The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Oct. 27, 2009

Filed:

Oct. 15, 2003
Applicants:

Livia Polanyi, Palo Alto, CA (US);

Martin H. Van Den Berg, Palo Alto, CA (US);

Giovanni Lorenzo Thione, San Francisco, CA (US);

Richard S. Crouch, Cupertino, CA (US);

Christopher D. Culy, Mountain View, CA (US);

David D. Ahn, Palo Alto, CA (US);

Inventors:

Livia Polanyi, Palo Alto, CA (US);

Martin H. Van Den Berg, Palo Alto, CA (US);

Giovanni Lorenzo Thione, San Francisco, CA (US);

Richard S. Crouch, Cupertino, CA (US);

Christopher D. Culy, Mountain View, CA (US);

David D. Ahn, Palo Alto, CA (US);

Assignee:
Attorneys:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06F 17/27 (2006.01);
U.S. Cl.
CPC ...
Abstract

Techniques are provided for segmenting text into categorized discourse constituents and attaching discourse constituents into a structural representation of discourse. Techniques for determining hybrid structural and non-structural summaries of a text are also provided. A text is segmented based on a theory of discourse analysis into at least a main discourse constituent containing spatio-temporal information about a single event in a possible world view. The discourse constituents are then inserted into a structural representation of discourse. Non-structural techniques are used to determine relevance scores and important discourse constituents are determined. Relevance scores are percolated through the structural representation of discourse to determine supporting preceding discourse constituents that preserve grammaticality. A hybrid text summary is then determined based on the structural representation of the discourse and relevance scores.


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