Burning Glass Technologies, LLC

Yahoo! Inc.

Mark Alan Laffoon

Anu Kumar Pathria

Theodore James Crooks

Amir Doron

Bradley D Kindig

Dayne B Freitag

Kevin L Sitze

Philip Mansiel Pellouchoud

Edmond D Chow

Daniel Baird

Michael J Kogan

Krishna Gopinathan

Sean Cornell Joshlin

Matthew N Dailey

Sean Robert Sullivan

Robert F Kleemann

Ameen Hikmat Abed

Nathan Lavar Clegg

An online music purchasing system and method is disclosed, in which a radio service operates on a user's computer and is configured for receiving and playing digital radio representations of media content in near real-time in a radio session. A content server is configured for serving the digital radio representations of media content to the radio service, and a radio sequence server is configured for serving a sequential list of currently-playing and previously-played media content of the radio session to the radio service. An account server is configured for receiving a signal indicative of a user's desire to purchase a file of one of a currently-playing or previously-played media content. A download manager is configured for downloading the file to the user's computer according to the signal indicative of the user's desire to purchase the file.

Music purchasing and playing system and method

The similarity between two data objects of the same type (e.g., two resumes, two job descriptions, etc.) is determined using predictive modeling. A basic assumption is that training datasets are available containing compatibility measures between objects of the first type and data objects of a second type, but that training datasets measuring similarity between objects of the first type are not. A first predictive model is trained to assess compatibility between data objects of a first type and data objects of a second type. Then, in one scenario, pairs of objects of the first type are compared for similarity by running them through the first predictive model as if one object of the pair is an object of the first type and the other object of the pair is an object of the second type. Alternatively, for each object in a set of objects of the first type, the first predictive model is used to create a respective vector of compatibility scores against a fixed set of objects of the second type; these various vectors are then used to derive measures of similarity between pairs of objects of the first type, from which a second predictive model is trained, and the second predictive model is then used to assess the similarity of pairs of objects of the first type.

Application-specific method and apparatus for assessing similarity between two data objects

A method and apparatus is disclosed for making predictions about entities represented in documents and for information analysis of text documents or the like, from a large number of such documents. Predictive models are executed responsive to variables derived from canonical documents to determine documents containing desired attributes or characteristics. The canonical documents are derived from standardized documents, which, in turn, are derived from original documents.

Method and apparatus for making predictions about entities represented in documents

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San Diego, CA, United States of America

Mark Alan Laffoon