Applying Web Usage Mining Techniques to Design Effective Web Recommendation Systems: A Case Study
Publish Year: 1392
نوع سند: مقاله ژورنالی
زبان: English
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شناسه ملی سند علمی:
JR_ACSIJ-3-2_011
تاریخ نمایه سازی: 24 فروردین 1393
Abstract:
Recommender systems are helpful tools which provide an adaptive Web environment for Web users. Recently, a number of Web page recommender systems have been developed to extract the user behavior from the user’s navigational path and predict the next request as he/she visits Web pages. Web Usage Mining(WUM) is a kind of data mining method that can be used to discover this behavior of user and his/her access patterns fromWeb log data. This paper first presents an overview of the used concepts and techniques of WUM to design Web recommender systems. Then it is shown that how WUM can be applied to Web server logs for discovering access patterns. Afterward, we analyze some of the problems and challenges in deploying recommender systems. Finally, we propose the solutions which address these problems.
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Authors
Maryam Jafari
Department of Computer, Novin Higher Education Institute Ardabil, Iran
Farzad Soleymani Sabzchi
Department of Computer, Novin Higher Education Institute Ardabil, Iran
Amir Jalili Irani
Sama technical and vocational training college, Islamic Azad University, Ardebil branch Ardebil, Iran