Text evaluation data specialization level analyzing method for electronic commerce

Abstract

The invention discloses a text evaluation data specialization level analyzing method for electronic commerce. The text evaluation data specialization level analyzing method for the electronic commerce comprises the following steps of (S1) acquiring concept hierarch trees relevant to evaluation text data of all commodities; (S2) calculating a specialization level value of the evaluation text data on each concept hierarch tree; (S3) synthesizing values of all the concept hierarch trees and calculating specialization level of the evaluation text data; and (S4) dividing the specialization level of the evaluation text data into a plurality of grades to obtain specialization level grades of the evaluation text data of all the commodities and recommending the commodity evaluation text data with high specialization level to users. By the technical scheme, the users can directly and objectively acquire evaluation data, and contents of the evaluation data are quantified and are sorted objectively according to the grades.

Description

technical field [0001] The invention relates to the field of computers, in particular to a method for analyzing the professional degree of text evaluation data used in electronic commerce. It is beneficial for consumers to view evaluation information with more reference value. Background technique [0002] In recent years, the e-commerce industry has developed rapidly, and more and more people tend to shop online. In order to ensure the authenticity of product information and supervise the service of merchants, buyers can evaluate the purchased products. These evaluation data include Simple scoring and text description data. These evaluation data, especially text evaluation data, are important references for other consumers to conduct transactions. Therefore, these evaluation data are of great value to consumers, marketers, manufacturers, and e-commerce platform operators. Due to the huge differences in the consumption experience and evaluation attitude of different consu...

AI Technical Summary

Problems solved by technology

Due to the huge differences in the consumption experience and evaluation attitude of different consumers, the information and value contained in the evaluation data are also quite different.

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