A FAQ matching method and system integrating multi-algorithm models

Abstract

The present invention provides a method and system for FAQ question-and-answer matching that integrates multi-algorithm models. The method includes: constructing an inverted index based on a FAQ knowledge base; acquiring user questions, preprocessing to obtain a first preprocessing result, Search the knowledge base questions associated with the user questions; train the sentence encoder, use the sentence encoder to encode the user questions and the knowledge base questions into sentence vectors, and calculate the cosine value between the two sentence vectors, that is, the similarity; The question and the knowledge base question are preprocessed to obtain the second preprocessing result; the matching algorithm is used to calculate the matching degree of the second preprocessing result of the user question and the knowledge base question; the weighted average calculation is carried out combining the similarity and the matching degree to obtain the final similarity degree value; according to the final similarity value and the set threshold, give the answer. The present invention achieves the overall optimal matching effect by embedding algorithm logic models based on different rules, and has high overall question-and-answer accuracy and good effect.

Description

technical field [0001] The present invention relates to the technical field of natural language processing, and in particular, to a method and system for FAQ question-and-answer matching that integrates a multi-algorithm model. Background technique [0002] In the intelligent customer service system, the question and answer based on FAQ (frequently-asked questions, referred to as FAQ) is the basic ability of the system, and the accuracy of the FAQ question and answer is a very important indicator to measure the advanced nature of the system. Based on the characteristics of different industries and different business priorities of customers, the maintenance level of the FAQ database is different. [0003] At present, FAQ matching is generally carried out by using models or rules, and this matching method has great limitations. (1) Limitations of the model: The model itself needs to be trained well before it can be used. There will be a lag in online business changes. If ther...

AI Technical Summary

Problems solved by technology

(1) Limitations of the model: the model itself needs to be trained well before it can be used, and there will be a lag in online business changes. If there is a badcase online, it will be slow to repair

(2) Limitations of the rules: The rule algorithm will rely too much on basic semantic data, such as similar questions, words and other data. Once these words have problems with maintenance, it will lead to algorithm errors

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