregator 33 at 520 via such tools may extract trademark product names from the content in order to better ascertain to which products of the product catalog 300 that the obtained content relates.
  • the content aggregator 33 at 520 may further look for entities not extracted by the SNER or OpenNLP tools. To this end, the content aggregator 33 may maintain a list of names, phrases, etc. to match against the obtained content in order to determine whether such content includes such names, phrases, etc.
  • the content aggregator 33 at 530 may remove blacklisted phrases from phrases obtained at 520 .
  • the content aggregator 33 may maintain a list of names, phrases, etc. and remove such names, phrases, etc. from the phrases extracted at 520 .
  • a technician or other employee may tweak and fine tune the results of the phrase extraction by removing phrases that routine provide false associations between content and products.
  • the content aggregator 33 may rank the remaining phrases based on a weighted term frequency. In particular, the content aggregator 33 may rank the remaining phrases not only upon the frequency of such phrases occur in the content but also on the position of such phrases in the content. For example, the content aggregator 33 may give terms used in the title of the content the greatest weight, terms used in the first paragraph the next greatest weight, etc. The content aggregator 33 may further affect the weight of a term based on how often the term appeared in other documents.
  • the content aggregator 33 at 550 may select phrases with a score greater than a threshold level. To this end, the content aggregator 33 may sort the phrases based on their weighted term frequency scores. The content aggregator 33 may then select all such phrases greater than a specified minimum threshold score or may select the top specified percentage (e.g. the top 20%) of phrases in the sorted list.
  • the content aggregator 33 After 550 , the content aggregator 33 now has a list of phrases which are likely the most relevant phrases for the content.
  • the content aggregator 33 searches through the product catalog 300 to identify products which match the selected phrases. Using the metadata of the article and products (ex. Category), the content aggregator 33 may remove irrelevant products.
  • the content aggregator 33 at 570 may update the product associations 320 of the product catalog 300 to include a reference (e.g., a hyperlink with descriptive link text) to the content. In this manner the content aggregator 33 may automatically collect lists of references 320 to relevant content for its products in the product catalog 300 .
  • the content aggregator 33 may obtain or otherwise collect content from various content providers on the Internet.
  • the content aggregator 33 may obtain such content via RSS feeds, polling, and/or crawling in a manner similar to that described above in regard to step 510 of process 500 .
  • the content aggregator 33 may extract the main text of the obtained content using various classification algorithms, shallow text processing, metadata parsing, etc.
  • the content aggregator 33 then at 630 may analyze the content to extract the context of the content.
  • the content aggregator 33 may extract the context of the content using a natural language processing technique such as, for example, Latent Dirichlet Allocation (LDA) using a set of topics or categories such as, for example, Wikipedia tags.
  • LDA Latent Dirichlet Allocation
  • the content aggregator may express the context of each obtained document as a sparse probability distribution over the set of topics.
  • the content aggregator 33 may extract the context of each product in the product catalog 300 .
  • the content aggregator 33 may extract such context in a manner similar to that used at 630 to extract the context of the content.
  • the content aggregator 33 may use LDA natural language and Wikipedia tags to obtain for each product a sparse probability distribution of its product listing 310 over the Wikipedia tags.
  • the content aggregator 33 at 650 may generate distance measures between the probability distributions of the content and each product of the catalog 300 .
  • the content aggregator 33 may use various distance measures such as Euclidean distance, Chebschev distance, Jaccard's distance, etc. to obtain such distance measures.
  • the content aggregator 33 at 660 may determine to which products that the content is most related. In particular, the content aggregator 33 may select the product with the smallest distance, the products with the smallest distances, and/or the products with a distance smaller than a threshold distance. The content aggregator 33 may also sort the products based on their distance measures, and select a predefined percentage of the products having the smallest distance measures.
  • the content aggregator 33 then at 670 may update the product associations 320 for the selected products to include a reference (e.g., a hyperlink with descriptive link text) to the content. In this manner the content aggregator 33 may automatically collect lists of references 320 to relevant content for its products in the product catalog 300 .
  • a reference e.g., a hyperlink with descriptive link text
  • certain embodiments may be implemented as a plurality of instructions on a non-transitory, computer readable storage medium such as, for example, flash memory devices, hard disk devices, compact disc media, DVD media, EEPROMs, etc.
  • Such instructions when executed by one or more computing devices, may result in the one or more computing devices identifying relevant content for a particular product or service and associating the relevant content with the product or service.

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US14/104,070 2013-12-12 2013-12-12 Product and content association Abandoned US20150170248A1 (en)

Priority Applications (8)

Application Number Priority Date Filing Date Title
US14/104,070 US20150170248A1 (en) 2013-12-12 2013-12-12 Product and content association
MX2014015348A MX2014015348A (es) 2013-12-12 2014-12-11 Asociacion de producto y contenido.
EP14197661.3A EP2884451A1 (en) 2013-12-12 2014-12-12 Product and content association
CA2874614A CA2874614A1 (en) 2013-12-12 2014-12-12 Product and content association
US16/673,365 US11127063B2 (en) 2013-12-12 2019-11-04 Product and content association
US17/471,274 US11610246B2 (en) 2013-12-12 2021-09-10 Product and content association
US18/113,551 US11836778B2 (en) 2013-12-12 2023-02-23 Product and content association
US18/496,360 US20240054545A1 (en) 2013-12-12 2023-10-27 Product and content association

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US14/104,070 US20150170248A1 (en) 2013-12-12 2013-12-12 Product and content association

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US16/673,365 Continuation US11127063B2 (en) 2013-12-12 2019-11-04 Product and content association

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US20150170248A1 true US20150170248A1 (en) 2015-06-18

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US14/104,070 Abandoned US20150170248A1 (en) 2013-12-12 2013-12-12 Product and content association
US16/673,365 Active 2034-03-06 US11127063B2 (en) 2013-12-12 2019-11-04 Product and content association
US17/471,274 Active US11610246B2 (en) 2013-12-12 2021-09-10 Product and content association
US18/113,551 Active US11836778B2 (en) 2013-12-12 2023-02-23 Product and content association
US18/496,360 Pending US20240054545A1 (en) 2013-12-12 2023-10-27 Product and content association

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US16/673,365 Active 2034-03-06 US11127063B2 (en) 2013-12-12 2019-11-04 Product and content association
US17/471,274 Active US11610246B2 (en) 2013-12-12 2021-09-10 Product and content association
US18/113,551 Active US11836778B2 (en) 2013-12-12 2023-02-23 Product and content association
US18/496,360 Pending US20240054545A1 (en) 2013-12-12 2023-10-27 Product and content association

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EP (1) EP2884451A1 (es)
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US20240054545A1 (en) 2024-02-15
US11610246B2 (en) 2023-03-21
CA2874614A1 (en) 2015-06-12
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US11836778B2 (en) 2023-12-05
US20200134689A1 (en) 2020-04-30

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