Ebay, Incorporated

Paypal, Inc.

Julie Lavee Netzloff

Muhammad Faisal Rehman

Ryan McDonald

Ken Sun

Olivier G Dumon

Oliver G Dumon

Sanjay Pundlkrao Ghatare

Brian Scott Johnson

Michael Ching

Vamsi Salaka

Ashita Achuthan

Methods and systems for analyzing, ordering and presenting item listings are described. In one example embodiment, a search query is processed to identify item listings satisfying the search query. Then, for each item listing that satisfies the search query, a ranking score is derived and assigned to the item listing. The ranking score is based in part on a relevance score, a listing quality score and a business rules score (or, adjustment factor). Finally, the item listings are ordered, based on their corresponding ranking score, and presented in order in a search results page.

Methods and systems for deriving a score with which item listings are ordered when presented in search results

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 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.

Methods and systems for using a demand metric for disambiguating a keyword entered from a user of a client machine, the keyword ambiguously identifying a product category, deriving a dominant product category that indicates the probable identity of the product category, and providing selectable images of aspects of the dominant product category for rendering at the client machine. Selection of one of the selectable images of aspects of the dominant product category disambiguates the identity of the ambiguously identified product category. Additional aspects of the disambiguated product category are then presented to the user.

Methods and systems for determining a product category

A method and system for determining an order of presentation of the search results is provided. An example system comprises a search request detector, a search engine, and an intermingler. The search request detector may be configured to receive a search request, and the search engine may be configured to determine search results based on the search request. The search results may comprise a first set of items of a first type and a second set of items of a second type. The number of items in the first set and the number of items in the second may reflect a predetermined target ratio. The intermingler may be configured to determine an order of presentation of the search results in a list of search results based on the target ratio.

Method and system for determining an order of presentation of search results

Methods and systems for using a demand metric for disambiguating a keyword entered from a client machine, the keyword identifying a product brand and ambiguously identifying a product category of the product brand; computing the dominant product category that indicates the probable identity of the product category; and providing signals representing selectable images of aspects of the dominant product category for rendering at the client machine.

Methods and systems using demand metrics for presenting aspects for item listings presented in a search results page

A method and system for determining an order of presentation of the search results is provided. An example system comprises a search request detector, a search engine, and an intermingler. The search request detector may be configured to receive a search request, and the search engine may be configured to determine search results based on the search request. The search results may comprise a first set of items in a first format and a second set of items in a second format. The number of items in the first set and the number of items in the second may reflect a predetermined target ratio and respective exposure percentages for items in the first format and items in the second format. The intermingler may be configured to determine an order of presentation of the search results in a list of search results based on the target ratio.

Methods and systems for evaluating business rules for the purpose of promoting or demoting an item listing are presented. Consistent with an example embodiment, a conditional statement of a business rule that includes one or more expressions involving an item attribute and/or a seller attribute for an item listing is evaluated. If the conditional statement evaluates true, an adjustment factor set forth in the business rule is applied to a ranking score assigned to the item listing. The item listing is then presented in a search results page in a position relative to other item listings based upon the adjusted ranking score.

Method and system for adjusting product ranking scores based on an adjustment factor

Methods and systems for using a half-life formula for deriving demand metrics used in ordering item listings, when presenting those item listings in a search results page, are described. In some embodiments, a demand metric for an item listing is derived by monitoring events associated with item listings, such as, keeping a count of the number of search impressions an item listing receives. A half-life formula is used to ensure that events occurring earlier in time contribute less to the demand metric than more recently occurring events. The demand metric are used to order the item listings, when the item listings are being presented in a search results page.

Growing community of inventors

San Jose, CA, United States of America

Julie Lavee Netzloff