Website-oriented recommendation based on heat spreading and tag-aware collaborative filtering

Zi-Ke Zhang, Lu Yu, Kuan Fang, Zhi-Qiang You, Chuang Liu, Hao Liu and Xiao-Yong Yan

Physica A: Statistical Mechanics and its Applications, 2014, vol. 399, issue C, 82-88

Abstract: 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 k-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.

Keywords: Recommender systems; Collaborative filtering; Heat spreading; SVD; Tag-aware (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:399:y:2014:i:c:p:82-88

DOI: 10.1016/j.physa.2013.12.030

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