Ebay, Incorporated

Brian Scott Johnson

Neelakantan Sundaresan

Alvaro Bolivar

Jean-David Ruvini

Randall Scott Shoup

Nishith Parikh

Gyanit Singh

Badrul M Sarwar

Brian M Johnson

Rajyashree Mukherjee

Venkat Sundaranatha

Shashi Seth

Musaab At-Taras

Vamsi Salaka

Udayan Khurana

Jason M Heidema

Benny Soetarman

Robin Kennedy

Niraj Kothari

Daniel Kramer

Mohammad Al Hasan

Michael Ching

Julie Lavee Netzloff

Ravi Chandra Jammalamadaka

Tracy Holloway King

A system and method of identifying suspicious item-related features are disclosed. In some embodiments, a new item listing is received. The item listing may correspond to a request to list an item for sale on an e-commerce website. Item-related data for the item listing may be extracted. The item-related data can be used by a model to classify the new item listing. The model may be trained on data comprising identifications of which item listings in the sample of item listings are suspicious and identifications of which item listings in the sample of item listings are not suspicious may be received.

Suspicion classifier for website activity

A computer-implemented system and method for providing information tagging in a networked system is disclosed. The apparatus in an example embodiment includes a tag engine configured to process a database of categorized product listings; to receive a user-provided tag associated with at least one of the product listings; to retain the user-provided tag; and to serve the user-provided tag to a user viewing at least one of the product listings.

Providing informational tags within networked systems

A method and system to automatically categorize a merchant listing in an electronic marketplace are provided. The method includes parsing the category information submitted by a seller to derive a first category identifier. A first search is performed to locate the first category identifier in a first database containing a listing of category identifiers. If no match is found, the first category identifier is identified as expired or invalid. A second search is performed on a second database that includes mapping information of an expired category identifier to a new category identifier. If a match is found, the first category identifier is assigned as the new category identifier, thereby enabling the listing to be listed in the updated category automatically.

Method and system to categorize items automatically

A system and method of identifying suspicious item-related features are disclosed. In some embodiments, a sample of item listings is received. Each item listing in the sample of item listings may correspond to an item offered for sale on an e-commerce website. Item-related data for each item listing in the sample of item listings may be extracted. Training data comprising identifications of which item listings in the sample of item listings are suspicious and identifications of which item listings in the sample of item listings are not suspicious may be received. A model for classifying a candidate item listing on the e-commerce website as being suspicious may be determined using the training data.

A system and method of providing related search queries are disclosed. A new item listing is identified based on a determination that the new item listing lacks a predetermined minimum amount of clickstream data. Similar item listings for the new item listing is determined from a plurality of old item listings based on at least one item feature of the new item listing and the plurality of old item listings. The plurality of old item listings comprises live item listings and completed item listings. Each old item listing has at least the predetermined minimum amount of clickstream data. Related search queries of the similar item listings are associated with the new item listing. The related search queries for the new item listing are provided along with the new item listing to a user on a client device.

View item related searches

System and method for providing information tagging in a networked system

Query suggestions are provided using a query log including a number of user sessions that comprise training data. The training data includes a sequence of a plurality of sets of queries, some of the sets of queries including query transitions followed by a purchase related event. From a cleaned and normalized query log stationary scores and transition scores of at least some of the plurality of sets are generated. A set of query suggestions is built and similarity scores are computed for at least some of the set of query suggestions to determine whether individual ones of the at least some of the set of query suggestions meet a predetermined assurance level. Those that meet the assurance level are included as elements of the set of query suggestions. The set of query suggestions is mixed and ranked according to a user behavior that is sought to be influenced.

Query suggestion for e-commerce sites

Various embodiments disclose methods and systems to categorize automatically a merchant listing. In one example, the method includes determining a first category identifier for the merchant listing by performing a first search to compare the first category identifier with a plurality of category identifiers in a first database. Based on a determination that no match was found as a result of the first search, a second search is performed to compare the first category identifier with a plurality of category relationships in a second database. A second category identifier of the merchant listing is provided in response to a match being found in the second search and the second category identifier is associated with the merchant listing. Other methods and systems are disclosed.

A system and method of query expansion are disclosed. A query expansion source, a query expansion candidate, and feature data for the query expansion source and the query expansion candidate are received. The feature data comprises information for a plurality of features. A determination is made as to whether the query expansion candidate qualifies as an expansion of the query expansion source based on an analysis of the information for the plurality of features. The query expansion candidate is assigned as an expanded query of the query expansion source in a query expansion dictionary in response to a determination that the query expansion candidate qualifies as an expansion of the query expansion source.

Query expansion classifier for E-commerce

Providing query suggestions using a query log including a number of user sessions that comprise training data including a sequence of a plurality of sets of queries. Some of the sets of queries include query transitions followed by a purchase related event. The query log is cleaned and normalized. Query log stationary scores and transition scores of at least some of the plurality of sets is generated. A set of query suggestions is built and similarity scores are computed for at least some of the set of query suggestions to determine whether individual ones of the at least some of the set of query suggestions meet a predetermined assurance level. Those that meet the level are included as elements of the set of query suggestions that meet the predetermined assurance level. That set of query suggestions are mixed and ranked in accordance with a user behavior sought to be optimized.

Query suggestion for E-commerce sites

Method and system for categorizing items automatically

A system and method for modifying publication data in a publication system are described. An example embodiment includes receiving proposed publication data and accessing a success measurement associated with past publications within a publication system. The success measurement may indicate a measurement of success associated with the past publications. An example system and method may generate modification data to be used to modify the proposed publication data. The modification data may be based on the success measurement and proposed publication data.

Growing community of inventors

Campbell, CA, United States of America

Brian Scott Johnson