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. 25, 2020

Filed:

Dec. 25, 2017
Applicant:

Industrial Technology Research Institute, Hsinchu, TW;

Inventors:

Cheng-Liang Lin, Kaohsiung, TW;

Jie-Sin Li, New Taipei, TW;

En-Tzu Wang, Kaohsiung, TW;

Jyun-Tang Huang, Taoyuan, TW;

Tsung-Wen Tso, Hsinchu, TW;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06Q 30/00 (2012.01); G06Q 30/06 (2012.01); G06Q 30/02 (2012.01); G06F 17/18 (2006.01); G06N 5/04 (2006.01); G06F 16/2457 (2019.01);
U.S. Cl.
CPC ...
G06Q 30/0631 (2013.01); G06F 16/24578 (2019.01); G06F 17/18 (2013.01); G06N 5/04 (2013.01); G06Q 30/0201 (2013.01);
Abstract

A decision factors analyzing device and a decision factors analyzing device for analyzing a plurality of decision factors which cause a product of a product type to be purchased are provided. The method includes identifying a plurality of product sequences corresponding to the product type from a plurality of browse history data and a plurality of purchase history data corresponding to a plurality of consumers of a consumer database, wherein each of the product sequences includes a unpurchased product and a purchased product; obtaining a feature sequence according to the produce sequences and a plurality of product information; training a regression model corresponding to the product type according to K decision factors of the feature sequence to obtain an optimized regression model, and obtaining K decision values respectively corresponding to the K decision factors according to the optimized regression model to generate a decision factor sequence corresponding to the product type.


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