Cyber Times International Journal of Technology & Management

For many years, people have been searching the complete dataset for a particular interest only. The huge amount of data in the dataset makes it very time consuming and tedious job to find exact information. The collaborative filtering with clustering performance used to solve problem. The collaborative filtering with implicit feedback can give better results. Use of a high dimensional divisive hierarchical clustering of categorical data based on the clustering results, creates personalized recommendation of high interest to the user. To avoid the drawback of getting excessive explicit feedback in collaborative filtering and leading to unsatisfactory results, the implicit feedback recommender domain is used. Implicit feedback is becoming an effective technique for recommender systems.