Zhou Meilin
School of Information Science, Beijing Language and Culture University, Beijing, 100083, People`s Republic of China
Xu Yan
Institute of Computing Technology, Chinese Academy of Sciences, 100190, Beijing, People`s Republic of China
Han Siyao
School of Information Science, Beijing Language and Culture University, Beijing, 100083, People`s Republic of China
Zhao Yaqing
School of Information Science, Beijing Language and Culture University, Beijing, 100083, People`s Republic of China
ABSTRACT
Recommendation systems have become an important research area since the appearance of the first studys on collaborative filtering in the mid-1990 (Hill et al., 1995). Several existing methods came from the perspective of content and each of them has advantages and disadvantages. In this study, we proposed a recommendation method based on url-based hierarchical relationships. We calculate level of candidate pages after the analysis of the hierarchical relationship between pages. Different from traditional methods, this can implicitly use pages category information. At the same time considering the hierarchical relationship of web page to get more information. Thus, to a certain extent, resolve data sparsity problem. Experiment shows that, in this way, result is better than those hierarchies are not considered in recommended precision.
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How to cite this article
Zhou Meilin, Xu Yan, Han Siyao and Zhao Yaqing, 2013. An Exploration of Recommender Systems Based on Url Hierarchy Relationships. Information Technology Journal, 12: 5367-5371.
DOI: 10.3923/itj.2013.5367.5371
URL: https://scialert.net/abstract/?doi=itj.2013.5367.5371
DOI: 10.3923/itj.2013.5367.5371
URL: https://scialert.net/abstract/?doi=itj.2013.5367.5371
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