Cited By
View all- Cheng SJiang HWang WJiang W(2023)Research on multi-context aware recommendation methods based on tensor factorizationMultimedia Systems10.1007/s00530-023-01103-z29:4(2253-2262)Online publication date: 15-May-2023
Valid context detection based on context filter in context-aware recommendation system
Authors: 
Shulin Cheng, Bofeng Zhang, Guobing Zou, Mingqing Huang, and Ying LvAuthors Info & Claims
Shulin Cheng, Bofeng Zhang, Guobing Zou, Mingqing Huang, and Ying LvAuthors Info & ClaimsJuly 2018
Pages 149 - 153
Abstract
Context as a kind of quite important information plays a significant role in context-aware recommendation system (CARS). Many studies have been proved that context help promote to improve the effectiveness of recommendations. But a serious challenge has yet not been solved well, which is how to detect valid contexts for users in CARS, since different users have different sensitivity to contexts. Motivated by the observations, we proposed a method of valid context detection based on context filter. Context filter comprises two selection phases. In the first phase, context selection depends on the expert experiences, which is also called primary selection. We focus on the second selection phase named refinement selection based on one-way analysis of variance (ANOVA). By one-way ANOVA, a utility function is put forward to measure user's context sensitivity to detect valid contexts. We verified the effectiveness of detection method by the experiments on a small real film dataset.
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Index Terms
- Valid context detection based on context filter in context-aware recommendation system
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Proceedings, Part I, of the 16th International Conference on Web Information Systems Engineering --- WISE 2015 - Volume 9418Context-aware recommender systems CARS take context into consideration when modeling user preferences. There are two general ways to integrate context with recommendation: contextual filtering and contextual modeling. Currently, the most effective ...
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July 2018
174 pages
ISBN:9781450365215
DOI:10.1145/3239283
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Published: 20 July 2018
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DSIT2018: 2018 International Conference on Data Science and Information Technology
July 20 - 22, 2018
Singapore, Singapore
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DSIT '18 Paper Acceptance Rate 31 of 85 submissions, 36%;
Overall Acceptance Rate 114 of 277 submissions, 41%
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View all- Cheng SJiang HWang WJiang W(2023)Research on multi-context aware recommendation methods based on tensor factorizationMultimedia Systems10.1007/s00530-023-01103-z29:4(2253-2262)Online publication date: 15-May-2023
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