Abstract
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 22nd International Conference on Intelligent User Interfaces |
| Place of Publication | New York, NY, USA |
| Publisher | ACM |
| Pages | 35-44 |
| DOIs | |
| Publication status | Published - Mar 2017 |
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Keywords
- Recommender System
- Curiosity
- Television/Video
- Entertainment
- Design Methods
- Personalization
- Qualitative Methods
- User and Cognitive models
- User Studies
- Serendipity
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SIRUP: Serendipity In Recommendations via User Perceptions. / Maccatrozzo, V.; Aroyo, L.M.; Terstall, Manon; Schreiber, Guus.
Proceedings of the 22nd International Conference on Intelligent User Interfaces. New York, NY, USA : ACM, 2017. p. 35-44.Research output: Chapter in Book / Report / Conference proceeding › Conference contribution › Academic › peer-review
TY - GEN
T1 - SIRUP: Serendipity In Recommendations via User Perceptions
AU - Maccatrozzo, V.
AU - Aroyo, L.M.
AU - Terstall, Manon
AU - Schreiber, Guus
PY - 2017/3
Y1 - 2017/3
N2 - In this paper, we propose a model to operationalise serendipity in content-based recommender systems. The model, called SIRUP, is inspired by the Silvia's curiosity theory, based on the fundamental theory of Berlyne, aims at (1) measuring the novelty of an item with respect to the user profile, and (2) assessing whether the user is able to manage such level of novelty (coping potential). The novelty of items is calculated with cosine similarities between items, using Linked Open Data paths. The coping potential of users is estimated by measuring the diversity of the items in the user profile. We deployed and evaluated the SIRUP model in a use case with TV recommender using BBC programs dataset. Results show that the SIRUP model allows us to identify serendipitous recommendations, and, at the same time, to have 71% precision.
AB - In this paper, we propose a model to operationalise serendipity in content-based recommender systems. The model, called SIRUP, is inspired by the Silvia's curiosity theory, based on the fundamental theory of Berlyne, aims at (1) measuring the novelty of an item with respect to the user profile, and (2) assessing whether the user is able to manage such level of novelty (coping potential). The novelty of items is calculated with cosine similarities between items, using Linked Open Data paths. The coping potential of users is estimated by measuring the diversity of the items in the user profile. We deployed and evaluated the SIRUP model in a use case with TV recommender using BBC programs dataset. Results show that the SIRUP model allows us to identify serendipitous recommendations, and, at the same time, to have 71% precision.
KW - Recommender System
KW - Curiosity
KW - Television/Video
KW - Entertainment
KW - Design Methods
KW - Personalization
KW - Qualitative Methods
KW - User and Cognitive models
KW - User Studies
KW - Serendipity
U2 - https://doi.org/10.1145/3025171.3025185
DO - https://doi.org/10.1145/3025171.3025185
M3 - Conference contribution
SP - 35
EP - 44
BT - Proceedings of the 22nd International Conference on Intelligent User Interfaces
PB - ACM
CY - New York, NY, USA
ER -