Early findings from a large-scale user study of CHESTNUT: Validations and implications
Towards a serendipitous recommender system with user-centred understanding, we have built CHESTNUT , an Information Theory-based Movie Recommender System, which introduced a more comprehensive understanding of the concept. Although off-line evaluations have already demonstrated that CHESTNUT has gre...
| Main Authors: | , , , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2020
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| Subjects: | |
| Online Access: | https://eprints.nottingham.ac.uk/60668/ |
| _version_ | 1848799792696655872 |
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| author | Peng, Xiangjun Huang, Zhentao Yang, Cheng Song, Zilin Sun, Xu |
| author_facet | Peng, Xiangjun Huang, Zhentao Yang, Cheng Song, Zilin Sun, Xu |
| author_sort | Peng, Xiangjun |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | Towards a serendipitous recommender system with user-centred understanding, we have built CHESTNUT , an Information Theory-based Movie Recommender System, which introduced a more comprehensive understanding of the concept. Although off-line evaluations have already demonstrated that CHESTNUT has greatly improved serendip-ity performance, feedback on CHESTNUT from real-world users through online services are still unclear now. In order to evaluate how serendip-itous results could be delivered by CHESTNUT , we consequently designed , organized and conducted large-scale user study, which involved 104 participants from 10 campuses in 3 countries. Our preliminary feedback has shown that, compared with mainstream collaborative filtering techniques, though CHESTNUT limited users' feelings of unex-pectedness to some extent, it showed significant improvement in their feelings about certain metrics being both beneficial and interesting, which substantially increased users' experience of serendipity. Based on them, we have summarized three key takeaways, which would be beneficial for further designs and engineering of serendipitous recommender systems, from our perspective. All details of our large-scale user study could be found at https://github.com/unnc-idl-ucc/Early-Lessons-From-CHESTNUT |
| first_indexed | 2025-11-14T20:41:18Z |
| format | Conference or Workshop Item |
| id | nottingham-60668 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T20:41:18Z |
| publishDate | 2020 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-606682020-05-21T06:30:27Z https://eprints.nottingham.ac.uk/60668/ Early findings from a large-scale user study of CHESTNUT: Validations and implications Peng, Xiangjun Huang, Zhentao Yang, Cheng Song, Zilin Sun, Xu Towards a serendipitous recommender system with user-centred understanding, we have built CHESTNUT , an Information Theory-based Movie Recommender System, which introduced a more comprehensive understanding of the concept. Although off-line evaluations have already demonstrated that CHESTNUT has greatly improved serendip-ity performance, feedback on CHESTNUT from real-world users through online services are still unclear now. In order to evaluate how serendip-itous results could be delivered by CHESTNUT , we consequently designed , organized and conducted large-scale user study, which involved 104 participants from 10 campuses in 3 countries. Our preliminary feedback has shown that, compared with mainstream collaborative filtering techniques, though CHESTNUT limited users' feelings of unex-pectedness to some extent, it showed significant improvement in their feelings about certain metrics being both beneficial and interesting, which substantially increased users' experience of serendipity. Based on them, we have summarized three key takeaways, which would be beneficial for further designs and engineering of serendipitous recommender systems, from our perspective. All details of our large-scale user study could be found at https://github.com/unnc-idl-ucc/Early-Lessons-From-CHESTNUT 2020-01-01 Conference or Workshop Item NonPeerReviewed application/pdf en cc_by https://eprints.nottingham.ac.uk/60668/1/Early%20Findings%20from%20a%20Large-scale%20User%20Study%20of%20CHESTNUT%20Validations%20and%20Implications.pdf Peng, Xiangjun, Huang, Zhentao, Yang, Cheng, Song, Zilin and Sun, Xu (2020) Early findings from a large-scale user study of CHESTNUT: Validations and implications. In: 22th Springer International Conference on Human-Computer Interaction, 19-24 July 2020, Copenhagen, Denmark. (Unpublished) Serendipity; RecommederSystems; UserStudy |
| spellingShingle | Serendipity; RecommederSystems; UserStudy Peng, Xiangjun Huang, Zhentao Yang, Cheng Song, Zilin Sun, Xu Early findings from a large-scale user study of CHESTNUT: Validations and implications |
| title | Early findings from a large-scale user study of CHESTNUT: Validations and implications |
| title_full | Early findings from a large-scale user study of CHESTNUT: Validations and implications |
| title_fullStr | Early findings from a large-scale user study of CHESTNUT: Validations and implications |
| title_full_unstemmed | Early findings from a large-scale user study of CHESTNUT: Validations and implications |
| title_short | Early findings from a large-scale user study of CHESTNUT: Validations and implications |
| title_sort | early findings from a large-scale user study of chestnut: validations and implications |
| topic | Serendipity; RecommederSystems; UserStudy |
| url | https://eprints.nottingham.ac.uk/60668/ |