Diversity-based recommender systems aim to select a wide rangeof relevant content for users, but diversity needs for users withdifferent personalities are rarely studied. Similarly, research onpersonality-based recommender systems has primarily focused onthe ‘cold-start problem’; few previous works have investigated howpersonality influences users’ diversity needs. This paper combinesthese two branches of research together: re-ranking for diversifica-tion, and improving accuracy using personality traits. Anchoredin the music domain, we investigate how personality informationcan be used to adjust the diversity degrees for people with differentpersonalities. We proposed a personality-based diversification algo-rithm to help enhance the diversity adjusting strategy according topeople’s personality information in music recommendations. Ouroffline and online evaluation results demonstrate that our proposedmethod is an effective solution to generate personalized recommen-dation lists that not only have relatively higher diversity as well asaccuracy, but which also lead to increased user satisfaction.
|Title of host publication||Proceedings of the 5th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems|
|Editors||Peter Brusilovsky, Marco de Gemmis, Alexander Felfernig, Pasquale Lops, John O'Donovan, Giovanni Semeraro, Martijn C. Willemsen|
|Number of pages||8|
|Publication status||Published - 2018|
|Event||IntRS 2018: 5th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems - Vancouver, Canada|
Duration: 7 Oct 2018 → 7 Oct 2018
|Name||CEUR Workshop Proceedings|
|Period||7/10/18 → 7/10/18|
- Recommender Systems
- Music Recommendation
Lu, F., & Tintarev, N. (2018). A Diversity Adjusting Strategy with Personality for Music Recommendation. In P. Brusilovsky, M. de Gemmis, A. Felfernig, P. Lops, J. O'Donovan, G. Semeraro, & M. C. Willemsen (Eds.), Proceedings of the 5th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (pp. 7-14). (CEUR Workshop Proceedings; Vol. 2225). CEUR.