Hewlett-packard Development Company, L.p.

Yahoo! Inc.

Excalibur Ip, LLC

Slack Technologies, Inc.

Ooyala, Inc.

Zhichen Xu

Jianchang Mao

Chung-Man Tam

Kenneth Norton

Mallik Mahalingam

Yun Fu

Qi Lu

Eckart Walther

David Ku

Zheng Zhang

Chunqiang Tang

Ashley Woodman Hall

Adrienne Bassett

Nathan Arnold

Sung-Ju Lee

Sujata Banerjee

Daniel Eric Rose

Ali Diab

Magnus Karlsson

Kevin Lee

Neal J Sample

Li Xiao

George H Forman

Hao Xu

Bo Shen

Farzin Maghoul

Wenting Tang

Abe Taha

Zhiheng Wang

Aurora Skarra-Gallagher

Pavel Berkhim

Dejan S Milojicic

Christos Karamanolis

John JianShi Wang

Vanish Talwar

Rajendra Kumar

Liang-Yu Tom Chi

Liang-Yu (Tom) Chi

Chad P Walters

Pavel Berkhin

Lei Huang

Eren Manavoglu

Artur Andrzejak

Yong Yan

Nimrod Hoofien

Peter Yen

Ning Song

Pavel Berkin

Dan Rose

Jiangchang Mao

Sami Abu-El-Haija

Dmitry Yurievich Pavlov

Paul Heymann

Chungtang Tang

Difu Su

Albert Meltzer

Computer systems and methods incorporate user annotations (metadata) regarding various pages or sites, including annotations by a querying user and by members of a trust network defined for the querying user into search and browsing of a corpus such as the World Wide Web. A trust network is defined for each user, and annotations by any member of a first user's trust network are made visible to the first user during search and/or browsing of the corpus. Users can also limit searches to content annotated by members of their trust networks or by members of a community selected by the user.

Search system and methods with integration of user annotations from a trust network

The present invention is directed towards systems and methods for trust propagation. The method according to one embodiment comprises calculating a first feature vector for a first user, calculating a second feature for a second user and comparing the first feature vector with the second feature vector to calculate a similarity value. A determination is made as to whether the similarity value falls within a threshold. If the similarity value falls within the threshold, a relationship is recorded between the first user and the second user in a first user profile and a second user profile.

Trust propagation through both explicit and implicit social networks

The present invention relates to systems, methods, and user interfaces for browsing a collection of content items saved by a user or by one or more buddies associated with a given user. The method of the present invention comprises saving one or more content items and one or more associated keywords as specified by a user. An interface is generated that displays the one or more saved content items and the one or more associated keywords, as well as the one or more buddies associated with a given user. A user indication of the selection of a given keyword or the selection of a given buddy by the user is received. The one or more displayed content items are filtered according to the selected keyword, buddy, or combination of selected keyword and buddy.

User interface for navigating a keyword space

Techniques are described for identifying one or more 'interest twins' of a user. An interest twin of a user in another user that has demonstrated interests in items that are the same as or similar to the items in which the user has demonstrated an interest. Various techniques are described for reducing the overhead in interest twin determination operations. Once the interest twins for a user have been identified, the knowledge of the interest twins may be used in a variety of ways to enhance to experience of the user. For example, a mechanism may be provided which allows the user to see a list of items in which the user's interest twins have indicated an interest.

Asymmetric identification of interest twins in an online community

Services are provided via a multicast tree. A request to receive a service is received at a node. Stored information at the node is searched to identify a service path or a service node operable to provide the requested service.

Requesting a service from a multicast network

Embodiments are directed towards modifying a distribution of writers as either a push writer or a pull writer based on a cost model that decides for a given content reader whether it is more effective for the writer to be a pull writer or a push writer. A cache is maintained for each content reader for caching content items pushed by a push writer in the content writer's push list of writers when the content is generated. At query time, content items are pulled by the content reader based on writers a content reader's pull list. One embodiment of the cost model employs data about a previous number of requests for content items for a given writer for a number of previous blended display results of content items. When a writer is determined to be popular, mechanisms are proposed for pushing content items to a plurality of content readers.

Push pull caching for social network information

Techniques are provided for selecting a diverse mix of content items that may be displayed to a user. Content items such as user-generated events are received from a variety of sources. One or more content items are added to a set of content items based on a diversity of characteristics. The diversity of characteristics for the one or more content items may be calculated by measuring a diversity of characteristics of the set as if the one or more content items were added to the set. Content items that produce a greater diversity are selected for addition to the set. The set is displayed to the user, who is provided with a more meaningful mix of content due to the greater diversity in content.

Entropy-based mixing and personalization

A method and a computer-readable medium are provided which perform screen scraping via grammar induction. The computer-readable medium stores instructions of the method, the instructions directing a computer processor to intercept display information transmitted to a computer-implemented display device representing information stored in a data source; induce a grammar via statistical analysis of the intercepted display information; provide the grammar to a parser-generator to generate a parser corresponding to the induced grammar; and perform screen scraping using the generated parser.

Automated screen scraping via grammar induction

Embodiments are directed towards a Modified Sequitur algorithm (MSA) using pipelining and indexed arrays to identify trending topics within a plurality of documents having user generated content (UGC). The documents are parallelized and distributed across a plurality of network devices, which place at least some of the received documents into a buffer for which the MSA may then be applied to the documents within the buffer to identify n-grams or phrases within the documents' contents. The identified phrases are further analyzed to remove extraneous co-occurrences of phrases, and/or words based on a part of speech analysis. A weighting of the remaining phrases is used to identify trending topic phrases. Links to content in the plurality of UGC documents that is associated with the trending topic phrases may then be displayed to a client device.

Efficient lexical trending topic detection over streams of data using a modified sequitur algorithm

Location information for a node in a network is determined. A first distance from the node to at least one global landmark node is determined and a second distance from the node to at least one local landmark node proximally located to the node is determined. Location information for the node based on the first distance and the second distance is generated.

Determining location information for a node in a network using at least one local landmark node

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Zhichen Xu