Improving Multi-class Co-Clustering-Based Collaborative Recommendation Using Item Tags
نویسندگان
چکیده
منابع مشابه
Recommendation of (IP)TV Programs based on Collaborative Filtering using n-tuple Item Clustering
With the advent of multi-channel TV services, a prohibited amount of IPTV program contents becomes available to user’s sides. Furthermore, the number of IPTV service providers is rapidly increasing over internets. Therefore such information overload requires large amounts of efforts for users to search and navigate the program contents that they like to watch. In this paper, we incorporate coll...
متن کاملUserrank for item-based collaborative filtering recommendation
Article history: Received 23 February 2010 Received in revised form 7 February 2011 Accepted 7 February 2011 Available online 15 February 2011 Communicated by J. Chomicki
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Recommender systems utilize information retrieval and machine learning techniques for filtering information and can predict whether a user would like an unseen item. User similarity measurement plays an important role in collaborative filtering based recommender systems. In order to improve accuracy of traditional user based collaborative filtering techniques under new user cold-start problem a...
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Personalized recommendation systems can help people to find interesting things and they are widely used with the development of electronic commerce. Many recommendation systems employ the collaborative filtering technology, which has been proved to be one of the most successful techniques in recommender systems in recent years. With the gradual increase of customers and products in electronic c...
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Recommendations that are personalized help the users in getting the list of items that are of their interest in e-commerce sites. Majority of recommender systems use Collaborative Filtering techniques to generate recommendations to their users. This project implements an information filtering technique called as Collaborative Filtering for generating personalized recommendations in movies for u...
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ژورنال
عنوان ژورنال: Revue d'Intelligence Artificielle
سال: 2020
ISSN: 0992-499X,1958-5748
DOI: 10.18280/ria.340108