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:
Jul. 19, 2011

Filed:

Nov. 16, 2009
Applicants:

Peter Jackson, Burnsville, MN (US);

Khalid Al-kofahi, Rochester, NY (US);

Inventors:

Peter Jackson, Burnsville, MN (US);

Khalid Al-Kofahi, Rochester, NY (US);

Assignee:

West Services, Inc., Eagan, MN (US);

Attorneys:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06F 7/00 (2006.01); G06F 17/00 (2006.01);
U.S. Cl.
CPC ...
Abstract

The American legal system, judges and lawyers are continually researching an ever-expanding body of past judicial opinions, or case law, for the ones most relevant to resolution of new disputes. To facilitate these searches, some companies collect and publish the judicial opinions of courts across the United States in both paper and electronic forms, with some of the cases containing references to prior cases from other courts that have previously ruled on all or part of the same dispute. Identifying the prior cases is problematic, because, for example, conventional computer text-matching not only suggests too many non-prior cases, but also misses too many actual prior cases. Accordingly, the present inventors devised systems, methods, and software that generally facilitate identification of one or more documents that are related to a given document, and particularly facilitate identification of prior cases for a given case. One specific embodiment retrieves prior-case candidates based on information extracted from an input case, and then uses a support vector machine to determine which of the prior-case candidates are most probably prior cases for the input case.


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