Cross-Domain Recommendations with Overlapping Items
Denis Kotkov, Shuaiqiang Wang, Jari Veijalainen
2016
Abstract
In recent years, there has been an increasing interest in cross-domain recommender systems. However, most existing works focus on the situation when only users or users and items overlap in different domains. In this paper, we investigate whether the source domain can boost the recommendation performance in the target domain when only items overlap. Due to the lack of publicly available datasets, we collect a dataset from two domains related to music, involving both the users' rating scores and the description of the items. We then conduct experiments using collaborative filtering and content-based filtering approaches for validation purpose. According to our experimental results, the source domain can improve the recommendation performance in the target domain when only items overlap. However, the improvement decreases with the growth of non-overlapping items in different domains.
References
- Abel, F., Herder, E., Houben, G.-J., Henze, N., and Krause, D. (2013). Cross-system user modeling and personalization on the social web. User Modeling and UserAdapted Interaction, 23(2-3):169-209.
- Berkovsky, S., Kuflik, T., and Ricci, F. (2008). Mediation of user models for enhanced personalization in recommender systems. User Modeling and User-Adapted Interaction, 18(3):245-286.
- Cantador, I. and Cremonesi, P. (2014). Tutorial on crossdomain recommender systems. In Proceedings of the 8th ACM Conference on Recommender Systems, RecSys 7814, pages 401-402, New York, NY, USA. ACM.
- Cremonesi, P., Tripodi, A., and Turrin, R. (2011). Crossdomain recommender systems. In Data Mining Workshops (ICDMW), 2011 IEEE 11th International Conference on, pages 496-503.
- Ekstrand, M. D., Riedl, J. T., and Konstan, J. A. (2011). Collaborative filtering recommender systems. Foundations and Trends in Human-Computer Interaction, 4(2):81-173.
- Fernández-Tobías, I., Cantador, I., Kaminskas, M., and Ricci, F. (2012). Cross-domain recommender systems: A survey of the state of the art. In Spanish Conference on Information Retrieval.
- Järvelin, K. and Kekäläinen, J. (2002). Cumulated gainbased evaluation of IR techniques. ACM Transactions on Information Systems, 20(4):422-446.
- Kille, B., Hopfgartner, F., Brodt, T., and Heintz, T. (2013). The plista dataset. In Proceedings of the 2013 International News Recommender Systems Workshop and Challenge, NRS 7813, pages 16-23, New York, NY, USA. ACM.
- Lops, P., de Gemmis, M., and Semeraro, G. (2011). Content-based recommender systems: State of the art and trends. In Recommender Systems Handbook, pages 73-105. Springer US.
- Ricci, F., Rokach, L., and Shapira, B. (2011). Introduction to Recommender Systems Handbook. Springer US.
- Sahebi, S. and Brusilovsky, P. (2013). Cross-domain collaborative recommendation in a cold-start context: The impact of user profile size on the quality of recommendation. In User Modeling, Adaptation, and Personalization, volume 7899 of Lecture Notes in Computer Science, pages 289-295. Springer Berlin Heidelberg.
- Sang, J. (2014). Cross-network social multimedia computing. In User-centric Social Multimedia Computing, Springer Theses, pages 81-99. Springer Berlin Heidelberg.
- Shapira, B., Rokach, L., and Freilikhman, S. (2013). Facebook single and cross domain data for recommendation systems. User Modeling and User-Adapted Interaction, 23(2-3):211-247.
- Winoto, P. and Tang, T. (2008). If you like the devil wears prada the book, will you also enjoy the devil wears prada the movie? a study of cross-domain recommendations. New Generation Computing, 26(3):209-225.
- Zhao, Y.-L. (2013). Community Learning in Locationbased Social Networks. Thesis. Ph.D.
Paper Citation
in Harvard Style
Kotkov D., Wang S. and Veijalainen J. (2016). Cross-Domain Recommendations with Overlapping Items . In Proceedings of the 12th International Conference on Web Information Systems and Technologies - Volume 2: WEBIST, ISBN 978-989-758-186-1, pages 131-138. DOI: 10.5220/0005851301310138
in Bibtex Style
@conference{webist16,
author={Denis Kotkov and Shuaiqiang Wang and Jari Veijalainen},
title={Cross-Domain Recommendations with Overlapping Items},
booktitle={Proceedings of the 12th International Conference on Web Information Systems and Technologies - Volume 2: WEBIST,},
year={2016},
pages={131-138},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005851301310138},
isbn={978-989-758-186-1},
}
in EndNote Style
TY - CONF
JO - Proceedings of the 12th International Conference on Web Information Systems and Technologies - Volume 2: WEBIST,
TI - Cross-Domain Recommendations with Overlapping Items
SN - 978-989-758-186-1
AU - Kotkov D.
AU - Wang S.
AU - Veijalainen J.
PY - 2016
SP - 131
EP - 138
DO - 10.5220/0005851301310138