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Cross-Space Affinity Learning with Its Application to Movie Recommendation | |
Tang, Jinhui1; Qi, Guo-Jun2,3; Zhang, Liyan4; Xu, Changsheng5![]() | |
发表期刊 | IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING
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2013-07-01 | |
卷号 | 25期号:7页码:1510-1519 |
文章类型 | Article |
摘要 | In this paper, we propose a novel cross-space affinity learning algorithm over different spaces with heterogeneous structures. Unlike most of affinity learning algorithms on the homogeneous space, we construct a cross-space tensor model to learn the affinity measures on heterogeneous spaces subject to a set of order constraints from the training pool. We further enhance the model with a factorization form which greatly reduces the number of parameters of the model with a controlled complexity. Moreover, from the practical perspective, we show the proposed factorized cross-space tensor model can be efficiently optimized by a series of simple quadratic optimization problems in an iterative manner. The proposed cross-space affinity learning algorithm can be applied to many real-world problems, which involve multiple heterogeneous data objects defined over different spaces. In this paper, we apply it into the recommendation system to measure the affinity between users and the product items, where a higher affinity means a higher rating of the user on the product. For an empirical evaluation, a widely used benchmark movie recommendation data set-MovieLens-is used to compare the proposed algorithm with other state-of-the-art recommendation algorithms and we show that very competitive results can be obtained. |
关键词 | Cross-space Affinity Learning Heterogeneous Spaces Movie Recommendation |
WOS标题词 | Science & Technology ; Technology |
关键词[WOS] | SYSTEMS |
收录类别 | SCI |
语种 | 英语 |
WOS研究方向 | Computer Science ; Engineering |
WOS类目 | Computer Science, Artificial Intelligence ; Computer Science, Information Systems ; Engineering, Electrical & Electronic |
WOS记录号 | WOS:000319461800006 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/2844 |
专题 | 多模态人工智能系统全国重点实验室_多媒体计算 |
作者单位 | 1.Nanjing Univ Sci & Technol, Sch Comp Sci & Technol, Nanjing 210094, Jiangsu, Peoples R China 2.Univ Illinois, Dept Elect & Comp Engn, Urbana, IL 61801 USA 3.Univ Illinois, Beckman Inst, Urbana, IL 61801 USA 4.Univ Calif Irvine, Dept Informat & Comp Sci, Irvine, CA 92697 USA 5.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Beijing 100190, Peoples R China |
推荐引用方式 GB/T 7714 | Tang, Jinhui,Qi, Guo-Jun,Zhang, Liyan,et al. Cross-Space Affinity Learning with Its Application to Movie Recommendation[J]. IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING,2013,25(7):1510-1519. |
APA | Tang, Jinhui,Qi, Guo-Jun,Zhang, Liyan,&Xu, Changsheng.(2013).Cross-Space Affinity Learning with Its Application to Movie Recommendation.IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING,25(7),1510-1519. |
MLA | Tang, Jinhui,et al."Cross-Space Affinity Learning with Its Application to Movie Recommendation".IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 25.7(2013):1510-1519. |
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