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:
Dec. 22, 2015

Filed:

Jul. 29, 2011
Applicants:

Donghui Feng, Fremont, CA (US);

Kirk Boydston, Amsterdam, NL;

Nathaniel A. Murray, Valencia, CA (US);

Clarke Retzer, Van Nuys, CA (US);

James G. Shanahan, San Francisco, CA (US);

Remi Zajac, Pasadena, CA (US);

Inventors:

Donghui Feng, Fremont, CA (US);

Kirk Boydston, Amsterdam, NL;

Nathaniel A. Murray, Valencia, CA (US);

Clarke Retzer, Van Nuys, CA (US);

James G. Shanahan, San Francisco, CA (US);

Remi Zajac, Pasadena, CA (US);

Assignee:

YELLOWPAGES.COM LLC, Tucker, GA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06F 7/00 (2006.01); G06F 17/30 (2006.01);
U.S. Cl.
CPC ...
G06F 17/30401 (2013.01); G06F 17/3087 (2013.01);
Abstract

A system and method is provided which may comprise parsing an unstructured geographic web-search query into a field-based format, by utilizing conditional random fields, learned by semi-supervised automated learning, to parse structured information from the unstructured geographic web-search query. The system and method may also comprise establishing semi-supervised conditional random fields utilizing one of a rule-based finite state machine model and a statistics-based conditional random field model. Systematic geographic parsing may be used with the one of the rule-based finite state machine model and the statistics-based conditional random field model. Parsing an unstructured local geographical web-based query in local domain may be done by applying a learned model parser to the query, using at least one class-based query log from a form-based query system. The learned model parser may comprise at least one class-level n-gram language model-based feature harvested from a structured query log.


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