Comparative Analysis of Collaborative Filtering Technique

نویسندگان

  • Urmila Shinde
  • Rajashree Shedge
چکیده

Today it is almost impossible to retrieve information with a keyword search when the information is spread over several pages. The Semantic Web is an extension of the current web in which information is given well-defined meaning. Web personalization is the one application of semantic web usage mining. In this report we have explored comparison of various collaborative filtering techniques. Those techniques are memory based, model based and hybrid collaborative filtering. Our study shows that the performance of hybrid collaborative filtering technique is better than memory based and model based collaborative filtering technique. We have introduced normalization step, which will improve accuracy of traditional collaborative filtering techniques.

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تاریخ انتشار 2013