Improving Results and Performance of Collaborative Filtering-Based Recommender Systems Using Cuckoo Optimization Algorithm

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Provided by: International Journal of Computer Applications
Topic: Data Management
Format: PDF
An approach for improving quality and performance of collaborative filtering-based recommender systems is proposed in this paper. A slight change on similarity metric is proposed. To obtain more accurate similarity measurement between two users, similarity measurement method needs a well-chosen weight vector. Different weight vectors could be employed based on the recommender system and the taste of users, but only some of them are suitable. To obtain the best results the authors have to find the most suitable weight vector among all possible ones.
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