Research on Personalized Recommendation Based on Web Usage Mining Using Collaborative Filtering Technique

Collaborative filtering is the most successful technology for building personalized recommendation system and is extensively used in many fields. This paper presents a system architecture of personalized recommendation using collaborative filtering based on web usage mining and describes detailedly data preparation process. To improve recommending quantity, a new personalized recommendaton model is proposed in which takes the good consideration of URL related analysis and combines the K-means algorithm. Experimental results show that our proposed model is effective and can enhance the performance of recommendation. Key-Words: Collaborative filtering, Personalized recommendation, Web usage mining, Data preparation, Cluster algorithm, Similarity