Collaboration Filtering using K-Mean Algorithm
نویسنده
چکیده
Recommender systems apply data analysis techniques to the problem of helping users find the items they would like to purchase at E-Commerce sites by producing a predicted likeliness score or a list of top-N recommended items for a given user. We apply Clustering algorithms for finding nearest similar item. To finding nearest item for this we use C++ language. We apply improved K-mean algorithms method on preprocessed data. Finally we proposed a method that can increase accuracy based on previous K-mean algorithms.
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