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. 08, 2013

Filed:

Jul. 06, 2009
Applicants:

Frank Naeymi-rad, Libertyville, IL (US);

Regis Charlot, Lake Bluff, IL (US);

David Haines, Arlington Heights, IL (US);

Matthew C Cardwell, Geneva, IL (US);

Michael Decaro, St. Charles, IL (US);

Inventors:

Frank Naeymi-Rad, Libertyville, IL (US);

Regis Charlot, Lake Bluff, IL (US);

David Haines, Arlington Heights, IL (US);

Matthew C Cardwell, Geneva, IL (US);

Michael Decaro, St. Charles, IL (US);

Assignee:

Intelligent Medical Objects, Inc., Northbrook, IL (US);

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

A system and process for record duplication analysis that relies on a multi-membership Bayesian analysis to determine the probability that records within a data set are matches. The Bayesian calculation may rely on objective data describing the data set as well as subjective assessments of the data set. In addition, a system and process for record duplication analysis may rely on the predetermination of probabilistic patterns, where the system only searches for patterns exceeding a chosen threshold. Work flow may include selecting which fields within each record should be analyzed, normalizing the values within those fields and removing default data, calculating possible patterns and their match probabilities, analyzing record pairs to determine which have patterns exceeding a chosen threshold to determine the presence of duplicates, and merging duplicates, closing transactions reflecting non-duplicates, identifying records having insufficient data to determine the existence or lack of a match, and/or rolling back accidental merges.


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