Diversity optimization for recommendation using improved cover tree
Diversity optimization for recommendation using improved cover tree
复制标题
使用改进的覆盖树进行推荐的多样性优化
DOI:
10.1016/j.knosys.2017.07.004
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发表时间:
2017-11
影响因子:
8.8
通讯作者:
Dong Yongqiang
中科院分区:
文献类型:
--
作者:
Gu Liang;Yang Peng;Dong Yongqiang
Recently, diversity optimization has played an increasingly important role in recommender systems to improve user satisfaction, and it has attracted more attention in the research community. In this paper, we propose a novel diversity-optimization method based on a time-sensitive semantic cover tree (T2SCT). Specifically, we first define T2SCT and its construction algorithm. Based on T2SCT, we present details of the diversified item-selection algorithm and two supplement algorithms to obtain a complete diversified item list. Then, we give a theoretical analysis to prove the correctness of the proposed method. In general, the proposed method can make diverse recommendations with very little compromise on accuracy. Moreover, the proposed method converges quickly and exhibits good item novelty, owing to the inherent superiority of T2SCT. We conduct extensive experiments on a real-world dataset to verify the performance of our method. Results illustrate that the method is effective and efficient, outperforming other conventional approaches.
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DOI:
10.1016/j.knosys.2016.12.010
发表时间:
2017-03
期刊:
Knowl. Based Syst.
影响因子:
--
作者:
Mengsi Liu;Weike Pan;Miao Liu;Yaofeng Chen;Xiaogang Peng;Zhong Ming
通讯作者:
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1994-12
期刊:
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DOI:
10.1109/infcom.2011.5935224
发表时间:
2011-04
期刊:
2011 Proceedings IEEE INFOCOM
影响因子:
--
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通讯作者:
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DOI:
10.1145/3130348.3130369
发表时间:
1998-08
期刊:
ACM SIGIR Forum
影响因子:
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通讯作者:
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DOI:
--
发表时间:
2015-07
期刊:
--
影响因子:
--
作者:
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通讯作者:
Azin Ashkan;B. Kveton;S. Berkovsky;Zheng Wen