Big data based e-commerce company evaluating, analyzing and predicting method and system for online shopping

Abstract

The invention discloses a big data based e-commerce company evaluating, analyzing and predicting method and a system for online shopping, or more particularly, a big data acquiring, analyzing, and predicting method and a system which convert unstructured texts including evaluating contents into structured data by combining a control and exchange center deployed on Spark to a plurality of exchange proxies. The invention is performed on the basis of big data and utilizes a data mining algorithm of big data to effectively treat all information. The method and the system of the invention can be applied for online shopping by providing accurate evaluation and analysis so that a user can conveniently make judgments about whether the comments are true or false and whether their online shopping is worthwhile or not before he or she finally decides to purchase a product from an e-commerce company.

Description

technical field [0001] The present invention relates to the field of big data technology, in particular to a big data e-commerce online shopping evaluation analysis and prediction method and system. technical background [0002] With the advent of big data, data is gradually realized to be of great use. A large amount of data is extracted and analyzed to classify useful data, and the target is judged by analyzing useful data. When shopping online, perhaps the comments buyers see are written by the sellers themselves. Computers can be used to automatically process network information. At present, the main research object of opinion mining is the massive text information on the Internet. In recent years, the development of machine learning has brought new hope for opinion mining. Opinion mining is becoming increasingly intelligent. However, the above techniques can only roughly judge the authenticity of the collected data, but the collected data may have a certain degree of...

AI Technical Summary

Problems solved by technology

When shopping online, the reviews that buyers see may be created by sellers themselves, and false reviews will affect users' judgment;

[0007] The third is that merchants cannot accurately meet the needs of users, and the product information provided to users is not accurate and detailed enough.

[0008] In view of the above problems, the existing intelligent online shopping evaluation analysis and prediction system and online shopping evaluation analysis and prediction method also try to solve it, but the result is that most of them temporarily solve the problem that merchants provide users with accurate product information without too much consideration of false information. Evaluation and user's own factors

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