Research on Knowledge-based Personalized Recommendation Service System Retrieval Service

摘要

This article studies the personalized modeling techniques, presents a personalized client-based model and the user's access history page as mining object without the involvement of too many users. Automatic feedback is from the user who derived implicit in user's interest. This paper focuses on the user interest mining-related technology to the user's visitation page content as interest in the historical sources of information modeling, which are the use's 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.