Research And Application On Review Orientation Of Education Resources

The reviews of a product published on the network by users have very significant research value, whether they are for manufacturers or potential consumers. Similarly, the reviews of network education resources published by users are also of great research value, both for providers of education resources and learners. By the review information of resources, the providers who provide education resources can know what needs improvement, and they can absorb the strengths of other education resources to fill their own short; learners can get some references and recommendations by understanding the review information of resources, and they can find suitable education resources through comprehensive consideration and select. Therefore, it has a great deal of significance to research review orientation of education resources.Through forums, BBS, message boards, and Blog, E-learning users can publish reviews about education resources, which are important sources of review information. Sometimes the review information of education resources up to hundreds, it is a time-consuming and inefficient work if only relies on manual browsing. Therefore we need to use the information extraction technology to extract automatically orientation of education resources from users' reviews.It has two key steps to extract orientation of review information: semantic polarity analysis and opinion mining. We need to use computer technology to analyze automatically sentences and documents, which have emotional orientation; and extract topics or features, which users need subconsciously and analyze their semantic orientation and intensity. In terms of semantic polarity analysis of Chinese review information, most methods are based on methods of statistical analysis, and many research institutions have been made valuable progress using natural language processing technology to analyze semantic orientation for review information. The paper will try to use natural language processing technology to analyze semantic orientation of reviews about education resources; so that users can get education resources with high quality which they are interested in.This paper statistically analyzes resource types and media types of education resources, extract features of education resources, and benchmark words used for judging word polarity. When we compute sememe similarity, we analyze deeply relations of upper and lower; and antonym relations among sememes and adopt emotional words published recently by HowNet. By improved benchmark words and the algorithm of word semantic similarity, the calculation results of words' semantic polarity have higher accuracy and confidence in a certain degree. In the process of opinion mining, through lexical analysis results and parsing results of LTP system, we pass opinion's polarity to features using dependency relations, and get sentence orientation finally by algorithm of compute sentence orientation.In the experiment, we compare opinion results extracted automatically with manual judgment results and get high precision and recall rate. We design an application system of review mining about education resources to judge review sentence orientation.