Yahoo Assets LLC

Oath Inc.

Verizon Media Inc.

Yahoo Holdings, Inc.

Chun Ming Sze

Shenhong Zhu

Huming Wu

Scott J Gaffney

Hang Su

Hui Wu

Jiuhe Gan

Xiaobing Han

Yuan Zhang

Mingtian Liu

Farzin Maghoul

Kazuhiro Nakao

Zhongqiang Chen

The present teaching, which includes methods, systems and computer-readable media, relates to providing query suggestions based on a number of data sources that include person's personal data and non-personal data. The disclosed techniques may include receiving an input from a person, obtaining a first set of suggestions based on a person corpus derived from at least one data source private to the person, obtaining a second set of suggestions based on information from an additional data source, ranking the first and second sets of suggestions to generate a ranked list of suggestions, and presenting at least some of the ranked suggestions.

Methods, systems and techniques for ranking personalized and generic search query suggestions

The present teaching, which includes methods, systems and computer-readable media, relates to providing query suggestions based on a number of data sources including person's personal data and non-personal data. The disclosed techniques may include receiving an input from a person, obtaining a first set of suggestions based on information from a first data source, presenting the first set of suggestions to the person, and presenting, to the person, a second set of suggestions obtained from a person corpus when a portion of the person corpus relevant to the input is accessible. The person corpus may be from a second data source that is private to the person.

Methods, systems and techniques for providing search query suggestions based on non-personal data and user personal data according to availability of user personal data

The present teaching, which includes methods, systems and computer-readable media, relates to providing query suggestions based on multiple data sources including at least person's personal data. The disclosed techniques may include receiving an input from a person, obtaining one or more suggestions based on a person corpus derived from at least one data source private to the person, and presenting at least the one or more suggestions.

Methods, systems and techniques for personalized search query suggestions

Techniques are provided for automatically determining when to trigger instant search. In one technique, while a user is entering text to formulate a search query, and prior to receiving an indication that the user has completed formulation of the search query, a search assistant system determines the most popular queries that include the text the user has already entered. The search assistant system then determines whether to proactively provide, to the user, search results for the top-candidate of those completed queries. That determination may take into account factors such as whether the top-candidate qualifies as a dominant completed query, a richness metric determined for the search results for the particular completed query, and/or a satisfaction metric determined for the search results for the particular completed query. If the search assistant system determines to proactively provide search results for the particular completed query, the search results for the particular completed query are presented to the user prior to receiving any indication that the user has completed formulation of the search query.

Triggering method for instant search

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Fremont, CA, United States of America

Chun Ming Sze