The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Hybrid Recommender Systems: Survey and Experiments
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The anatomy of a large-scale hypertextual Web search engine
Brin, S., & Page, L. (1998) · Computer Networks and ISDN Systems · doi:10.1016/s0169-7552(98)00110-x · Cited by 16,004
Cited by
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
Generation Z consumers’ expectations of interactions in smart retailing: A future agenda
Priporas, C.-V., Stylos, N., & Fotiadis, A. K. (2017) · Computers in Human Behavior · doi:10.1016/j.chb.2017.01.058 · Cited by 838
The effects of transparency on trust in and acceptance of a content-based art recommender
Cramer, H., Evers, V., Ramlal, S., van Someren, M., Rutledge, L., Stash, N., Aroyo, L., & Wielinga, B. (2008) · User Modeling and User-Adapted Interaction · doi:10.1007/s11257-008-9051-3 · Cited by 448
SCHATZMANN, J., WEILHAMMER, K., STUTTLE, M., & YOUNG, S. (2006) · The Knowledge Engineering Review · doi:10.1017/s0269888906000944 · Cited by 336
Sun, D., Wang, M., & Li, A. (2019) · IEEE/ACM Transactions on Computational Biology and Bioinformatics · doi:10.1109/tcbb.2018.2806438 · Cited by 338
Bodily, R., & Verbert, K. (2017) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2017.2740172 · Cited by 306
Feature weighting in content based recommendation system using social network analysis
Debnath, S., Ganguly, N., & Mitra, P. (2008) · Proceedings of the 17th international conference on World Wide Web · doi:10.1145/1367497.1367646 · Cited by 253
SuggestBot: using intelligent task routing to help people find work in wikipedia
Cosley, D., Frankowski, D., Terveen, L., & Riedl, J. (2007) · Proceedings of the 12th international conference on Intelligent user interfaces · doi:10.1145/1216295.1216309 · Cited by 245
Personalized recommender system for e-Learning environment
Benhamdi, S., Babouri, A., & Chiky, R. (2017) · Education and Information Technologies · doi:10.1007/s10639-016-9504-y · Cited by 146
Al-Hassan, M., Lu, H., & Lu, J. (2015) · Decision Support Systems · doi:10.1016/j.dss.2015.02.001 · Cited by 136
Acceptance of recommendations to buy in online retailing.
Baier, D., & Stüber, E. (2010) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2010.03.005 · Cited by 106
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
(2006) · Cited by 72
Transforming Digital Marketing with Generative AI
Islam, T., Miron, A., Nandy, M., Choudrie, J., Liu, X., & Li, Y. (2024) · Computers · doi:10.3390/computers13070168 · Cited by 68
Embedding Emotional Context in Recommender Systems
Gonzalez, G., de la Rosa, J. L., Montaner, M., & Delfin, S. (2007) · 2007 IEEE 23rd International Conference on Data Engineering Workshop · doi:10.1109/icdew.2007.4401075 · Cited by 64
Ozok, A. A., Fan, Q., & Norcio, A. F. (2010) · Behaviour & Information Technology · doi:10.1080/01449290903004012 · Cited by 60
Recommender Systems: Do They Have a Viable Business Model in e-Tourism?
Rabanser, U., & Ricci, F. (2005) · Information and Communication Technologies in Tourism 2005 · doi:10.1007/3-211-27283-6_15 · Cited by 52
Responsible and human centric AI-based insurance advisors
Pisoni, G., & Díaz-Rodríguez, N. (2023) · Information Processing & Management · doi:10.1016/j.ipm.2023.103273 · Cited by 42
A systematic review of privacy techniques in recommendation systems
Ogunseyi, T. B., Avoussoukpo, C. B., & Jiang, Y. (2023) · International Journal of Information Security · doi:10.1007/s10207-023-00710-1 · Cited by 27
(2006) · Open Research (University of Surrey) · Cited by 23
Huang, J., Oosterhuis, H., Mansoury, M., van Hoof, H., & de Rijke, M. (2024) · Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval · doi:10.1145/3626772.3657749 · Cited by 17
Optimal Sepsis Patient Treatment using Human-in-the-loop Artificial Intelligence
Gupta, A., Lash, M. T., & Nachimuthu, S. K. (2021) · Expert Systems with Applications · doi:10.1016/j.eswa.2020.114476 · Cited by 13
The Impact of Generative AI on Personalized Content Marketing in E-Commerce
Mohiuddin, D., Tariq, M. H., & Tahir, A. (2025) · Inverge Journal of Social Sciences · doi:10.63544/ijss.v4i1.288
Metadata
- Authors
- Burke, R.
- Venue
- User Modeling and User-Adapted Interaction
- Published
- 2002-11
- Volume
- 12
- Issue
- 4
- Pages
- 331-370
- ISSN
- 0924-1868 (ISSN-L)
- 1573-1391
- OpenAlex
- W281665770
- Cited by
- 3,871
- References
- 1
- FWCI
- 102.72
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
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.