The Study, Based On User Interest In Network Information Filtering Model

With the development of Internet and Web technology, Internet has been a gigantic space of information exchange. Facing the gigantic information, People often lose their direction when they look for their requisite information. How quickly searching for their requisite information from gigantic information resource has been a difficult problem of perplexing the user. Given the high rate of the volume of data available on the Internet, finding useful information in such a large amount of data becomes a more difficult process every day. Therefore how to provide the personal information to people is becoming the important problem that researchers care for. Text filtering is of great value and used widely with the increasing text information because it can help users get information which they are interested in and realize personalized information service.There are three kinds of text filtering: content-based filtering, collaborative filtering and value filtering. Content-based filtering mainly adopts some technologies such as natural language processing, artificial intelligence and probability statistic to analyze text content, then calculate degree of similarity between content vector and user profiles vector and select high correlative text to registered users. Collaborative filtering mainly makes use of users' opinions that have similar interest to predict and recommend. Now it has been used in personalized recommendation system. But with the system scale enlarging, its efficiency gradually declines and some problems such as sparse matrix, scalability and early rater will appear. Value filtering may be formalized as a decision rule: select a message if and only if the cost of selecting a message for examination is lower than the cost of rejecting a message–that is, choosing not to examine a message.In this paper, the research background and current situation of the network information filtering has been analyzed, point out the keys of information filtering based on the user interest ,that is user interest profile ,the upgrade of user interest ,and the union of content-based filtering , collaborative filtering and value filtering.Based on previous research, the major research works and initiative points in this article are:First, analyses the research background and current situation of the network information filtering, points out the key of research that is the establishment, upgrade and the union of content-based filtering, collaborative filtering and value.Second, the key techniques in content-based information filtering are particularly discussed, that is how to segment Chinese words, how to extract suitable features from documents, and how to classify.Third, in view of information filtering based on the user interest, proposes one kind of new user interest profile, the upgrade method, which enables the user profile to be proper to both user's long-term interest and the short-term interest.Fourth, the paper suggests the method of Interest degree of user. The method is based on user viewed content and combining with analysis of user's behavior. It can adapt the changes of user interests quickly, and present the user interest degree to the information.Finally, through analyzing the union necessity of content-based, collaborative filtering and value filtering, proposes an information system based on three kinds of information methods. This model may enhance strong points and avoid weaknesses, and may enhance the accuracy of the information.