Shahrzad Motamedi Mehr

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Recommendation systems aim at directing users toward the resources that best meet their needs and interests. In this paper, we propose a new recommendation algorithm based on a hybrid method of distributed learning automata and graph partitioning. The proposed method utilizes usage data and hyperlink graph of the web site. The idea of the proposed method is(More)
Determining similarity between web pages is a key factor for the success of many web mining applications such as recommendation systems and adaptive web sites. In this paper, we propose a new hybrid method of distributed learning automata and graph partitioning to determine similarity between web pages using the web usage data. The idea of the proposed(More)
Recommendation systems aim at directing users toward the resources that best meet their needs and interests. One of the challenging tasks in improving web recommendation algorithms is the simultaneous use of users's activity log and hyperlink graph of the web site. In this paper, we propose a new recommendation algorithm based on web usage data and(More)
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