US20150066684A1 - Real-time recommendation browser plug-in - Google Patents

Real-time recommendation browser plug-in Download PDF

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US20150066684A1
US20150066684A1 US14/139,274 US201314139274A US2015066684A1 US 20150066684 A1 US20150066684 A1 US 20150066684A1 US 201314139274 A US201314139274 A US 201314139274A US 2015066684 A1 US2015066684 A1 US 2015066684A1
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item
information pertaining
user
content page
additional item
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US14/139,274
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Prasanth K. V
Jeetendra Agrawal
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eBay Inc
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eBay Inc
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Priority to US14/139,274 priority patent/US20150066684A1/en
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    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00Commerce, e.g. shopping or e-commerce
    • G06Q30/06Buying, selling or leasing transactions
    • G06Q30/0601Electronic shopping
    • G06Q30/0631Item recommendations
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/20Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
    • G06F16/28Databases characterised by their database models, e.g. relational or object models
    • G06F16/282Hierarchical databases, e.g. IMS, LDAP data stores or Lotus Notes
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/90Details of database functions independent of the retrieved data types
    • G06F16/95Retrieval from the web
    • G06F16/951Indexing; Web crawling techniques

Abstract

Systems, methods, and computer-readable media for performing operations comprising: extracting product information from a webpage; getting recommendations from an online marketplace server; and displaying the recommendation from the online marketplace server in a plug-in on the webpage.

Description

    CROSS-REFERENCE TO RELATED APPLICATIONS
  • This application claims the benefit of U.S. Provisional Application No. 61/872,015, filed Aug. 30, 2013, entitled “REAL-TIME RECOMMENDATION BROWSER PLUG-IN,” which is incorporated herein by reference in its entirety.
  • TECHNICAL FIELD
  • The present application relates generally to the technical field of internet commerce, and, in one specific example, to a system and method of providing real-time recommendations of listings of items (e.g., products or services) on a second marketplace system based on a determination that the user is browsing the same or similar items on a first marketplace system.
  • BACKGROUND
  • While shopping for items on the Internet, a user may access information pertaining to the items on a web page of a first web system without being aware that the same or similar items are available for purchasing on a second web system.
  • BRIEF DESCRIPTION OF THE DRAWINGS
  • Some embodiments are illustrated by way of example and not limitation in the figures of the accompanying drawings.
  • FIG. 1 is a network diagram depicting a client-server system within which one example embodiment may be deployed.
  • FIG. 2A is a screenshot of an example user interface that includes a user interface 202 in the top right corner for presenting real-time recommendations pertaining to an item that a user may be interested in.
  • FIG. 2B is a screenshot of an additional example user interface that includes a user interface in the top right corner for presenting real-time recommendations pertaining to an item that a user may be interested in.
  • FIG. 3 is a screenshot of example structured data corresponding to a content page that is analyzed by the real-time recommendation plug-in of FIG. 2A;
  • FIG. 4 is an example embodiment of a method of getting a recommendation from an online marketplace in real-time.
  • FIG. 5 is an example embodiment of a sequence diagram for displaying recommended items in a user interface of a software application executing on a device of the user (e.g., a web browser).
  • FIG. 6 is a block diagram of machine in the example form of a computer system within which instructions, for causing the machine to perform any one or more of the methodologies discussed herein, may be executed.
  • DETAILED DESCRIPTION
  • Example methods and systems to provide real-time recommendations in a web browser application 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 invention may be practiced without these specific details.
  • The described systems and methods leverage the structured data associated with production description, view item, and review pages on shopping websites, and showing real time recommendations from a preferred online marketplace.
  • FIG. 1 is a network diagram depicting a client-server system 100, within which one example embodiment may be deployed. A networked system 102, in the example forms of a network-based marketplace or publication system, provides server-side functionality, via a network 104 (e.g., the Internet or Wide Area Network (WAN)) to one or more clients. FIG. 1 illustrates, for example, a web client 106 (e.g., a browser), and a programmatic client 108 executing on respective client machines 110 and 112.
  • An Application Program Interface (API) server 114 and a web server 116 are coupled to, and provide programmatic and web interfaces respectively to, one or more application servers 118. The application servers 118 host one or more marketplace applications 120 and payment applications 122. The application servers 118 are, in turn, shown to be coupled to one or more databases servers 124 that facilitate access to one or more databases 126.
  • The marketplace applications 120 may provide a number of marketplace functions and services to users that access the networked system 102. The payment applications 122 may likewise provide a number of payment services and functions to users. The payment applications 122 may allow users to accumulate value (e.g., in a commercial currency, such as the U.S. dollar, or a proprietary currency, such as “points”) in accounts, and then later to redeem the accumulated value for products (e.g., goods or services) that are made available via the marketplace applications 120. While the marketplace and payment applications 120 and 122 are shown in FIG. 1 to both form part of the networked system 102, it will be appreciated that, in alternative embodiments, the payment applications 122 may form part of a payment service that is separate and distinct from the networked system 102.
  • Further, while the system 100 shown in FIG. 1 employs a client-server architecture, the present invention is of course not limited to such an architecture, and could equally well find application in a distributed, or peer-to-peer, architecture system, for example. The various marketplace and payment applications 120 and 122 could also be implemented as standalone software programs, which do not necessarily have networking capabilities.
  • The web client 106 accesses the various marketplace and payment applications 120 and 122 via the web interface supported by the web server 116. Similarly, the programmatic client 108 accesses the various services and functions provided by the marketplace and payment applications 120 and 122 via the programmatic interface provided by the API server 114. The programmatic client 108 may, for example, be a seller application (e.g., the TurboLister application developed by eBay Inc., of San Jose, Calif.) to enable sellers to author and manage listings on the networked system 102 in an off-line manner, and to perform batch-mode communications between the programmatic client 108 and the networked system 102.
  • FIG. 1 also illustrates a third party application 128, executing on a third party server machine 130, as having programmatic access to the networked system 102 via the programmatic interface provided by the API server 114. For example, the third party application 128 may, utilizing information retrieved from the networked system 102, support one or more features or functions on a website hosted by the third party. The third party website may, for example, provide one or more promotional, marketplace or payment functions that are supported by the relevant applications of the networked system 102.
  • FIG. 2A is a screenshot of an example user interface 200 that includes a user interface 202 in the top right corner for presenting real-time recommendations pertaining to an item that a user may be interested in. The real-time plug-in may gather information pertaining to listings of an item that the user may be interested based on information extracted from structured data, rich data, metadata, or other data associated with a web page that the user is currently browsing. For example, based on a determination that the user is browsing a web page pertaining to a camera on a first ecommerce web site, such as a web site of a vendor of the camera, the plugin may present the user with information pertaining to one or more listings of the same camera (or a similar camera) on a second ecommerce web site (e.g., eBay). Thus, before the user purchases the camera from the vendor, the user may be presented with information pertaining to alternative purchasing options.
  • For example, as will be described in more detail below, the plugin may extract information pertaining to the item that the user may interested in from structured data on a content page that the user is browsing. Such information may include the title, model number, manufacturer, vendor, price, and so on. Then, based on a recommendation received from a web site that is separate from the web site presenting the content page that the user is currently browsing, the plug in may present information pertaining to listings of the item (or a similar item) on the separate web site. For example, the plugin may present a drop down window or toolbar, such as the user interface 202 of FIG. 2A, that includes information pertaining to one or more listings on a separate web site of items that are the same as or similar to the items that the user is currently browsing. The information presented in the user interface may include any information that the separate web site maintains with respect to the listings of the items, such as photos of the items, descriptions of the items, specifications of the items, how many of listings of the item may be found on the separate web site, the listing prices of the items, current auction prices of the items, buy-it-now prices of the items, time remaining in auctions of the items, numbers of watchers of the listings of the items, information pertaining to the sellers of the item (ratings, usernames etc.), terms or guarantees pertaining to the listings, and so on.
  • In various embodiments, one or more listings may be presented as thumbnails or condensed information in a scrollable region of a user interface presented by the plugin. Thus, the user may view information pertaining to the various listings on the external web site without leaving the user's current web browsing context.
  • FIG. 2B is a screenshot of an example user interface 250 that includes a user interface 252 in the top right corner for presenting real-time recommendations pertaining to an item that a user may be interested in. Here, the user is browsing a web page of a first web site that features a smart phone. As a result of a determination that the same type of smart phone or a similar smart phone is listed on a second web site (e.g., based a comparison of model number or other information pertaining to the item on the content page being browsed by the user on the first web site and information pertaining to the listings of additional items on the second web site), the plugin presents information to the user pertaining to the listings on the second web site. In various embodiments, the presenting of the information pertaining to the listings includes how much money the user may save by purchasing the product on the external web site instead of the current web site (e.g., expressed as a percentage savings, such as 29% less, 18% less, and so on).
  • FIG. 3 is a screenshot of example structured data corresponding to a content page being browsed by a user that is analyzed by the real-time recommendation plug-in of FIG. 2A. Various e-commerce sites, vendor sites, blogs, and review sites may use a structured data protocol, such as microformats, open graph protocol, or Twitter Card. Microformats may be used to yield better Google search results placement and more prominent result descriptions. In microformats, structured data such as title, image, price, etc. are structured through predefined HTML attributes. Open graph protocol is used by pages using Facebook social plugins such as “like” and “comments”. The structured data may be embedded in meta tags.
  • So, when a user is using an Internet browser (e.g., Google Chrome, Internet Explorer, and so on) to browse content (e.g., a web page) pertaining to an item listed on a network-based publication system, e-commerce, or marketplace web site or system (e.g., eBay, Amazon.com, craigslist, and so on), an extension (e.g., a plug-in) of the Internet browser application may extract information from the structured data associated with the content, such as a title of an item that a user is browsing or otherwise has demonstrated an interest in (e.g., based on a monitoring of the user's behaviour with respect to the content). For example, the extension may extract the information from structured data that is associated with the content using the microformats or open graph protocol. Furthermore, the extension may use the extracted information when calling an API (e.g., a finding API or a shopping API) of an additional network-based publication system or online marketplace to find listings of the same item on the additional system. In some embodiments, a dedicated Search/Recommendation API may be provided by the additional system for access by the extension. The extension may then neatly display search results (e.g., in a pop-down window) in conjunction with the same page that the user is browsing and from which the information was extracted by the extension (see, e.g., FIGS. 2A and 2B). From the pop-down, if the user is interested in the results returned by the extension, he/she can navigate to a listing corresponding to the item (e.g., by clicking on a product image or a search result page link). In this way, the user may be provided with great visibility to product pricing or other information as provided by the additional online marketplace.
  • In one example embodiment, the extension may be implemented as Chrome Extensions built with core technologies like jQuery, HTML, and CSS. The algorithms used to implement the Chrome Extensions may be used to build plugins for other browsers like Internet Explorer. Safari, FireFox, Opera, etc. In various embodiments, the plugin may call server-side commands to extract data from the content page that the user is currently browsing or visiting. For example. Custom Scripts may be used to extract a title of an item that is associated with web pages or sites that the user frequently visits or that are otherwise popular with the user. If a Custom Recommendation service of the additional marketplace system is used by the plug-in, the data posted to the recommendation service may be used by the additional marketplace system to give personalized recommendation when the user accesses (e.g., browses a web page of) the additional online marketplace.
  • FIG. 4 is an example embodiment of a method 400 of getting a recommendation from an online marketplace in real-time. In various embodiments, operations of the method 400 may be performed by one or more of the marketplace application(s) 120.
  • At operation 402, product information is extracted by the plug-in. In various embodiments, the plug-in uses standard structured data (e.g., microformats data) associated with many e-commerce websites. Or the plug-in uses site-specific data (e.g., structured data defined in web sites of vendors of items that a user is browsing, such as Nokia, Canon, or other vendor web sites.
  • At operation 404, the plugin gets a recommendation from an online-marketplace that is separate from the online marketplace or vendor web site that the user is currently browsing. For example, if the user is currently browsing a camera or a mobile phone on a vendor web site, the plug-in may get a recommendation from an additional web site (e.g., eBay.com) pertaining to a listing of the same item on the additional web site. In various embodiments, the plugin may call an API of a service provided by the additional web site, such as a Finding Service or a Shopping Service, providing the information extracted in step 404 as a parameter of the API. In various embodiments, the calling of the Finding Service may take a form such as {OPERATION-NAME: findItemsByKeywords}. In various embodiments, the calling of the Shopping Service may take a form such as {CALL-NAME: Finditems}. The API may then return results corresponding to the API call.
  • At operation 406, the plugin may present the results to the user on a device of the user. For example, the plugin may present the results in a pop-up window as depicted in FIGS. 2A and 2B, allowing the user to view the results without leaving the web page that the user is currently browsing.
  • In various embodiments, the plugin may determine to get product recommendations from the additional marketplace based on an identification of a market segment in which an item that the user is interested belongs. For example, the plugin may be used, for example, to get recommendations for products in segments including books, memory cards, laptops, mobile phones, digital cameras, and accessories for laptops, mobile phones, and digital cameras.
  • In various embodiments, user history or profile data (e.g., as communicated to the additional marketplace system by the plugin) may be retrieved, used to personalize recommendations, and show more relevant personalized recommendations or deals to the user when the user accesses the additional marketplace system (e.g., by browsing to the home page of the additional online marketplace system).
  • FIG. 5 is an example embodiment of a sequence diagram for displaying recommended items in a user interface of a software application executing on a device of the user (e.g., a web browser). In various embodiments, the plugin detects an accessing of a web page of a first web site that is associated with an item that is listed (e.g., as being for sale) on a second web site (e.g., eBay). For example, the plugin may generate a document including information extracted from the web page, such as information extracted from structured data (e.g., microformats or rich snippets) that specifies a title or other information pertaining to an item that the user may be interested in, or information extracted from social tags (e.g., open graph or Twitter card) associated with the web page. The plugin may then send the document to an application executing on the server of the second web site (e.g., eBay) for crawling. The crawling application may crawl the document and then identify a match for the item (e.g., a listing of the item on the second web site that matches the information extracted from the web page of the first web site). For example, the crawling application may call a Find Item Service, providing some or all of the information extracted from the document received from the plugin. The Find Item Service may then return one or more relevant matches (e.g., one or more links to listings of the item on the second web site, information pertaining to the listings of the items on the second web site, such as price, quantity, or other information maintained by the second web site with respect to the listing).
  • The crawling application may then generate or build a user interface for presenting some or all of the information returned by the Find Item Service with respect to the item. The crawling application may then communicate the user interface to the plugin for displaying to the user in conjunction with the web page that the user is currently viewing and from which the information about the item was extracted.
  • Although client-side functionality is described above as being included in a plug-in of a web browser application, one skilled in the art would understand that the client-side functionality described above may also be implemented as a stand-alone application executing on a client device of a user or as a plug-in or extension of other types of applications in addition to web-browser applications. Additionally, although some functionality is described above as being client-side functionality and other functionality is described above as being server-side functionality, one skilled in the art would understand that this functionality may be distributed in various additional ways between client systems and server systems.
  • Modules, Components and Logic
  • Certain embodiments are described herein as including logic or a number of components, modules, or mechanisms. Modules may constitute either software modules (e.g., code embodied (1) on a non-transitory machine-readable medium or (2) in a transmission signal) or hardware-implemented modules. A hardware-implemented module is tangible unit capable of performing certain operations and may be configured or arranged in a certain manner. In example embodiments, one or more computer systems (e.g., a standalone, client or server computer system) or one or more processors may be configured by software (e.g., an application or application portion) as a hardware-implemented module that operates to perform certain operations as described herein.
  • In various embodiments, a hardware-implemented module may be implemented mechanically or electronically. For example, a hardware-implemented module may comprise dedicated circuitry or logic that is permanently configured (e.g., as a special-purpose processor, such as a field programmable gate array (FPGA) or an application-specific integrated circuit (ASIC)) to perform certain operations. A hardware-implemented module may also comprise programmable logic or circuitry (e.g., as encompassed within a general-purpose processor or other programmable processor) that is temporarily configured by software to perform certain operations. It will be appreciated that the decision to implement a hardware-implemented module mechanically, in dedicated and permanently configured circuitry, or in temporarily configured circuitry (e.g., configured by software) may be driven by cost and time considerations.
  • Accordingly, the term “hardware-implemented module” should be understood to encompass a tangible entity, be that an entity that is physically constructed, permanently configured (e.g., hardwired) or temporarily or transitorily configured (e.g., programmed) to operate in a certain manner and/or to perform certain operations described herein. Considering embodiments in which hardware-implemented modules are temporarily configured (e.g., programmed), each of the hardware-implemented modules need not be configured or instantiated at any one instance in time. For example, where the hardware-implemented modules comprise a general-purpose processor configured using software, the general-purpose processor may be configured as respective different hardware-implemented modules at different times. Software may accordingly configure a processor, for example, to constitute a particular hardware-implemented module at one instance of time and to constitute a different hardware-implemented module at a different instance of time.
  • Hardware-implemented modules can provide information to, and receive information from, other hardware-implemented modules. Accordingly, the described hardware-implemented modules may be regarded as being communicatively coupled. Where multiple of such hardware-implemented modules exist contemporaneously, communications may be achieved through signal transmission (e.g., over appropriate circuits and buses) that connect the hardware-implemented modules. In embodiments in which multiple hardware-implemented modules are configured or instantiated at different times, communications between such hardware-implemented modules may be achieved, for example, through the storage and retrieval of information in memory structures to which the multiple hardware-implemented modules have access. For example, one hardware-implemented module may perform an operation, and store the output of that operation in a memory device to which it is communicatively coupled. A further hardware-implemented module may then, at a later time, access the memory device to retrieve and process the stored output. Hardware-implemented modules may also initiate communications with input or output devices, and can operate on a resource (e.g., a collection of information).
  • The various operations of example methods described herein may be performed, at least partially, by one or more processors that are temporarily configured (e.g., by software) or permanently configured to perform the relevant operations. Whether temporarily or permanently configured, such processors may constitute processor-implemented modules that operate to perform one or more operations or functions. The modules referred to herein may, in some example embodiments, comprise processor-implemented modules.
  • Similarly, the methods described herein may be at least partially processor-implemented. For example, at least some of the operations of a method may be performed by one or processors or processor-implemented modules. The performance of certain of the operations may be distributed among the one or more processors, not only residing within a single machine, but deployed across a number of machines. In some example embodiments, the processor or processors may be located in a single location (e.g., within a home environment, an office environment or as a server farm), while in other embodiments the processors may be distributed across a number of locations.
  • The one or more processors may also operate to support performance of the relevant operations in a “cloud computing” environment or as a “software as a service” (SaaS). For example, at least some of the operations may be performed by a group of computers (as examples of machines including processors), these operations being accessible via a network (e.g., the Internet) and via one or more appropriate interfaces (e.g., Application Program Interfaces (APIs)).
  • Electronic Apparatus and System
  • Example embodiments may be implemented in digital electronic circuitry, or in computer hardware, firmware, software, or in combinations of them. Example embodiments may be implemented using a computer program product, e.g., a computer program tangibly embodied in an information carrier, e.g., in a machine-readable medium for execution by, or to control the operation of, data processing apparatus, e.g., a programmable processor, a computer, or multiple computers.
  • A computer program can be written in any form of programming language, including compiled or interpreted languages, and it can be deployed in any form, including as a stand-alone program or as a module, subroutine, or other unit suitable for use in a computing environment. A computer program can be deployed to be executed on one computer or on multiple computers at one site or distributed across multiple sites and interconnected by a communication network.
  • In example embodiments, operations may be performed by one or more programmable processors executing a computer program to perform functions by operating on input data and generating output. Method operations can also be performed by, and apparatus of example embodiments may be implemented as, special purpose logic circuitry, e.g., a field programmable gate array (FPGA) or an application-specific integrated circuit (ASIC).
  • The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. In embodiments deploying a programmable computing system, it will be appreciated that that both hardware and software architectures require consideration. Specifically, it will be appreciated that the choice of whether to implement certain functionality in permanently configured hardware (e.g., an ASIC), in temporarily configured hardware (e.g., a combination of software and a programmable processor), or a combination of permanently and temporarily configured hardware may be a design choice. Below are set out hardware (e.g., machine) and software architectures that may be deployed, in various example embodiments.
  • Example Machine Architecture and Machine-Readable Medium
  • FIG. 6 is a block diagram of machine in the example form of a computer system 600 within which instructions, for causing the machine to perform any one or more of the methodologies discussed herein, may be executed. In alternative embodiments, the machine operates as a standalone device or may be connected (e.g., networked) to other machines. In a networked deployment, the machine may operate in the capacity of a server or a client machine in server-client network environment, or as a peer machine in a peer-to-peer (or distributed) network environment. The machine may be a personal computer (PC), a tablet PC, a set-top box (STB), a Personal Digital Assistant (PDA), a cellular telephone, a web appliance, a network router, switch or bridge, or any machine capable of executing instructions (sequential or otherwise) that specify actions to be taken by that machine. Further, while only a single machine is illustrated, the term “machine” shall also be taken to include any collection of machines that individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methodologies discussed herein.
  • The example computer system 600 includes a processor 602 (e.g., a central processing unit (CPU), a graphics processing unit (GPU) or both), a main memory 604 and a static memory 606, which communicate with each other via a bus 608. The computer system 600 may further include a video display unit 610 (e.g., a liquid crystal display (LCD) or a cathode ray tube (CRT)). The computer system 600 also includes an alphanumeric input device 612 (e.g., a keyboard or a touch-sensitive display screen), a user interface (UI) navigation device 614 (e.g., a mouse), a disk drive unit 616, a signal generation device 618 (e.g., a speaker) and a network interface device 620.
  • Machine-Readable Medium
  • The disk drive unit 616 includes a machine-readable medium 622 on which is stored one or more sets of instructions and data structures (e.g., software) 624 embodying or utilized by any one or more of the methodologies or functions described herein. The instructions 624 may also reside, completely or at least partially, within the main memory 604 and/or within the processor 602 during execution thereof by the computer system 600, the main memory 604 and the processor 602 also constituting machine-readable media.
  • While the machine-readable medium 622 is shown in an example embodiment to be a single medium, the term “machine-readable medium” may include a single medium or multiple media (e.g., a centralized or distributed database, and/or associated caches and servers) that store the one or more instructions or data structures. The term “machine-readable medium” shall also be taken to include any tangible medium that is capable of storing, encoding or carrying instructions for execution by the machine and that cause the machine to perform any one or more of the methodologies of the present invention, or that is capable of storing, encoding or carrying data structures utilized by or associated with such instructions. The term “machine-readable medium” shall accordingly be taken to include, but not be limited to, solid-state memories, and optical and magnetic media. Specific examples of machine-readable media include non-volatile memory, including by way of example semiconductor memory devices, e.g., Erasable Programmable Read-Only Memory (EPROM), Electrically Erasable Programmable Read-Only Memory (EEPROM), and flash memory devices; magnetic disks such as internal hard disks and removable disks; magneto-optical disks; and CD-ROM and DVD-ROM disks.
  • Transmission Medium
  • The instructions 624 may further be transmitted or received over a communications network 626 using a transmission medium. The instructions 624 may be transmitted using the network interface device 620 and any one of a number of well-known transfer protocols (e.g., HTTP). Examples of communication networks include a local area network (“LAN”), a wide area network (“WAN”), the Internet, mobile telephone networks, Plain Old Telephone (POTS) networks, and wireless data networks (e.g., WiFi and WiMax networks). The term “transmission medium” shall be taken to include any intangible medium that is capable of storing, encoding or carrying instructions for execution by the machine, and includes digital or analog communications signals or other intangible media to facilitate communication of such software.
  • Although an embodiment has been described with reference to specific example 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. The accompanying drawings that form a part hereof, show by way of illustration, and not of limitation, specific embodiments in which the subject matter may be practiced. The embodiments illustrated are described in sufficient detail to enable those skilled in the art to practice the teachings disclosed herein. Other embodiments may be utilized and derived therefrom, such that structural and logical substitutions and changes may be made without departing from the scope of this disclosure. This Detailed Description, therefore, is not to be taken in a limiting sense, and the scope of various embodiments is defined only by the appended claims, along with the full range of equivalents to which such claims are entitled.
  • Such embodiments of the inventive subject matter may be referred to herein, individually and/or collectively, by the term “invention” merely for convenience and without intending to voluntarily limit the scope of this application to any single invention or inventive concept if more than one is in fact disclosed. Thus, although specific embodiments have been illustrated and described herein, it should be appreciated that any arrangement calculated to achieve the same purpose may be substituted for the specific embodiments shown. This disclosure is intended to cover any and all adaptations or variations of various embodiments. Combinations of the above embodiments, and other embodiments not specifically described herein, will be apparent to those of skill in the art upon reviewing the above description.

Claims (20)

What is claimed is:
1. A method comprising:
determining that a user is browsing a content page served by a first marketplace system;
determining that the content page includes information pertaining to an item;
determining that the information pertaining to the item relates to information pertaining to an additional item, the additional item being included in a listing associated with a second marketplace system; and
generating a user interface for presentation to the user, the user interface configured to present the information pertaining to the additional item while the user is browsing the content page served by the first marketplace system, wherein the generating of the user interface is performed by a computer processor.
2. The method of claim 1, wherein the determining that the content page includes information pertaining to the item is based on a web crawler a document pertaining to the content page, the document being provided to the web crawler by a plugin application, the plug-in application executing within a web-browser application, the web-browser application executing on a client device of the user, the web crawler executing on a server of the second marketplace system.
3. The method of claim 2, wherein the determining that the information pertaining to the item relates to information pertaining to an additional item is based on a crawling by the web crawler of a plurality of listings on the second marketplace system, the plurality of listings including the listing in which the additional item is included.
4. The method of claim 1, wherein the identifying that the content page includes information pertaining to the item includes extracting the information from structured data associated with the content page.
5. The method of claim 2, wherein the structured data includes social tags as a fallback based on the structured data not including another open data format.
6. The method of claim 1, wherein the determining that the information pertaining to the item relates to the information pertaining to the additional item is based on a similarity between the information pertaining to the item and the information pertaining to the additional item.
7. The method of claim 1, wherein the information pertaining to the item includes at least one of a title of the item, a product description of the item, and a model number of the item and the information pertaining to the additional item includes at least one of the title of the additional item, a product description of the additional item, and a model number of the additional item.
8. A system comprising:
one or more computer processors configured to:
determine that a user is browsing a content page served by a first marketplace system;
determine that the content page includes information pertaining to an item;
determine that the information pertaining to the item relates to information pertaining to an additional item, the additional item being included in a listing on a second marketplace system; and
generating a user interface for presentation to the user, the user interface configured to present the information pertaining to the additional item while the user is browsing the content page served by the first marketplace system.
9. The system of claim 8, wherein the determining that the content page includes information pertaining to the item is based on a web crawler a document pertaining to the content page, the document being provided to the web crawler by a plugin application, the plug-in application executing within a web-browser application, the web-browser application executing on a client device of the user, the web crawler executing on a server of the second marketplace system.
10. The system of claim 9, wherein the determining that the information pertaining to the item relates to information pertaining to an additional item is based on a crawling by the web crawler of a plurality of listings on the second marketplace system, the plurality of listings including the listing in which the additional item is included.
11. The system of claim 8, wherein the identifying that the content page includes information pertaining to the item includes extracting the information from structured data associated with the content page.
12. The system of claim 9, wherein the structured data includes social tags as a fallback based on the structured data not including another open data format.
13. The system of claim 8, wherein the determining that the information pertaining to the item relates to the information pertaining to the additional item is based on a similarity between the information pertaining to the item and the information pertaining to the additional item.
14. The system of claim 8, wherein the information pertaining to the item includes at least one of a title of the item, a product description of the item, and a model number of the item and the information pertaining to the additional item includes at least one of the title of the additional item, a product description of the additional item, and a model number of the additional item.
15. A non-transitory machine readable storage medium storing a set of instructions that, when executed by at least one processor, causes the at least one processor to perform operations comprising:
determining that a user is browsing a content page served by a first marketplace system;
determining that the content page includes information pertaining to an item;
determining that the information pertaining to the item relates to information pertaining to an additional item, the additional item being included in a listing associated with a second marketplace system; and
generating a user interface for presentation to the user, the user interface configured to present the information pertaining to the additional item while the user is browsing the content page served by the first marketplace system, wherein the generating of the user interface is performed by a computer processor.
16. The non-transitory machine readable storage medium of claim 15, wherein the determining that the content page includes information pertaining to the item is based on a web crawler a document pertaining to the content page, the document being provided to the web crawler by a plugin application, the plug-in application executing within a web-browser application, the web-browser application executing on a client device of the user, the web crawler executing on a server of the second marketplace system.
17. The non-transitory machine readable storage medium of claim 16, wherein the determining that the information pertaining to the item relates to information pertaining to an additional item is based on a crawling by the web crawler of a plurality of listings on the second marketplace system, the plurality of listings including the listing in which the additional item is included.
18. The non-transitory machine readable storage medium of claim 15, wherein the identifying that the content page includes information pertaining to the item includes extracting the information from structured data associated with the content page.
19. The non-transitory machine readable storage medium of claim 16, wherein the structured data includes social tags as a fallback based on the structured data not including another open data format.
20. The non-transitory machine readable storage medium of claim 15, wherein the determining that the information pertaining to the item relates to the information pertaining to the additional item is based on a similarity between the information pertaining to the item and the information pertaining to the additional item.
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