Facebook, Inc.

Aol Inc.

Mercury Kingdom Assets Limited

Bright Sun Technologies

Harmannus Vandermolen

Lara Mehanna

Gerald Campbell

Shawkat Hasan

Abdur Chowdhury

Karen Nelson Howe

Scott J Levine

Anthony Wiegering

Michael Sommers

Charles Fish

Paul Vidich

Alexander Franco

Eric Jensen

David C Sobotka

Gregory Scott Pass

Dimitre Piskyulev

Justin M Law

James Mark Canon

David Pautler

Oliver Cahill

Martin Boyle

Ultan O'Carroll

Shawn C Rose

John McClean

Amelia P Williams

Content that is significant to a user may be determined. An indication that a user finds content within a document significant may be received. In response to the received indication, the document may be analyzed to identify a set of topics associated with the content of the document. From the set of topics, a subset of topics responsible for the user finding the document significant may be identified. A user profile associated with the user may be updated based on the subset of topics.

Identification and disambiguation of electronic content significant to a user

Video trailers for a video quote may be created and provided to a user. The Internet may be searched to identify documents that likely include references to a video. A reference to the video within an identified document may be detected and determined to be a video quote. The video quote and related information may be extracted from the identified document. A location of the video quote within the video may be determined. A video trailer that includes the video quote may be created based on the location of the video quote. A request for a video trailer that includes a video quote or a partial video quote, specified by the user, may be received from the user. A video trailer that includes the video quote or the partial video quote may be identified and provided to the user.

Audio and/or video scene detection and retrieval

Identification of electronic content significant to a user

Information may be presented to a user by using a first application to receive a character stream of one or more noncompletion characters. The noncompletion characters indicate that additional characters may be received. The character stream is exchanged with a host that analyzes the character stream to generate results that are responsive to the user's predicted interest. Results are received and displayed so that the user may select one of the results to launch a code segment related to the selected result.

Host-based intelligent results related to a character stream

Multimedia stream search results may be made perceivable to a user. A multimedia search query may be received from a user. The multimedia search query may be compared with information related to known multimedia streams and multimedia search results may be determined based on the comparison. A popularity of the multimedia streams corresponding to the multimedia stream search results may be determined based on a number of canonical URLs associated with the multimedia stream. A presentation of the multimedia stream search results to the user may be configured based on the popularity of the corresponding multimedia streams.

Storing fingerprints of multimedia streams for the presentation of search results

Search results may be yielded based on a search query. A search query inspired by a user may be received. Based on the search query, multiple search results each including links may be determined. The multiple search results may include a first search result that includes a link to a first digital instance that describes or embodies a first content item, and a second search result that includes a link to a second digital instance that describes or embodies a second content item. A perceived popularity may be assessed for each of the first and second content items. The perceived popularity may be a measure of the popularity of the first and second content items, and may be distinct from a popularity of the first and second digital instances. A presentation of the multiple search results may be determined based on the accessed perceived popularity.

Popularity of content items

User interface elements for identifying electronic content significant to a user

Search results may be provided to a user. A search query may be received from the user. A query feature vector may be formed for the search query. The query feature vector may be compared with news feature vectors associated with documents related to current events. An augmented query feature vector may be formed based on results of the comparison of the query feature vector with the news feature vectors. The augmented query feature vector may be compared with feature vectors related to target documents. Search results that include target documents may be identified based on results of the comparison of the augmented query feature vector with the feature vectors related to the target documents. The user may be made able to perceive at least some of the identified search results.

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Leesburg, VA, United States of America

Harmannus Vandermolen