Comment analysis method based on word vectors and syntactic features and visual interactive interface

Abstract

The invention provides a comment analysis method based on word vectors and syntactic characteristics in the field of data analysis. The comment analysis method comprises the steps of obtaining commodity page comment data of an e-commerce website; preprocessing the acquired target data set; extracting a appendix lexical set provided by Hownet and NTU to form a basic emotion dictionary; carrying outword vector training on the obtained preprocessed data set through a Word2Vec tool; establishing a probability transfer matrix by using the semantic similarity matrix; carrying out core sentence rule-based processing on the obtained commodity comment text; carrying out preprocessing on the obtained text without the redundancy; performing part-of-speech extraction (commodity attributes, negative words, degree words and sentiment words) evaluation matching on the obtained dependency relationship pairs; combining the evaluation matching pair with an emotion dictionary, subjecting evaluation objects to appraisal value calculation and quality sorting, and finally, realizing the evaluation objects through a visual interaction interface, so that accurate, real-time, automatic and convenient processing and analysis on commodity comment data are realized, and the method can be used in an e-commerce platform.

Description

Technical field [0001] The invention belongs to the technical field of data analysis, and in particular relates to a sentiment dictionary, an attribute recognition algorithm and a comment analysis system based on word vectors and syntactic features constructed using word vectors trained by a neural network model and suitable for commodity reviews. Background technique [0002] With the popularity of the Internet and the development of e-commerce, Internet e-commerce sites such as JD.com and Taobao have developed rapidly, and more and more consumers have begun to choose online shopping; these e-commerce sites have a large number of products and a large user base. , Resulting in huge review data. The reviews given by consumers often carry the user's subjective feelings about the consumption, including the degree of preference for the purchased goods, and the degree of satisfaction with the merchant's services. For consumers, these review texts can help them to more objectively und...

AI Technical Summary

Problems solved by technology

However, with the explosive growth of data volume, the cost for users to obtain useful information from massive comment data is also increasing. Therefore, how to process and analyze user comment text quickly and effectively, and extract Produce valuable information, which has important application value and research significance

[0003] At present, a large amount of review data cannot be fully utilized, and it is difficult for consumers to obtain valuable information from massive review data

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