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Recommender Systems Handbook
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Citations
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Context-Aware Recommender Systems
Adomavicius, G., & Tuzhilin, A. (2011) · Recommender Systems Handbook · doi:10.1007/978-0-387-85820-3_7 · Cited by 1,102
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Towards Conversational Search and Recommendation: System Ask, User Respond
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Neural Rating Regression with Abstractive Tips Generation for Recommendation
Li, P., Wang, Z., Ren, Z., Bing, L., & Lam, W. (2017) · Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval · doi:10.1145/3077136.3080822 · Cited by 313
Human-Data Interaction: The Human Face of the Data-Driven Society
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Trust-based recommendation systems in Internet of Things: a systematic literature review
Mohammadi, V., Rahmani, A. M., Darwesh, A. M., & Sahafi, A. (2019) · Human-centric Computing and Information Sciences · doi:10.1186/s13673-019-0183-8 · Cited by 185
Reputation Transferability in Online Labor Markets
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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
Himeur, Y., Sohail, S. S., Bensaali, F., Amira, A., & Alazab, M. (2022) · Computers & Security · doi:10.1016/j.cose.2022.102746 · Cited by 139
Recommender systems and the amplification of extremist content
Whittaker, J., Looney, S., Reed, A., & Votta, F. (2021) · Internet Policy Review · doi:10.14763/2021.2.1565 · Cited by 135
Futures of artificial intelligence through technology readiness levels
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I can do better than your AI: expertise and explanations
Schaffer, J., O'Donovan, J., Michaelis, J., Raglin, A., & Höllerer, T. (2019) · Proceedings of the 24th International Conference on Intelligent User Interfaces · doi:10.1145/3301275.3302308 · Cited by 119
Automated Product Recommendations with Preference-Based Explanations
Marchand, A., & Marx, P. (2020) · Journal of Retailing · doi:10.1016/j.jretai.2020.01.001 · Cited by 100
Privacy-preserving collaborative recommendations based on random perturbations
Polatidis, N., Georgiadis, C. K., Pimenidis, E., & Mouratidis, H. (2017) · Expert Systems with Applications · doi:10.1016/j.eswa.2016.11.018 · Cited by 80
Factors influencing willingness to provide personal information for personalized recommendations
Kim, M. S., & Kim, S. (2018) · Computers in Human Behavior · doi:10.1016/j.chb.2018.06.031 · Cited by 78
Persuasive computing: Feeling peer pressure from multiple computer agents
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Complementing educational recommender systems with open learner models
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Exploiting Publication Contents and Collaboration Networks for Collaborator Recommendation
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FCMF: Federated collective matrix factorization for heterogeneous collaborative filtering
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Fairness metrics and bias mitigation strategies for rating predictions
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Cross-domain recommendation with user personality
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An Interactive Personalized Recommendation System Using the Hybrid Algorithm Model
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New SVD-based collaborative filtering algorithms with differential privacy
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Carrera-Rivera, A., Larrinaga, F., Lasa, G., Martinez-Arellano, G., & Unamuno, G. (2024) · User Modeling and User-Adapted Interaction · doi:10.1007/s11257-024-09414-0 · Cited by 30
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Enriched music representations with multiple cross-modal contrastive learning
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On the Detection of Shilling Attacks in Federated Collaborative Filtering
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Radensky, M., Séguin, J. A., Lim, J. S., Olson, K., & Geiger, R. (2023) · 2023 ACM Conference on Fairness Accountability and Transparency · doi:10.1145/3593013.3594043 · Cited by 14
Can user privacy and recommendation performance be preserved simultaneously?
Feng, T., Guo, Y., & Chen, Y. (2015) · Computer Communications · doi:10.1016/j.comcom.2015.06.013 · Cited by 9
Understanding User Perspectives on Sustainability and Fairness in Tourism Recommender Systems
Banik, P., Banerjee, A., & Wörndl, W. (2023) · Adjunct Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization · doi:10.1145/3563359.3597442 · Cited by 9
(2018) · ACM Conference on Recommender Systems (RecSys)
Metadata
- Venue
- Springer eBooks
- Publisher
- Springer US
- Published
- 2011
- OpenAlex
- W1690919088
- Cited by
- 3,761
- References
- 1
- FWCI
- 165.97
- Type
- book
- Language
- en
- Open access
- closed
- Licence
- www.springernature.com/gp/researchers/text-and-data-mining (tdm)
- www.springernature.com/gp/researchers/text-and-data-mining (vor)
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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.
