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- W2099306325 abstract "Different efforts have been done to address the problem of information overload on the Internet. Recommender systems aim at directing users through this information space, toward the resources that best meet their needs and interests by extracting knowledge from the previous userspsila interactions. In this paper, we propose an algorithm to solve the Web page recommendation problem. In our algorithm, we use distributed learning automata to learn the behavior of previous users' and recommend pages to the current user based on learned pattern. Our experiments on real data set show that the proposed algorithm performs better than the other algorithms that we compared to and, at the same time, it is less complex than other algorithms with respect to memory usage and computational cost too." @default.
- W2099306325 created "2016-06-24" @default.
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- W2099306325 date "2009-01-01" @default.
- W2099306325 modified "2023-09-23" @default.
- W2099306325 title "Effective Page Recommendation Algorithms Based on Distributed Learning Automata" @default.
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- W2099306325 doi "https://doi.org/10.1109/iccgi.2009.14" @default.
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