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:
Feb. 07, 2023

Filed:

Sep. 15, 2017
Applicant:

Oracle International Corporation, Redwood Shores CA, CA (US);

Inventors:

Michael Edward Pearmain, Guildford, GB;

Janet Barbara Barnes, Yalding, GB;

David John Dewsnip, Hampshire, GB;

Zengguang Wang, Foster City, CA (US);

Assignee:

Oracle International Corporation, Redwood Shores, CA (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 5/02 (2006.01); G06N 7/00 (2006.01); G06K 9/62 (2022.01); G06N 20/00 (2019.01); G06F 16/33 (2019.01); G06F 16/9535 (2019.01);
U.S. Cl.
CPC ...
G06N 5/025 (2013.01); G06F 16/3334 (2019.01); G06F 16/9535 (2019.01); G06K 9/6269 (2013.01); G06N 7/005 (2013.01); G06N 20/00 (2019.01);
Abstract

Techniques are described for training and evaluating a proximal factorization machine engine. In one or more embodiments, the engine receives a set of training data that identifies a set of actions taken by a plurality of users with respect to a plurality of items. The engine generates, for a prediction model, (a) a first set of model parameters representing relationships between features of the plurality of users and the set of actions, and (b) a second set of model parameters representing interactions between different features of the plurality of users and the plurality of items. For each respective item in a plurality of items, the engine computes a probabilistic score based on the model parameters. The engine selects and presents a subset of items based on the probabilistic scores.


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