Personalized Recommendation based on WAR
Personalized recommendation is the process of customizing Web site to meet the requirement of specific user by analyzing users browsing behavior and extracting knowledge based on Web logs. Association rules mining technology is widely adopted in this field. However, the resulting association patterns can not effectively predict users future browsing behavior because of the low similarity degree between resulting rules and users browsing behavior. In this paper, we assign a weight to each item in a transaction to reflect the interest degree, which extends the traditional association rule method. We also proposed weighted association rule (WAR) through associating a weight with each item in resulting association rules. Each Web page is assigned to a weight according to interest degree and three key factors, I.e. visit frequency, stay duration and operation time. A novel personalized recommendation mechanism is presented based our proposed WAR. The weighted measurement in our personalized recommendation can be used to determine the importance of Web pages for user. We try to acquire users requirement more precisely so as to more useful Web pages are discovered and recommended for user.
personalizd recommendation weighted association rule (WAR) data mining web personalization
Zhang Junyan Shao Peiji
School of Economics and Management University of Electronic Science and Technology of China Chengdu, China
国际会议
太原
英文
108-111
2010-10-22（万方平台首次上网日期，不代表论文的发表时间）