The DOI matches its Crossref record; 108 of the 108 references it cites were found in a registry or an index.
Recommender systems based on user reviews: the state of the art
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Cites
(2003) · Journal of Machine Learning Research · doi:10.5555/944919.944937 · Cited by 32,337
Greedy function approximation: A gradient boosting machine
Friedman, J. H. (2001) · The Annals of Statistics · doi:10.1214/aos/1013203451 · Cited by 30,731
(1999) · Cited by 12,854
Introduction to information retrieval
(2009) · Choice Reviews Online · doi:10.5860/choice.46-2715 · Cited by 12,278
Matrix Factorization Techniques for Recommender Systems
Koren, Y., Bell, R., & Volinsky, C. (2009) · Computer · doi:10.1109/mc.2009.263 · Cited by 11,673
WordNet: An Electronic Lexical Database
Kilgarriff, A., & Fellbaum, C. (2000) · Language · doi:10.2307/417141 · Cited by 11,464
Introduction to Information Retrieval
Manning, C. D., Raghavan, P., & Schütze, H. (2008) · doi:10.1017/cbo9780511809071 · Cited by 11,288
Adomavicius, G., & Tuzhilin, A. (2005) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2005.99 · Cited by 10,310
Term-weighting approaches in automatic text retrieval
Salton, G., & Buckley, C. (1988) · Information Processing & Management · doi:10.1016/0306-4573(88)90021-0 · Cited by 9,740
Item-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
Cited by
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
Systematic reviews in sentiment analysis: a tertiary study
Ligthart, A., Catal, C., & Tekinerdogan, B. (2021) · Artificial Intelligence Review · doi:10.1007/s10462-021-09973-3 · Cited by 303
MRR: an unsupervised algorithm to rank reviews by relevance
Woloszyn, V., dos Santos, H. D. P., Wives, L. K., & Becker, K. (2017) · Proceedings of the International Conference on Web Intelligence · doi:10.1145/3106426.3106444 · Cited by 9
Metadata
- Authors
- Chen, L., Chen, G., & Wang, F.
- Venue
- User Modeling and User-Adapted Interaction
- Published
- 2015-01-22
- Volume
- 25
- Issue
- 2
- Pages
- 99-154
- ISSN
- 0924-1868 (ISSN-L)
- 1573-1391
- OpenAlex
- W2037351199
- Cited by
- 403
- References
- 108
- FWCI
- 100.01
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Recommender systems based on user reviews: the state of the art. https://app.cochat.ai/papers/10.1007/s11257-015-9155-5
- The paper
- Chen, L., Chen, G., & Wang, F. (2015). Recommender systems based on user reviews: the state of the art. User Modeling and User-Adapted Interaction. https://doi.org/10.1007/s11257-015-9155-5
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.
