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. 18, 2024

Filed:

Aug. 24, 2023
Applicant:

Qilu University of Technology (Shandong Academy of Sciences), Jinan, CN;

Inventors:

Dongfeng Li, Jinan, CN;

Peng Ji, Jinan, CN;

Wanlong Dong, Jinan, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06F 40/30 (2020.01); G06F 40/56 (2020.01);
U.S. Cl.
CPC ...
G06F 40/56 (2020.01); G06F 40/30 (2020.01);
Abstract

Disclosed is a multi-turn human-machine conversation method and apparatus based on a time-sequence feature screening encoding module, belonging to the technical field of natural language processing and artificial intelligence. The technical problem to be solved by the disclosure is how to screen information for each utterance in a historical conversation so as to obtain semantic information only relevant to candidate responses and how to reserve and extract time-sequence features in the historical conversation, thus improving prediction accuracy of a multi-turn human-machine conversation system. The adopted technical scheme is as follows: S1, acquiring a multi-turn human-machine conversation data set; S2, constructing a multi-turn human-machine conversation model: constructing a multi-turn human-machine conversation model based on the time-sequence feature screening encoding module; and S3, training the multi-turn human-machine conversation model: training the multi-turn human-machine conversation model constructed in S2 on the multi-turn human-machine conversation data set obtained in S1.


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