Research And Implementation On User-Oriented Information Filtering

Up to now, the World Wide Web (WWW) grows into a large hyperlinked corpus with more than 800 million pages and 5600 million hyperlinks, The web contains a rich and dynamic collection of hyperlink information and Web page access and usage information, providing rich sources for us. However, the information in Internet is disorder, it's a real challenge for us to make Internet easier to use. Traditional information retrieval technologies satisfy users's general needs-common characteristics, the current Search Engine cannot satisfy users' specific need.Because everybody has specific need which is relative unchanged but will be changed over time slowly, the personalized information service will play an more and more important role based on the user's interest in the Internet.Based on the user's specific information service, we hope implement that can obtain information in Internet accurately. We filter the information (which come from the Google, baidu Search Engine) based on the user's profiles, then submit the filtered result to the user, then updated the user's profiles dynamically based on the user's feedback.The main research works are:(1)Implementing a prototype system for personalized information filtering;(2)Making use of maximum probabilistic method to segment the Chinese documents;(3)Giving a scheme to represent the user's interest categories, every user's interest categories is a n-tuple: C=(C1,C2....Cn), each C1 represents the user's a interest category,Ci=(Ip, In,Iq),Ip ={(t1, w1 ),...... ,(tn,wn)} captures the user's positive profile, we call it attract factor, In= {(t1,w1 ),.....,(tn, wn)}captures the user's negative profile, we call it reject factor, Iq= {(t1 ,w1 ),....,(tk, wk )} captures the user's query keyword, wecall it query;(4)Based on Vector Space Model filtering the web document according to adaptive user model.(5)Modifying the user's profiles based on the user relevance feedback information.This paper describes a scheme to represent a user's interest categories and updates the user's profiles according to the user's relevance feedback and implements a prototype System.