Ebay, Incorporated

Paypal, Inc.

Jean-David Ruvini

Neelakantan Sundaresan

Badrul M Sarwar

Hassan Sawaf

Hill Trung Nguyen

Alvaro Bolivar

Hugh Evan Williams

Randall Scott Shoup

Gurudatta Horantur Shivaswamy

Sunil Mohan

Brian Scott Johnson

Brian M Johnson

Rajyashree Mukherjee

Venkat Sundaranatha

Musaab At-Taras

Jason M Heidema

Arun Lakshminarayanan

Benny Soetarman

Daniel Kramer

Smruthi Mukund

Prakash S Arunachalam

Qiaosong Wang

Andrew Chalkley

Ramesh Periyathambi

Lakshimi Duraivenkatesh

Ethan Benjamin Rubinson

Chi-Hsien Chiu

Bindia Saraf

Derek Barnes

Dileep Kumar Basam

Karin Mauge′

Radoslav Valentinov Petranov

Antoniya T Statelova

Vasilios Mitrokostas

Lauren Olver

Yingwei Xin

Ethan J Hart

A counterfeit item detection system detects counterfeit items during an item listing processes provided by an online marketplace. The system enhances the ability of the online marketplace to identify and reject potential counterfeit items. The system comprises a trained counterfeit item detection model that is configured to receive an image and identify whether the image includes a counterfeit item. The model is trained using a data set of training images. An image of the data set is taken from a video related to the time based on identifying that the context of text associated with the video relates to counterfeit items. The text can be determined from the video's audio, and the image is obtained at a time in the video where the text corresponds to a counterfeit item context.

Counterfeit item detection system

In an example, a text sentence comprising a plurality of words is obtained. Each of the plurality of words is passed through a deep compositional character-to-word model to encode character-level information of each of the plurality of words into a character-to-word expression. The character-to-word expressions are combined with pre-trained word embeddings. The combined character-to-word expressions and pre-trained word embeddings are fed into one or more bidirectional long short-term memories to learn contextual information for each of the plurality of words. Then, sequential conditional random fields are applied to the contextual information for each of the plurality of words.

Deep hybrid neural network for named entity recognition

Techniques for automatically modulating a physical configuration of a reconfigurable building structure. A reconfigurable building structure may be constructed of physical elements that are movable with respect to one another to facilitate actuating the reconfigurable building structure between a plurality of different physical configurations. The physical configuration of a reconfigurable building structure may be adjusted to accommodate for physical dimensions of an item that is going to be moved into the reconfigurable building structure. For example, a spacing between two shelves may be expanded in response to an order being placed for a large item. In this way, when the item is delivered to a physical address associated with the reconfigurable building structure, various physical characteristics of the reconfigurable building structure may have already been modulated to accept the item.

Systems and methods for automatically reconfiguring a building structure

A method of propagating annotations of content items to a search query is disclosed. A strength of a correspondence between a search query and a listing of an item on a network-based publication system is determined. The strength of the correspondence is based on an analysis of a set of actions by a set of users who submitted the search query. A set of annotations is generated. The set of annotations is propagated to a search engine and used to enhance search results.

Method for performing sequence labelling on queries

A counterfeit item detection system detects counterfeit items during an item listing processes provided by an online marketplace. The system enhances the ability of the online marketplace to identify and reject potential counterfeit items. The system collects item data in various formats. The item data is analyzed using speech-to-text software and natural language processing to determine data elements representing items, item features, and language context. Questions are generated using the items and item features, and stored for each item. Answers to the questions have associated counterfeit indication weights. The weights are modified and used to rank the questions as feedback is received about counterfeit items. The ranking determines future question selection, allowing the best questions to continually be identified and provided. The counterfeit item detection system also trains a neural network to detect counterfeit items in images, where the training images are obtained from videos related to the item.

An apparatus and method for predicting a brand name of a product are disclosed herein. A product identification number for the product is converted into a normalized global trade item number (GTIN). For each of a plurality of GTIN prefixes corresponding to the normalized GTIN, brand names and counts of each of the brand names using product information stored in a product catalog are identified. A probability distribution of the brand names is determined in accordance with the brand names and the counts of the brand names for the plurality of the GTIN prefixes. A predicted brand name for the product is identified from among the brand names for the plurality of the GTIN prefixes, the predicted brand name having a highest probability score in the probability distribution of the brand names.

Determining and using brand information in electronic commerce

Systems and methods for improving an information provisioning system using a natural language conversational assistant is provided. A machine agent initiates an interactive natural language conversation with a user to provide the user with guidance on one or more products. The machine agent receives a request for information from the user, and accesses, from a product knowledge database, textual statements about features of the one or more products, whereby the textual statements are obtained by a machine-based offline knowledge extraction process that extracts the textual statements from reviews or product guides. Based on the accessed textual statements and an overall empirical utility of each of the accessed textual statements, the machine agent determines one or more statements of the accessed textual statements to convey to the user. The machine agent causes presentation of the one or more statements to the user.

Conversational assistant using extracted guidance knowledge

There is provided a method and system for qualification testing in a social network service. Qualification testing provides access control into a social network, wherein qualification is based on answers to questions related to a topic. In one example, members admitted to the network provide guidance, notes and research assistance to another member. The social network members access the social network from an external networked computing service, such as another social network, to facilitate easy connection to potential members. The social network may be implemented as an application overlay to the external service, or may access connections in the external network.

Method and apparatus for social network qualification systems

In some embodiments, a method includes receiving an electronic document that comprises a plurality of sections. The method includes marking the plurality of sections as a content section or a non-content section using a visual attribute of the sections that includes at least one of a width of the section, a density of the plurality of hyperlinks in the section, a size of a font of text in the section and whether a title of the electronic document overlaps with text in the section. The method also includes storing the marking of the plurality of sections of the electronic document in a machine-readable medium.

Identification of content in an electronic document

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 of forming parallel corpora comprises receiving sets of items in first language and second languages, each of the sets having one or more associated descriptions and metadata. The metadata is collected from the two sets of items and are aligned using the metadata. The aligned metadata are mapped from the first language to the second language for each of the sets. The descriptions of two items are fetched and the structural similarity of the descriptions is measured to assess whether two items are likely to be translations of each other. For mapped items with structurally similar descriptions, the mapped item descriptions are formed into respective sentences in first language and in the second language. The sentences are parallel corpora which may be used to translate an item from the first language to the second language, and also to train a machine translation system.

Methods for automatic generation of parallel corpora

Growing community of inventors

Los Gatos, CA, United States of America

Jean-David Ruvini