Ebay, Incorporated

Paypal, Inc.

Ranjan Sinha

Ashish Gupta

Sami Ben-Romdhane

Chaitali Gupta

Matthias Spycher

Charles Bracher

Mayank Bansal

Tzu-Cheng Chuang

In various example embodiments, a system and method for constructing and scoring word vectors between natural language words and generating output to a user in the form of personalized recommendations are presented.

Generating personalized user recommendations using word vectors

A personalization system includes a user events module configured to receive a plurality of user events, each user event of the plurality of user events including one or more of a transactional event and a behavioral event associated with the online user, and a personalization cluster including a plurality of personalization servers, each personalization server of the plurality of personalization servers configured to receive a personalization request from a requesting system, the personalization request including a plurality of intermediate results identified by the requesting system, each intermediate result representing a possible outcome that may be presented by the requesting system to the online user, compute a score for each intermediate result of the plurality of immediate results based at least in part on the plurality of user events, thereby generating a plurality of scores, and return the plurality of scores to the requesting system.

Personalization platform

In an example embodiment, clusters of nodes in a network are monitored. Then the monitored data may be stored in an open time-series database. Data from the open time-series database is collected and labeled it as training data. Then a model is built through machine learning using the training data. Additional data is retrieved from the open time-series database. The additional data is left as unlabeled. Anomalies in the unlabeled data are computed using the model, producing prediction outcomes and metrics. Finally, the prediction outcomes and the network.

Predictive model for anomaly detection and feedback-based scheduling

Growing community of inventors

San Jose, CA, United States of America

Ranjan Sinha