The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
TFMAP: optimizing MAP for top-n context-aware recommendation
Abstract
In this paper, we tackle the problem of top-N context-aware recommendation for implicit feedback scenarios. We frame this challenge as a ranking problem in collaborative filtering (CF). Much of the past work on CF has not focused on evaluation metrics that lead to good top-N recommendation lists in designing recommendation models. In addition, previous work on context-aware recommendation has mainly focused on explicit feedback data, i.e., ratings. We propose TFMAP, a model that directly maximizes Mean Average Precision with the aim of creating an optimally ranked list of items for individual users under a given context. TFMAP uses tensor factorization to model implicit feedback data (e.g., purchases, clicks) with contextual information.
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Cites
Introduction to information retrieval
(2009) · Choice Reviews Online · doi:10.5860/choice.46-2715 · Cited by 12,278
Introduction to Information Retrieval
Manning, C. D., Raghavan, P., & Schütze, H. (2008) · doi:10.1017/cbo9780511809071 · Cited by 11,288
Cited by
Rank-GeoFM: A Ranking based Geographical Factorization Method for Point of Interest Recommendation
Li, X., Cong, G., Li, X.-L., Pham, T.-A. N., & Krishnaswamy, S. (2015) · Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval · doi:10.1145/2766462.2767722 · Cited by 340
Latent Cross: Making Use of Context in Recurrent Recommender Systems
Beutel, A., Covington, P., Jain, S., Xu, C., Li, J., Gatto, V., & Chi, E. H. (2018) · Proceedings of the Eleventh ACM International Conference on Web Search and Data Mining · doi:10.1145/3159652.3159727 · Cited by 313
Optimizing top-n collaborative filtering via dynamic negative item sampling
Zhang, W., Chen, T., Wang, J., & Yu, Y. (2013) · Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval · doi:10.1145/2484028.2484126 · Cited by 256
Progress in context-aware recommender systems — An overview
Raza, S., & Ding, C. (2019) · Computer Science Review · doi:10.1016/j.cosrev.2019.01.001 · Cited by 151
A Graph-based model for context-aware recommendation using implicit feedback data
Yao, W., He, J., Huang, G., Cao, J., & Zhang, Y. (2015) · World Wide Web · doi:10.1007/s11280-014-0307-z · Cited by 54
Metadata
- Authors
- Shi, Y., Karatzoglou, A., Baltrunas, L., Larson, M., Hanjalic, A., & Oliver, N.
- Venue
- Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
- Publisher
- ACM
- Published
- 2012-08-12
- Pages
- 155-164
- OpenAlex
- W1999956270
- Cited by
- 189
- References
- 2
- FWCI
- 15.92
- Type
- conference paper
- Language
- en
- Open access
- closed
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- The paper
- Shi, Y., Karatzoglou, A., Baltrunas, L., Larson, M., Hanjalic, A., & Oliver, N. (2012). TFMAP: optimizing MAP for top-n context-aware recommendation. Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval. https://doi.org/10.1145/2348283.2348308
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