Research on Knowledge-based Personalized Recommendation Service System Retrieval Service
This article studies the personalized modeling techniques, presents a personalized client-based model and the users access history page as mining object without the involvement of too many users. Automatic feedback is from the user who derived implicit in users interest. This paper focuses on the user interest mining-related technology to the users visitation page content as interest in the historical sources of information modeling, which are the uses structural features of HTML page content to extract the important part of the sub-string matching that is based on words and the statistical method of combining segmentation. The word content of the page segmentation is used to express the thematic content of the page, and then it removes the segmentation results to stop words, use this theme in the page vector space model and represent the characteristics of words. With word frequency, position, and the weighted combination of the nonlinear function, it calculates the weights.
personalization information retrieval data mining
Xuanchun Liu Jiancun Zhou
hunan city University vivang, China
国际会议
成都
英文
246-249
2011-01-14（万方平台首次上网日期，不代表论文的发表时间）