Ebay, Incorporated

Manojkumar Rangasamy Kannadasan

Ajinkya Gorakhnath Kale

Ramesh Periyathambi

Lakshimi Duraivenkatesh

Selcuk Kopru

Tomer Lancewicki

Rajyashree Mukherjee

Vineet Bindal

Sai Vipin Siripurapu

Saratchandra Indrakanti

Amit Jaiswal

Shubhangi Tandon

Svetlana Strunjas

A search engine is provided that generates search results proportional to a natural distribution. Search results identified and ranked by the search engine for a search query are redistributed so that a fixed number of top ranked search results include search result attributes proportional to the natural distribution, as determined from interaction tracking of prior search results. A natural distribution index mapping prior search queries to search result attributes and a proportional representation of interactions with the search result attributes is generated. The natural distribution is determined from the proportional representation of interactions. The search engine redistributes the fixed number of top ranked search results by minimizing a gap between the ranked set of search results for the search query and the natural distribution.

Search system ranking using a natural distribution

In various example embodiments, a system and method for determining a spam publication using a spam detection system are presented. The spam detection system receives, from a device, an image of an item and an item attribute for the item. Additionally, the spam detection system extracts an image attribute based on the received image, and compares the item attribute and the image attribute. Moreover, the spam detection system calculates a confidence score based on the comparison. Furthermore, the spam detection system determines that the item attribute is incorrect based on the confidence score transgressing a predetermined threshold. In response to the determination that the item attribute is incorrect, the spam detection system causes presentation, on a display of the device, of a notification.

Methods and apparatus for detection of spam publication

Technologies are disclosed herein for distributing information. The disclosed technologies determine an application element configured to receive information that is updated at a variable rate, the information pertaining to an object. Feature data is received that is associated with the object and data associated with use of the application element. The feature data includes a time horizon for the object and supplemental information associated with the object. Based on the feature data and the data associated with use of the application element, a first rate is predicted for sending the information about the object to the application element. The information is sent to the application element at the first rate.

Adaptive timing prediction for updating information

A search engine provides diverse search results in response to a search query using a trained diversity ranker. The diverse results may be generated by determining ranking positions of at least some search results based on delta feature values that are dependent on higher-ranked results. Delta feature values indicate a degree or magnitude of difference between a particular result and other results with respect to a particular feature, such as price, category, or shipping type. In providing the ranked results for presentation to a user at a computing device, a diversity feature indicator for at least some results may be generated. The diversity feature is a feature that distinguishes a given result from other results. As such, the diversity feature indicator represents that diversity feature for the particular result being different from other results and distinguishes the diversity feature from other features in the particular result.

Method, media, and system for generating diverse search results for presenting to a user

Techniques for prefetching operation cost based digital content and digital content with emphasis that overcome the challenges of conventional systems are described. In one example, a computing device may receive digital content representations of digital content from a service provider system, which are displayed on a user interface of the computing device. Thereafter, the computing device may also receive digital content as prefetches having a changed display characteristic as emphasizing a portion of the digital content based on a model trained using machine learning. Alternatively, the computing device may receive digital content as a prefetch based on a model trained using machine learning in which the model addresses a likelihood of conversion of a good or service and an operation cost of providing the digital content. Upon receiving a user input selecting one of the digital content representations, digital content is rendered in the user interface of the computing device.

Techniques of prefetching operation cost based digital content and digital content with emphasis

Images of items often include a significant amount of information that can be used in categorizing the item (e.g., as a book, a phone, or an accessory) or in identifying attributes of the item (e.g., the item's color or style). A user provides a search query for listings of items. Images of items in listings previously selected by users providing the same search query are analyzed to identify the category or attributes of the depicted items. The identified category or attributes are added to the user's search query. Listings matching the modified search query are provided to the user.

Generating structured queries from images

In various example embodiments, techniques for querying a product in a database of a publication system using a tail query are presented. An application interface module receives, from a device of a user, a tail query for a product in the publication system. The tail query has a common term and an uncommon term. A data storage interface module can access, from a search metrics database, a plurality of product categories associated with the common term, and access user behavior data, with the user behavior data including product views corresponding to past search queries in the publication system. A category predictor can determine a first product category from the plurality of product categories for the tail query based on the user behavior data and information derived from the search metrics database. A listing generator can generate an ordered list of product listings associated with the first product category based on the user behavior data.

Growing community of inventors

Santa Clara, CA, United States of America

Manojkumar Rangasamy Kannadasan