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Semantic similarity calculation method based on FSM multi-round questions and answers

A technology of semantic similarity and calculation method, applied in the field of semantic similarity calculation based on FSM multi-round question answering, can solve the problems of insufficient number of people at low valleys, insufficient number of people in service peaks, consumption of large human resources, etc., and achieve the effect of improving efficiency.

Pending Publication Date: 2020-04-21
ZHONGBO INFORMATION TECH RES INST CO LTD
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Problems solved by technology

Due to the fact that the traditional manual customer service system often consumes a lot of human resources in the face of insufficient service peaks and low valleys.

Method used

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  • Semantic similarity calculation method based on FSM multi-round questions and answers
  • Semantic similarity calculation method based on FSM multi-round questions and answers
  • Semantic similarity calculation method based on FSM multi-round questions and answers

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Embodiment Construction

[0013] Depend on figure 1 It can be seen that the whole system is mainly divided into question analysis module, question retrieval module, question matching module, scoring module, SimNet module, and FAQ data set storage module. The functions and interactions of each module are as follows:

[0014] (1) Question analysis module: According to the question input by the user, judge the scene of the question (field-related, encyclopedic knowledge, chatting), call the question-answer pair data in the knowledge base according to the corresponding question scene, and use each of the input questions A character is converted into an index of the character in the dictionary, which is used to obtain the word vector stored by BERT pre-training.

[0015] (2) Question retrieval module: According to the converted user questions and the question-answer pair data extracted from the knowledge base, the first round of semantic similarity calculation is performed, and the retrieved answers are re...

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Abstract

The invention discloses a semantic similarity calculation method based on FSM multi-round questions and answers. According to the semantic similarity calculation method based on FSM multi-round questions and answers, according to user input questions, the user input questions and knowledge base question and answer pair data into a Transformer DSSM semantic similarity calculation model to carry outmultiple rounds of matching, and a candidate answer is returned t the user; the problem that a traditional customer service system often consumes a large number of human resources under the conditions of insufficient service peak people and insufficient valley people is solved, and the efficiency of obtaining answers of common questions in related fields by the user is improved.

Description

technical field [0001] The invention relates to a method for improving the matching speed and precision of question-answer pairs in a telecommunication intelligent customer service system—a semantic similarity calculation method based on FSM multi-round question-answer. Background technique [0002] Natural language processing is an important direction in the field of computer science and artificial intelligence. It studies various theories and methods that can realize effective communication between humans and computers using natural language. are fields of computer science, artificial intelligence, and linguistics concerned with the interaction between computers and human (natural) language. Because the traditional manual customer service system often consumes a lot of human resources in the face of insufficient service peaks and low valleys. Therefore, the application of natural language processing in the intelligent customer service question answering system, on the on...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/332G06F16/33G06K9/62G06F40/126
CPCG06F16/3329G06F16/3344G06F18/22
Inventor 王黎成高阳
Owner ZHONGBO INFORMATION TECH RES INST CO LTD
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