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:
Jun. 09, 2020

Filed:

Dec. 20, 2017
Applicant:

International Business Machines Corporation, Armonk, NY (US);

Inventors:

Jinfeng Yi, Ossining, NY (US);

Jun Wang, White Plains, NY (US);

Kush Varshney, Ossining, NY (US);

Aleksandra Mojsilovic, New York, NY (US);

Attorneys:
Primary Examiner:
Int. Cl.
CPC ...
G06F 16/2457 (2019.01); G06Q 30/06 (2012.01); G06F 17/16 (2006.01); G06F 17/18 (2006.01); G06F 16/9535 (2019.01);
U.S. Cl.
CPC ...
G06F 16/24578 (2019.01); G06F 16/9535 (2019.01); G06F 17/16 (2013.01); G06F 17/18 (2013.01); G06Q 30/0631 (2013.01);
Abstract

Methods and systems for generating prediction data are described. In an example, a processor may retrieve preferential data from a memory. The preferential data may include a set of preferences that corresponds to a first subset of objects among a set of objects, and may exclude preferences associated with a second subset of objects among the set of objects. Each preference may indicate a preferred object between a respective pair of objects among the first subset of objects. The processor may determine first predicted ratings corresponding to the first subset of objects based on the preferential data. The processor may determine second predicted ratings corresponding to the second subset of objects based on the preferential data. The processor may generate prediction data by populating entries of the prediction data with the first and second predicted ratings, where the prediction data may include predicted ratings of the set of objects.


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