Yahoo! Inc.

Excalibur IP, LLC

Jessi Dong

Wei Du

Frank Taehyun Yoo

Paul Alex Broman

Biswadeep Nag

Tim Rechin

Jon Sweet

Qiong Zhang

Burke Culligan

Wei Yu

Wei Chu

Seung-Taek Park

John Greene

Charles Wang

Michael Helman

Uminder Singh

When a user enters a primary search query into a primary search query input area to perform a first search of the primary search query, disclosed is a method and system for automatically entering the primary search query into a secondary search query input area to perform a second search of the primary search query. When the user enters a secondary search query into the secondary search query input area to perform a first search of the secondary search query, the method and system automatically enters the secondary search query into the primary search query input area to perform a second search of the secondary search query.

Method and system for performing bi-directional search

Disclosed is a method and system for navigating, by a browser executing on the computing device, to a web page; transmitting by a client-side module executing on the computing device to a server computer over a network a request to the server computer for topics associated with the web page; receiving, by the computing device, a set of (one or more) topics associated with the web page from the server computer; displaying by the browser in a first content area the web page; and displaying by the browser in a second content area the received set of topics associated with the web page.

Method and system for topic-based browsing

Incremental training data is used to supplement a trained model to provide personalized recommendations for a user. The personalized recommendations can be made by taking into account the user's behavior, such as, without limitation, the user's short and long term web page interactions, to identify item recommendations. A trained model is generated from training data indicative of the web page interaction data collected from a plurality of users. Incremental training data indicative of other web page interaction data can be used to supplement the trained model, or in place of the trained model. Incremental training data can be indicative of user behavior collected more recently than the data used to train the model, for example.

Supplementing a trained model using incremental data in making item recommendations

A system and method are disclosed for optimizing the performance of an advertisement. The advertisement may be targeted based on correlations between advertisements and/or users. The correlations may be used to improve the click-through rate of advertisements. As data is collected and feedback is received, the correlation between ads and users may be updated, so that an advertiser's campaign can optimize its targeting of users.

System for optimizing ad performance at campaign running time

Two items are determined to be similar to each not only based on previous actual user behavior, but also based on the observed relatedness of the characteristics of those two items. A first characteristic and a second characteristic are determined to have some affinity for each other if a high proportion of users who select items having the first characteristics also select items that have the second characteristic, and vice-versa. Two items having characteristics with high affinity for each other are determined to have some similarity to each other, even if very few or no users who selected one of those items ever selected the other of those items. A first item that is determined to be sufficiently similar to second item in this manner may be recommended to a user who has selected the second item as potentially also being of interest to that user.

Predicting item-item affinities based on item features by regression

Growing community of inventors

Saratoga, CA, United States of America

Jessi Dong