Google Inc.

Xerox Corporation

Palo Alto Research Center Inc.

Ioannis Tsochantaridis

Massimiliano Ciaramita

Francine R Chen

Steven D Baker

Srinivasan Venkatachary

Thorsten Brants

Thomas Hofmann

Hadar Shemtov

Yi Liu

Per Bjornsson

Robert Andrew Brennan

Enrique Alfonseca

Ekaterina Filippova

Jean-Yves Delort

Yasemin Altun

Evangelos Kanoulas

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for scoring candidate answer passages. In one aspect, a method includes receiving a query determined to be a question query that seeks an answer response and data identifying resources determined to be responsive to the query; for a subset of the resources: receiving candidate answer passages; determining, for each candidate answer passage, a query term match score that is a measure of similarity of the query terms to the candidate answer passage; determining, for each candidate answer passage, an answer term match score that is a measure of similarity of answer terms to the candidate answer passage; determining, for each candidate answer passage, a query dependent score based on the query term match score and the answer term match score; and generating an answer score that is a based on the query dependent score.

Scoring candidate answer passages

News documents from one or more sources are aggregated. The news documents are grouped into a plurality of news collections. Each of the news collections includes a sub-set of the news documents having related content. Objects described by the news collections are determined. The objects collectively form a set of objects. A relevance of each of the news collections is measured with respect to the objects respectively described by the news collections and one or more news collections are determined from the plurality of news collections to be associated with a first object included in the set of objects based on the relevance of the one or more news collections to the first object.

Relevance determination and summary generation for news objects

One aspect of the invention is that of efficiently and incrementally adding new terms to an already trained probabilistic latent semantic analysis (PLSA) model.

Methods, apparatus, and program products for performing incremental probabilistic latent semantic analysis

Systems and methods for determining the topic structure of a document including text utilize a Probabilistic Latent Semantic Analysis (PLSA) model and select segmentation points based on similarity values between pairs of adjacent text blocks. PLSA forms a framework for both text segmentation and topic identification. The use of PLSA provides an improved representation for the sparse information in a text block, such as a sentence or a sequence of sentences. Topic characterization of each text segment is derived from PLSA parameters that relate words to 'topics', latent variables in the PLSA model, and 'topics' to text segments. A system executing the method exhibits significant performance improvement. Once determined, the topic structure of a document may be employed for document retrieval and/or document summarization.

Systems and methods for determining the topic structure of a portion of text

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Zurich, Switzerland

Ioannis Tsochantaridis