A collaborative filtering framework based on both local user similarity and global user similarity
نویسندگان
چکیده
منابع مشابه
Use of Semantic Similarity and Web Usage Mining to Alleviate the Drawbacks of User-Based Collaborative Filtering Recommender Systems
One of the most famous methods for recommendation is user-based Collaborative Filtering (CF). This system compares active user’s items rating with historical rating records of other users to find similar users and recommending items which seems interesting to these similar users and have not been rated by the active user. As a way of computing recommendations, the ultimate goal of the user-ba...
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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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Memory-based collaborative filtering is the most popular approach to build recommender systems. Despite its success in many applications, it still suffers from several major limitations, including data sparsity. Sparse data affect the quality of the user similarity measurement and consequently the quality of the recommender system. In this paper, we propose a novel user similarity measure based...
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Recommender systems could be seen as an application of a data mining process in which data collection, pre-processing, building user profiles and evaluation phases are performed in order to deliver personalised recommendations. Collaborative filtering systems rely on user-to-user similarities using standard similarity measures. The symmetry of most standard similarity measures makes it difficul...
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Recommender systems play an important role in supporting people getting items they like. One type of recommender systems is userbased collaborative filtering. The fundamental assumption of user-based collaborative filtering is that people who share similar preferences for common items behave similar in the future. The similarity of user preferences is computed globally on common rated items suc...
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ژورنال
عنوان ژورنال: Machine Learning
سال: 2008
ISSN: 0885-6125,1573-0565
DOI: 10.1007/s10994-008-5068-4