Commodity evaluation sentiment analysis system based on attributive characteristics

Abstract

The invention relates to the technical field of big data, and discloses a commodity evaluation sentiment analysis system based on attribute characteristics. The system is used for obtaining sentimenttendencies of consumers for specific commodities and different attributes of the commodities so as to facilitate purchase evaluation and provide reference for subsequent product research and development and sales. The system comprises a user interaction module used for authenticating the identity of a user and receiving the website of a target commodity input by the user; an evaluation statement acquisition module used for capturing consumer evaluation data; a data preprocessing module used for preprocessing the data; an extraction module used for extracting attribute features and attribute weights of the commodities from the preprocessed data to obtain attribute feature-sentiment word pairs; an algorithm processing module used for inputting the extracted attribute feature-sentiment word pairs into an algorithm model for calculation and analysis, realizing an attribute feature-based sentiment analysis algorithm and outputting a commodity evaluation sentiment quantized value; and a result display module used for displaying the analysis result. The system is suitable for commodity evaluation sentiment analysis.

Description

technical field [0001] The invention relates to the technical field of big data, in particular to a commodity evaluation emotion analysis system based on attribute characteristics. Background technique [0002] Commodity evaluation is the subjective feeling of consumers when using commodities, and can express consumers' emotional tendencies. Compared with the merchant's own commodity information, the range of consumer groups' experience is wider and the number of people who experience it is larger. Due to the rise of e-commerce, consumers can buy their favorite products without leaving home. The popularity of Web2.0 has made it a habit for consumers to post product reviews on the Internet after purchasing products. On the basis of the explosive growth of text content, the research on the sentiment analysis of evaluation text based on Natural Language Processing (Natural Language Processing, NLP) technology came into being. [0003] In the face of increasingly complex text d...

AI Technical Summary

Problems solved by technology

[0004] (1) The acquisition, processing and analysis processes are independent of each other, and the integration of the whole stage has not been realized;

[0005] (2) The source platform of the data set is single, and the workload of obtaining data is heavy and repetitive;

[0006] (3) The results of sentiment analysis often lack unified quantitative standards, and users need to further process the analysis results by themselves to obtain data results and statistical charts that can be compared;

[0007] (4) In the existing online evaluation emotion research, scholars often regard online reviews as atomic objects, and the research on evaluation emotion stays at the level of a single product, and lacks finer-grained evaluation emotions for different attributes of the same product consideration

For a small amount of sentiment research based on commodity attributes, attributes and attribute weights are often set artificially, which makes it difficult to guarantee the objective and fair evaluation results

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