CHESTNUT: Improve serendipity in movie recommendation by an Information Theory-based collaborative filtering approach
The term serendipity has been understood narrowly in the Recommender System. Applying a user-centered approach, user-friendly serendipitous recommender systems are expected to be developed based on a good understanding of serendipity. In this paper, we introduce CHESTNUT , a memory-based movie colla...
| Main Authors: | , , , , , |
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| Format: | Monograph |
| Language: | English |
| Published: |
Unpublished
2019
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| Subjects: | |
| Online Access: | https://eprints.nottingham.ac.uk/60667/ |
| _version_ | 1848799792406200320 |
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| author | Peng, Xiangjun Zhang, Hongzhi Zhou, Xiaosong Wang, Shuolei Sun, Xu Wang, Qingfeng |
| author_facet | Peng, Xiangjun Zhang, Hongzhi Zhou, Xiaosong Wang, Shuolei Sun, Xu Wang, Qingfeng |
| author_sort | Peng, Xiangjun |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | The term serendipity has been understood narrowly in the Recommender System. Applying a user-centered approach, user-friendly serendipitous recommender systems are expected to be developed based on a good understanding of serendipity. In this paper, we introduce CHESTNUT , a memory-based movie collaborative filtering system to improve serendipity performance. Relying on a proposed Information Theory-based algorithm and previous study, we demonstrate a method of successfully injecting insight, unexpectedness and usefulness, which are key metrics for a more comprehensive understanding of serendipity, into a practical serendipitous runtime system. With lightweight experiments, we have revealed a few runtime issues and further optimized the same. We have evaluated CHESTNUT in both practicability and effectiveness , and the results show that it is fast, scalable and improves serendip-ity performance significantly, compared with mainstream memory-based collaborative filtering. The source codes of CHESTNUT are online at https://github.com/unnc-idl-ucc/CHESTNUT/. |
| first_indexed | 2025-11-14T20:41:18Z |
| format | Monograph |
| id | nottingham-60667 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T20:41:18Z |
| publishDate | 2019 |
| publisher | Unpublished |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-606672020-05-21T07:01:19Z https://eprints.nottingham.ac.uk/60667/ CHESTNUT: Improve serendipity in movie recommendation by an Information Theory-based collaborative filtering approach Peng, Xiangjun Zhang, Hongzhi Zhou, Xiaosong Wang, Shuolei Sun, Xu Wang, Qingfeng The term serendipity has been understood narrowly in the Recommender System. Applying a user-centered approach, user-friendly serendipitous recommender systems are expected to be developed based on a good understanding of serendipity. In this paper, we introduce CHESTNUT , a memory-based movie collaborative filtering system to improve serendipity performance. Relying on a proposed Information Theory-based algorithm and previous study, we demonstrate a method of successfully injecting insight, unexpectedness and usefulness, which are key metrics for a more comprehensive understanding of serendipity, into a practical serendipitous runtime system. With lightweight experiments, we have revealed a few runtime issues and further optimized the same. We have evaluated CHESTNUT in both practicability and effectiveness , and the results show that it is fast, scalable and improves serendip-ity performance significantly, compared with mainstream memory-based collaborative filtering. The source codes of CHESTNUT are online at https://github.com/unnc-idl-ucc/CHESTNUT/. Unpublished 2019-01-01 Monograph NonPeerReviewed application/pdf en cc_by https://eprints.nottingham.ac.uk/60667/1/CHESTNUT%20Improve%20Serendipity%20in%20Movie%20Recommendation%20by%20an%20Information%20Theory-based%20Collaborative%20Filtering%20Approach.pdf Peng, Xiangjun, Zhang, Hongzhi, Zhou, Xiaosong, Wang, Shuolei, Sun, Xu and Wang, Qingfeng (2019) CHESTNUT: Improve serendipity in movie recommendation by an Information Theory-based collaborative filtering approach. Working Paper. Unpublished. (Unpublished) Serendipity; RecommederSystems; InformationTheory |
| spellingShingle | Serendipity; RecommederSystems; InformationTheory Peng, Xiangjun Zhang, Hongzhi Zhou, Xiaosong Wang, Shuolei Sun, Xu Wang, Qingfeng CHESTNUT: Improve serendipity in movie recommendation by an Information Theory-based collaborative filtering approach |
| title | CHESTNUT: Improve serendipity in movie recommendation by an Information Theory-based collaborative filtering approach |
| title_full | CHESTNUT: Improve serendipity in movie recommendation by an Information Theory-based collaborative filtering approach |
| title_fullStr | CHESTNUT: Improve serendipity in movie recommendation by an Information Theory-based collaborative filtering approach |
| title_full_unstemmed | CHESTNUT: Improve serendipity in movie recommendation by an Information Theory-based collaborative filtering approach |
| title_short | CHESTNUT: Improve serendipity in movie recommendation by an Information Theory-based collaborative filtering approach |
| title_sort | chestnut: improve serendipity in movie recommendation by an information theory-based collaborative filtering approach |
| topic | Serendipity; RecommederSystems; InformationTheory |
| url | https://eprints.nottingham.ac.uk/60667/ |