The DOI matches its Crossref record; 49 of the 49 references it cites were found in a registry or an index.
A hybrid knowledge-based recommender system for e-learning based on ontology and sequential pattern mining
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
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
Adomavicius, G., & Tuzhilin, A. (2005) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2005.99 · Cited by 10,310
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
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
Amazon.com recommendations: item-to-item collaborative filtering
Linden, G., Smith, B., & York, J. (2003) · IEEE Internet Computing · doi:10.1109/mic.2003.1167344 · Cited by 5,403
Hybrid Recommender Systems: Survey and Experiments
Burke, R. (2002) · User Modeling and User-Adapted Interaction · doi:10.1023/a:1021240730564 · Cited by 3,871
Bobadilla, J., Ortega, F., Hernando, A., & Gutiérrez, A. (2013) · Knowledge-Based Systems · doi:10.1016/j.knosys.2013.03.012 · Cited by 3,158
Content-Based Recommendation Systems
Pazzani, M. J., & Billsus, D. (2007) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-72079-9_10 · Cited by 2,600
Introduction to Recommender Systems Handbook
Ricci, F., Rokach, L., & Shapira, B. (2011) · Recommender Systems Handbook · doi:10.1007/978-0-387-85820-3_1 · Cited by 2,378
Cited by
A Survey of Recommendation Systems: Recommendation Models, Techniques, and Application Fields
Ko, H., Lee, S., Park, Y., & Choi, A. (2022) · Electronics · doi:10.3390/electronics11010141 · Cited by 658
Raj, N. S., & Renumol, V. G. (2022) · Journal of Computers in Education · doi:10.1007/s40692-021-00199-4 · Cited by 253
Charitopoulos, A., Rangoussi, M., & Koulouriotis, D. (2020) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-020-00200-8 · Cited by 89
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
Metadata
- Authors
- Tarus, J. K., Niu, Z., & Yousif, A.
- Venue
- Future Generation Computer Systems
- Publisher
- Elsevier BV
- Published
- 2017-07
- Volume
- 72
- Pages
- 37-48
- ISSN
- 0167-739X (ISSN-L)
- OpenAlex
- W2592804878
- Cited by
- 284
- References
- 49
- FWCI
- 49.41
- 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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: A hybrid knowledge-based recommender system for e-learning based on ontology and sequential pattern mining. https://app.cochat.ai/papers/10.1016/j.future.2017.02.049
- The paper
- Tarus, J. K., Niu, Z., & Yousif, A. (2017). A hybrid knowledge-based recommender system for e-learning based on ontology and sequential pattern mining. Future Generation Computer Systems. https://doi.org/10.1016/j.future.2017.02.049
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.
