Jive Software, Inc.

Yahoo! Inc.

Pinterest, Inc.

Yahoo! Overture

Lance Alan Riedel

Vanja Josifovski

Mukund Narasimhan

Jared Smith-Mickelson

Andrei Z Broder

Marcus Felipe Fontoura

Evgeniy Gabrilovich

Sonja Sabina Knoll

Vitaliy Kulikov

Yu Liu

Chao Wang

Siyang Xie

Donald Metzler

Andrew Look

John Milinovich

Andrew Liu Chen

Raymond Hsu

Jiacheng Hong

Zheng Liu

Cole Timothy Rottweiler

Brian W Johnson

Robert J Collins

Yiping Zhou

Brian Johnson

Shaji Sebastian

Georgios Mavromatis

Peter Ciccolo

Graham Harris

Jesse Harris

Grant Kushida

Mohammad Sabah

Jeff Yuan

Techniques and tools are described for producing time-series data using faceted search based on document creation time. For example, index information can be created from events (e.g., by adding meta-data and indexing the events as documents). In addition, index information can be created that maps document creation time to time ranges. Search queries can then be executed (e.g., comprising ad-hoc filters to filter on the meta-data), and search results can be faceted on the time ranges to produce time-series data. The time-series data can be graphed to display trends of activity (e.g., trends of events based on user activity).

Fast ad-hoc filtering of time series analytics

According to aspects of the disclosed subject matter, a taste graph comprising likely content collection nodes with corresponding likely digital content items is generated through one or more analyses of a corpus of content collections that is maintained by the online content service. As should be understood, this corpus of content collections is comprised of a plurality of curated content collections, with each content collection comprising a plurality of digital content items. With this taste graph available, as a user generates (or in response to a user generating) a content collection of digital content items, reference can be made to the taste graph to identify one or more digital content items that may be added to the content collection, where the one or more digital content items have a probabilistic likelihood of being complimentary and/or compatible with the other digital content items of the content collection.

Probabilistic determination of compatible content

The described implementations are operable to determine potential objects of interest to a user based on a blend of the user's long-term behavior and short-term interests. Long term user behavior may be determined for the user over a period of time and represented as continuous data. Short-term interest may be determined based on objects with which the user has recently interacted, and attributes of those objects may be represented together as continuous data corresponding to the short-term user interest. The continuous data of the short-term user interest and long-term user behavior may be blended to produce a user embedding. The user embedding may then be compared with objects to determine objects that are of potential interest to the user.

Object identification based on long-term user behavior and short-term interest

The described implementations are operable to determine potential objects of interest to a user based on a blend of the user's long-term behavior and short-term interests. Long term user behavior may be determined for the user over a period of time and represented as continuous data. Short-term interest may be determined based on objects with which the user has recently interacted and attributes of those objects may be represented together as continuous data corresponding to the short-term user interest. The continuous data of the short-term interest and long-term user behavior may be blended to produce a user embedding. The user embedding may then be compared with objects to determine objects that are of potential interest to the user.

Techniques and tools are described for matching documents against monitors. An index can be generated from a plurality of monitors, where the index represents the query logic of the plurality of monitors. The index can be searched using the documents as search queries. The searching can comprise matching the documents against the monitors using the query logic represented in the index. An index can be distributed to a plurality of computing devices to be searched at the plurality of computing devices, where each computing device searches a subset of a plurality of documents against the full index. Searching at the plurality of computing devices can be performed in parallel, and results can be aggregated at a central location.

Matching documents against monitors

Techniques and tools are described for augmenting search using association information. Searches can be performed using a combination of index information and association information. In some examples, index information is stored in a first data store and association information is stored in a second data store. Search queries can be received and modified using association information. Modified search queries can be executed using a combination of index information and association information. Index information can be generated by indexing a set of documents. Association information can be generated by monitoring user activity occurring between users and a set of documents.

Augmenting search with association information

A system and method to facilitate matching of content to advertising information in a network are described. A request for advertising information is received over a network, the advertising information to be displayed for a user entity in association with content information within a web page requested by the user entity. Advertising information related to one or more themes of the content information on the web page is further determined, the themes representing subject matter contextually related to the content information. Advertisements are further selected from the advertising information based on keywords and metadata stored within the web page and based on a set of predetermined parameters stored within the data storage module. The selected advertisements are further ranked to obtain a ranked list of advertisements. The ranked list of advertisements is subsequently optimized based on feedback data to obtain a list of optimized advertisements to be displayed for the user entity on the requested web page.

System and method to facilitate matching of content to advertising information in a network

A method is disclosed for expansion of rare queries to improve advertisement results, including receiving a query from a user by a search engine; determining that the query does not match an entry in an ad query lookup table coupled with the search engine; retrieving one or more expanded queries located within a query feature index whose features relate to one or more features of the received query, wherein the query feature index includes a plurality of queries expanded based on at least corresponding search results; generating, in real time and by the search engine, an ad query including an expanded version of the received query based on features of the retrieved expanded queries; and selecting one or more advertisements based on the generated ad query, wherein the one or more advertisements are displayed to the user in response to the query received from the user.

Rare query expansion by web feature matching

A system and method to facilitate classification and storage of events in a network are described. An event and associated content information are received from an entity over a network. The content information is further analyzed to determine one or more themes representing subject matter related to the content information. The event is further classified according to the themes into one or more corresponding categories. Finally, the event is stored into one or more corresponding databases of a data storage module according to the one or more corresponding categories.

System and method to facilitate classification and storage of events in a network

The present invention is directed towards systems, methods and computer program products for providing query-based advertising content. According to one embodiment, a method for providing query-based advertising content comprises receiving a web query and generating an ad query associated with the web query, wherein the ad query is generated on the basis of one of a query to advertisement relationship, a query to feature vector relationship, or a rewritten query vector. An advertisement is selected on the basis of the generated ad query.

Systems and methods for query expansion in sponsored search

The present disclosure is directed to systems and methods for determining semantically related terms. Generally, one or more seed terms are received from a user. A system searches a first index comprising a plurality of terms and one or more webpages associated with each term of the plurality of terms to determine a plurality of webpages associated with the seed terms. The system then searches a second index comprising a plurality of webpages and one or more terms associated with each webpage of the plurality of webpages to determine a plurality of potential terms associated with the plurality of webpages associated with the seed terms. At least one term of the plurality of potential terms is suggested to a user.

System and method for determining semantically related terms

Growing community of inventors

Menlo Park, CA, United States of America

Lance Alan Riedel