Online comment automatic reply method based on deep semantic matching

Abstract

The invention discloses an online comment automatic reply method based on deep semantic matching, which is used for finding out online comments closest to input comment semantics in a database by combining sentence vector cosine similarity and multi-dimensional emotion matching degree. The method specifically comprises the steps that feature words of different topics are obtained through Canopy +Kmeans clustering, and on this basis, topic feature word expansion is conducted through a topic model CorEx based on priori knowledge. Meanwhile, a BERT-BiLSTM emotion analysis model is constructed, and multi-dimensional emotion analysis is carried out on online comments according to theme feature words obtained through clustering and by means of dependency syntactic analysis. Online comments arematched with the most similar semantics in the database by combining sentence vector cosine similarity and a multi-dimensional sentiment analysis result, data enhancement EDA operation is performed onmerchant replies of the comments, and sentences with the highest sentence vector cosine similarity are selected as automatic reply contents. According to the invention, automatic reply online comments can be provided for merchants conveniently, efficiently and accurately.

Description

technical field [0001] The invention belongs to the technical field of computer software and relates to an automatic reply method for online comments based on deep semantic matching, which can effectively improve the management reputation and user experience of merchants in e-commerce platforms. Background technique [0002] With the popularization of the Internet and the vigorous promotion of e-commerce, more and more consumers choose to shop online, which also attracts more merchants to start selling goods online. In the online shopping transaction process, consumers and merchants have information asymmetry and the transaction process is not synchronized. Compared with offline shopping, this online shopping process will make consumers feel higher risks, such as product quality, delivery security etc. Therefore, consumers tend to collect more detailed information about merchants and commodities in various ways. Among them, online reviews of commodities and replies from me...

AI Technical Summary

Problems solved by technology

In the process of online shopping transactions, there is information asymmetry between consumers and merchants and the transaction process is not synchronized. Compared with offline shopping, this online shopping process will make consumers feel higher risks, such as product quality, delivery security etc.

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