An Item-based Multi-Criteria Collaborative Filtering Algorithm for Personalized Recommender Systems
نویسندگان
چکیده
منابع مشابه
Item-level Turst-based Collaborative Filtering for Recommender Systems
With the dramatic growth of the Internet, it is much more convenient for users to acquire information than before. It is, however, relatively difficult to extract desired information through the huge information pool due to the information overload problem. Just like the situation that people rely on recommendation in their daily decision making process, recommender systems that filter unnecess...
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One of the potent personalization technologies powering the adaptive web is collaborative filtering. Collaborative filtering (CF) is the process of filtering or evaluating items through the opinions of other people. CF technology brings together the opinions of large interconnected communities on the web, supporting filtering of substantial quantities of data. In this chapter we introduce the c...
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Recommender systems are an important part of the information and e-commerce ecosystem. They represent a powerful method for enabling users to filter through large information and product spaces. Nearly two decades of research on collaborative filtering have led to a varied set of algorithms and a rich collection of tools for evaluating their performance. Research in the field is moving in the d...
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ژورنال
عنوان ژورنال: International Journal of Advanced Computer Science and Applications
سال: 2016
ISSN: 2156-5570,2158-107X
DOI: 10.14569/ijacsa.2016.070837