Research On The Approach Of Automatically Identifying Usefulness Of Online Product Reviews Based On Data Mining Technology

With the popularity of the Internet,online shopping has become an important part of people's daily life.By the end of 2017,online shopping users had reached 533 million,accounting for 40% of the total population of China.Based on the great advantages of the Internet in information,consumers can see a large number of evaluation information for the corresponding online goods,and the latter will be an important basis for consumers to buy or not.However,the quality of these comments on the information has shown a greater difference,thus affecting the quality of the consumer information screening.In this paper,the author studies the usefulness of these commodity reviews.Then,on the basis of exploring the influencing factors,the text classification technology is used to realize the automatic recognition.Firstly,the author summarizes the research on the usefulness of the commodity reviews and the research of text classification technology,and obtains the relationship between the comment utility and text classification.Then the method of automatic recognition is found.Then,through the study of the characteristics of online word-of-mouth and its relationship with the comments,the characteristics of these comments are summarized,and the definition and evaluation criteria of the usefulness of the definition are defined.Then reviews the source and review texts based on the perspective of exploring the influential factors,establish the evaluation index and the corresponding measure,so as to construct comment text feature vector basic support.Finally,the automatic recognition is realized successfully.In other words,it is possible to automatically classify all comments based on the needs of consumers.By constructing the text feature vector,and based on the support vector machine algorithm for classification,and then automatically identify useful comments.The research work is of great significance and role in the development of the online shopping users and websites.At the same time,it can promote the website comment system to be perfect in the corresponding degree,and then to provide consumers with better service.