Website-oriented recommendation based on heat spreading and tag-aware collaborative filtering
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Zhang, Zi-Ke
Institute of Information Economy, Hangzhou Normal University, China - Alibaba Research Center for Complexity Sciences, Hangzhou Normal University, China
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Yu, Lu
Institute of Information Economy, Hangzhou Normal University, China - Alibaba Research Center for Complexity Sciences, Hangzhou Normal University, China
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Fang, Kuan
Web Sciences Center, University of Electronic Science and Technology of China, Chengdu, China
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You, Zhi-Qiang
Institute of Information Economy, Hangzhou Normal University, China - Alibaba Research Center for Complexity Sciences, Hangzhou Normal University, China
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Liu, Chuang
Institute of Information Economy, Hangzhou Normal University, China - Alibaba Research Center for Complexity Sciences, Hangzhou Normal University, China
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Liu, Hao
Alibaba Research Center for Complexity Sciences, Hangzhou Normal University, China - Department of Physics, University of Fribourg, Switzerland
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Yan, Xiao-Yong
School of Systems Science, Beijing Normal University, China
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Published in:
- Physica A: Statistical Mechanics and its Applications. - 2014, vol. 399, p. 82–88
English
Recently, Recommender Systems has been widely applied in helping users find potentially interesting items from the era of big data. However, most of researches on this topic have focused on estimating the direct relationships between users and items, neglecting other available information. In this paper, we discuss about mining webs with information extracted from search and browser logs of users. In particular, we utilize the keywords correlated with corresponding websites by Singular Value Decomposition (SVD) technique to model users features and propose the tag-aware kk-nearest neighbor Collaborative Filtering (CF). We then build a hybrid recommendation method to help people accurately find websites by employing Heat Spreading (HeatS) method. Experimental results demonstrate that the hybrid method outperforms baseline algorithms at the global ranking metric.
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Faculty
- Faculté des sciences et de médecine
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Department
- Département de Physique
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Language
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Classification
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Physics
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License
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License undefined
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Identifiers
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Persistent URL
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https://folia.unifr.ch/unifr/documents/303709
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