The DOI matches its Crossref record; 76 of the 76 references it cites were found in a registry or an index.
Context‐Aware Recommender Systems
Open accessAbstract
Context‐aware recommender systems (CARS) generate more relevant recommendations by adapting them to the specific contextual situation of the user. This article explores how contextual information can be used to create intelligent and useful recommender systems. It provides an overview of the multifaceted notion of context, discusses several approaches for incorporating contextual information in the recommendation process, and illustrates the usage of such approaches in several application areas where different types of contexts are exploited. The article concludes by discussing the challenges and future research directions for context‐aware recommender systems.
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Cites
Adomavicius, G., & Tuzhilin, A. (2005) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2005.99 · Cited by 10,310
Self-citationItem-based collaborative filtering recommendation algorithms
Sarwar, B., Karypis, G., Konstan, J., & Riedl, J. (2001) · Proceedings of the 10th international conference on World Wide Web · doi:10.1145/371920.372071 · Cited by 9,135
Evaluating collaborative filtering recommender systems
Herlocker, J. L., Konstan, J. A., Terveen, L. G., & Riedl, J. T. (2004) · ACM Transactions on Information Systems · doi:10.1145/963770.963772 · Cited by 5,798
Empirical Analysis of Predictive Algorithms for Collaborative Filtering
Breese, J. S., Heckerman, D. E., & Kadie, C. M. (2013) · arXiv (Cornell University) · doi:10.48550/arxiv.1301.7363 · Cited by 4,772
Hybrid Recommender Systems: Survey and Experiments
Burke, R. (2002) · User Modeling and User-Adapted Interaction · doi:10.1023/a:1021240730564 · Cited by 3,871
Factorization meets the neighborhood: a multifaceted collaborative filtering model
Koren, Y. (2008) · Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining · doi:10.1145/1401890.1401944 · Cited by 3,852
Regression Analysis by Example.
Kmenta, J., Chatterjee, S., & Price, B. (1980) · Journal of the American Statistical Association · doi:10.2307/2287213 · Cited by 3,198
Dey, A. K., Abowd, G. D., & Salber, D. (2001) · Human–Computer Interaction · doi:10.1207/s15327051hci16234_02 · Cited by 2,951
An overview of data warehousing and OLAP technology
Chaudhuri, S., & Dayal, U. (1997) · ACM SIGMOD Record · doi:10.1145/248603.248616 · Cited by 2,424
Feature Selection for Knowledge Discovery and Data Mining
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Cited by
Bobadilla, J., Ortega, F., Hernando, A., & Gutiérrez, A. (2013) · Knowledge-Based Systems · doi:10.1016/j.knosys.2013.03.012 · Cited by 3,158
The use of machine learning algorithms in recommender systems: a systematic review
Portugal, I., Alencar, P., & Cowan, D. (2018) · Expert Systems with Applications · doi:10.1016/j.eswa.2017.12.020 · Cited by 743
Leveraging Meta-path based Context for Top- N Recommendation with A Neural Co-Attention Model
Hu, B., Shi, C., Zhao, W. X., & Yu, P. S. (2018) · Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining · doi:10.1145/3219819.3219965 · Cited by 674
Böhmer, M., Hecht, B., Schöning, J., Krüger, A., & Bauer, G. (2011) · Proceedings of the 13th International Conference on Human Computer Interaction with Mobile Devices and Services · doi:10.1145/2037373.2037383 · Cited by 604
Context-Aware Recommender Systems for Learning: A Survey and Future Challenges
Verbert, K., Manouselis, N., Ochoa, X., Wolpers, M., Drachsler, H., Bosnic, I., & Duval, E. (2012) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2012.11 · Cited by 560
Metadata
- Authors
- Adomavicius, G., Mobasher, B., Ricci, F., & Tuzhilin, A.
- Venue
- AI Magazine
- Publisher
- Wiley
- Published
- 2011-09
- Volume
- 32
- Issue
- 3
- Pages
- 67-80
- ISSN
- 0738-4602 (ISSN-L)
- 2371-9621
- OpenAlex
- W1560147776
- Cited by
- 1,355
- References
- 76
- FWCI
- 335.70
- Type
- journal article
- Language
- en
- Open access
- bronze
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
