New Hybrid Web Personalization Framework
Web personalized recommender systems based on web mining try to mine users behavior patterns from web access logs and site metadata, and recommend pages to the online user by matching the users browsing behavior with the mined previous users behavior patterns. Recommendation approaches proposed in previous works, however, cannot still satisfy users especially in huge and dynamic web sites. To provide recommendation efficiently, we advance a framework for web mining-based personalization that combines web usage data with web content and site structure for predicting users future requests more accurately. The experimental results on real dataset show that the approach can improve accuracy and coverage of recommendations to users.
web mining personalization weighted rule mining content clustering hybrid recommendation
Samira Khonsha Mohammad Hadi Sadreddini
Department of Computer Islamic Azad University, Zarghan Branch, Young Researchers Club,Zarghan, Iran Electrical and Computer Engineering Department Shiraz University Shiraz, Iran
国际会议
西安
英文
86-92
2011-05-13（万方平台首次上网日期，不代表论文的发表时间）