Yahoo! Inc.

Oath Inc.

Verizon Media Inc.

Yahoo Assets LLC

Excalibur Ip, LLC

Yahoo Holdings, Inc.

Scott J Gaffney

Jean-Marc Langlois

Xing Yi

Suju Rajan

Nathan Liu

Zornitsa Kozareva

Pavel Berkhin

Shenhong Zhu

Hang Su

Huming Wu

Hui Wu

Jiuhe Gan

George H John

John Canny

Xiaobing Han

Yuan Zhang

Chun Ming Sze

Liangjie Hong

Mingtian Liu

Chad Brower

Shi Zhong

Andrew Stephen Tomkins

Rajesh Girish Parekh

Yi Chang

Abhay K Gupta

Kunal Punera

Conrad Wai

Adwait Ratnaparkhi

Dragomir Dimitrov Yankov

Bruno Fernandez-Ruiz

Alyssa Glass

Prabhakar Krishnamurthy

Usama M Fayyad

Choon Hui Teo

Prateeksha Uday Chandraghatgi

Bruno Fernandez Ruiz

Aharon Lavi

Bassel Ojjeh

Yiping Han

Dilan Gorur

Dun Liu

Wanlin Pang

Jie Luo

Jin Lim

Shi Zhonog

Methods, systems, and computer programs are presented for displaying a customized news stream. One method includes an operation for identifying dwell times spent by users while accessing a first plurality of items, each item belonging to one media type from a plurality of media types (e.g., news articles, videos, slide shows, etc.). In addition, the method includes operations for determining statistical parameters for each media type based on the identified dwell times, and for detecting a news corpus having a second plurality of items. A priority for each item in the news corpus is determined based on the media type of the item, the corresponding statistical parameters for the media type of the item, and the profile of a user. The news stream is sent to the user for presentation on a display, the news stream being sorted based on the priority of the items in the news corpus.

Prioritizing items from different categories in a news stream

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

Method, system, and programs for measuring user engagement. In one example, a model generated based on user activities with respect to a plurality pieces of content is obtained. One or more actual occurrences of the user activities with respect to one piece of the plurality pieces of content are identified. One or more future occurrences of the user activities with respect to the piece of content are estimated based on the model. A user engagement score with respect to the piece of content is calculated based on the one or more actual occurrences of the user activities and the one or more future occurrences of the user activities.

Method and system for measuring user engagement using click/skip in content stream

The present teaching, which includes methods, systems and computer-readable media, relates to providing content from multiple disparate sources including a person's personal data sources and non-personal data sources. The disclosed techniques may include receiving a request for content from a person; obtaining first content from a first source private to the person based on the request; obtaining second content from at least one second source based on the request; blending the first content from the first source and the second content from the at least one second source to generate a blended content; and providing the blended content to the person in response to the request.

Methods, systems and techniques for blending online content from multiple disparate content sources including a personal content source or a semi-personal content source

A method, implemented on at least one computing device each of which has at least one processor, storage, and a communication platform connected to a network for providing synthetic answers to a personal question is disclosed. A personal question is received from a person. One or more entities are extracted from the personal question. One or more relations are extracted from the personal question. A model is selected based on the personal question. One or more synthetic answers to the personal question are obtained based on the one or more entities, the one or more relations, and the selected model.

Method and system for providing synthetic answers to a personal question

The present teaching, which includes methods, systems and computer-readable media, relates to ranking content from multiple disparate sources including a person's personal data sources and non-personal data sources. The disclosed techniques may include obtaining a plurality sets of content associated with a request from a person, each of which being from a separate data source, and applying a model for each set of content to obtain a set of features for each piece of content in the set of content, wherein the model is specific to a data source from where the set of content comes from. Each set of features for each piece of content of the set of content may be normalized with respect to a common space to generate a normalized feature set. Further, a score for each piece of content from a set of content may be estimated based on the normalized feature set for the piece of content, and based on the score of the piece of content, each piece of content of the plurality sets of content may be ranked.

Methods, systems and techniques for ranking blended content retrieved from multiple disparate content sources

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

The present teaching relates to online task exchange. In one example, information related to a task automatically created based on an intent of a person is received. The task is posted to a plurality of parties that are capable of completing the task. One or more bids are received from at least some of the plurality of parties. At least one winning bid is selected from the one or more bids based on at least one criterion. Information indicative of a status as to completion of the task is received. Resource is allocated to the at least one winning bid based on the status.

Method, system and machine-readable medium for online task exchange

A method, implemented on at least one computing device, each of which has at least one processor, storage, and a communication platform connected to a network for classifying a question is disclosed. A question is received from a person. A question pattern is determined. A model selected based on the question is retrieved. Further, a decision is made as to whether the question is a personal question based on the question pattern and the selected model.

Method and system for classifying a question

Methods, systems and programming for evaluating user satisfaction with respect to a user session are presented. In one example, one or more queries in a use session are received from a user. Information about one or more user activities is obtained. Each user activity is related to manipulation of a content item associated with one of the one or more queries. A score associated with the user session is computed based at least partially on the one or more user activities. User satisfaction with respect to the user session is determined based on the score.

Method and system for evaluating user satisfaction with respect to a user session

The present teaching relates to updating an intent space and estimating intent based on an intent space. In one example, an initial intent space is obtained. Each intent in the initial intent space is characterized in one or more dimensions. At least one model is received. Each of the at least one model provides features in each of the dimensions and relationship thereof. A new intent associated with an intent in the initial intent space is determined based on the at least one model. Based on the new intent, the initial intent space is updated to derive an updated intent space.

Method and system for updating an intent space and estimating intent based on an intent space

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Sunnyvale, CA, United States of America

Scott J Gaffney