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
Collaborative Filtering Recommender Systems
Schafer, J. B., Frankowski, D., Herlocker, J., & Sen, S. (2007) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-72079-9_9 · Cited by 2,120
Recommender system application developments: A survey
Lu, J., Wu, D., Mao, M., Wang, W., & Zhang, G. (2015) · Decision Support Systems · doi:10.1016/j.dss.2015.03.008 · Cited by 1,578
Context‐Aware Recommender Systems
Adomavicius, G., Mobasher, B., Ricci, F., & Tuzhilin, A. (2011) · AI Magazine · doi:10.1609/aimag.v32i3.2364 · Cited by 1,355
Evaluating Recommendation Systems
Shani, G., & Gunawardana, A. (2011) · Recommender Systems Handbook · doi:10.1007/978-0-387-85820-3_8 · Cited by 1,325
Hybrid Web Recommender Systems
Burke, R. (2007) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-72079-9_12 · Cited by 1,173
Recommender Systems: An Introduction
Jannach, D., Zanker, M., Felfernig, A., & FRIEDRICH, G. E. (2010) · Cited by 1,097
Protein-to-protein interactions: Technologies, databases, and algorithms
Cannataro, M., Guzzi, P. H., & Veltri, P. (2010) · ACM Computing Surveys · doi:10.1145/1824795.1824796 · Cited by 620
Knowledge-based recommendation: a review of ontology-based recommender systems for e-learning
Tarus, J. K., Niu, Z., & Mustafa, G. (2018) · Artificial Intelligence Review · doi:10.1007/s10462-017-9539-5 · Cited by 490
Self-citationA taxonomy of sequential pattern mining algorithms
Mabroukeh, N. R., & Ezeife, C. I. (2010) · ACM Computing Surveys · doi:10.1145/1824795.1824798 · Cited by 400
Recommender Systems in Technology Enhanced Learning
Manouselis, N., Drachsler, H., Vuorikari, R., Hummel, H., & Koper, R. (2011) · Recommender Systems Handbook · doi:10.1007/978-0-387-85820-3_12 · Cited by 367
Barragáns-Martínez, A. B., Costa-Montenegro, E., Burguillo, J. C., Rey-López, M., Mikic-Fonte, F. A., & Peleteiro, A. (2010) · Information Sciences · doi:10.1016/j.ins.2010.07.024 · Cited by 353
A Social Network-Based Recommender System (SNRS)
He, J., & Chu, W. W. (2010) · Annals of Information Systems · doi:10.1007/978-1-4419-6287-4_4 · Cited by 264
Choi, K., Yoo, D., Kim, G., & Suh, Y. (2012) · Electronic Commerce Research and Applications · doi:10.1016/j.elerap.2012.02.004 · Cited by 239
Unified Collaborative and Content-Based Web Service Recommendation
Yao, L., Sheng, Q. Z., Ngu, A. H. H., Yu, J., & Segev, A. (2015) · IEEE Transactions on Services Computing · doi:10.1109/tsc.2014.2355842 · Cited by 198
SigTur/E-Destination: Ontology-based personalized recommendation of Tourism and Leisure Activities
Moreno, A., Valls, A., Isern, D., Marin, L., & Borràs, J. (2013) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2012.02.014 · Cited by 198
RecomMetz: A context-aware knowledge-based mobile recommender system for movie showtimes
Colombo-Mendoza, L. O., Valencia-García, R., Rodríguez-González, A., Alor-Hernández, G., & Samper-Zapater, J. J. (2015) · Expert Systems with Applications · doi:10.1016/j.eswa.2014.09.016 · Cited by 184
A hybrid fuzzy-based personalized recommender system for telecom products/services
Zhang, Z., Lin, H., Liu, K., Wu, D., Zhang, G., & Lu, J. (2013) · Information Sciences · doi:10.1016/j.ins.2013.01.025 · Cited by 183
A hybrid recommendation algorithm adapted in e-learning environments
Chen, W., Niu, Z., Zhao, X., & Li, Y. (2014) · World Wide Web · doi:10.1007/s11280-012-0187-z · Cited by 183
Self-citationThe use of sequential pattern mining to predict next prescribed medications
Wright, A. P., Wright, A. T., McCoy, A. B., & Sittig, D. F. (2015) · Journal of Biomedical Informatics · doi:10.1016/j.jbi.2014.09.003 · Cited by 173
Evaluating Recommender Systems for Technology Enhanced Learning: A Quantitative Survey
Erdt, M., Fernández, A., & Rensing, C. (2015) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2015.2438867 · Cited by 146
Ontology-Based Recommender Systems
Middleton, S. E., Roure, D. D., & Shadbolt, N. R. (2009) · Springer eBooks · doi:10.1007/978-3-540-92673-3_35 · Cited by 140
SMARTMUSEUM: A mobile recommender system for the Web of Data
Ruotsalo, T., Haav, K., Stoyanov, A., Roche, S., Fani, E., Deliai, R., Eetu Mäkelä, A., Kauppinen, T., & Eero Hyvönen, A. (2013) · Journal of Web Semantics · doi:10.1016/j.websem.2013.03.001 · Cited by 131
Web-Page Recommendation Based on Web Usage and Domain Knowledge
Nguyen, T. T. S., Lu, H., & Lü, J. (2014) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2013.78 · Cited by 122
Ranjbar, M., Moradi, P., Azami, M., & Jalili, M. (2015) · Engineering Applications of Artificial Intelligence · doi:10.1016/j.engappai.2015.08.010 · Cited by 91
Cold-Start Recommendation with Provable Guarantees: A Decoupled Approach
Barjasteh, I., Forsati, R., Ross, D., Esfahanian, A., & Radha, H. (2016) · IEEE Transactions on Knowledge and Data Engineering · doi:10.1109/tkde.2016.2522422 · Cited by 86
Cobos, C., Rodriguez, O., Rivera, J. J., Betancourt, J., Mendoza, M., León, E., & Herrera‐Viedma, E. (2013) · Information Processing & Management · doi:10.1016/j.ipm.2012.12.002 · Cited by 80
Najafabadi, M. K., & Mahrin, M. N. (2015) · Artificial Intelligence Review · doi:10.1007/s10462-015-9443-9 · Cited by 80
e‐Learning recommender system for a group of learners based on the unified learner profile approach
Dwivedi, P., & Bharadwaj, K. K. (2013) · Expert Systems · doi:10.1111/exsy.12061 · Cited by 69
A hybrid collaborative filtering recommendation mechanism for P2P networks
Liu, Z., Qu, W., Li, H., & Xie, C. (2010) · Future Generation Computer Systems · doi:10.1016/j.future.2010.04.002 · Cited by 60
Measuring learner's performance in e-learning recommender systems
Ghauth, K. I., & Abdullah, N. A. (2010) · Australasian Journal of Educational Technology · doi:10.14742/ajet.1041 · Cited by 60
A Hybrid Trust-Based Recommender System for Online Communities of Practice
Zheng, X., Chen, C., Hung, J.-L., He, W., Hong, F., & Lin, Z. (2015) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2015.2419262 · Cited by 59
A Framework of Semantic Recommender System for e-Learning
Fraihat, S., & Shambour, Q. Y. (2015) · Journal of Software · doi:10.17706/jsw.10.3.317-330 · Cited by 49
An efficient approach for finding weighted sequential patterns from sequence databases
Lan, G.-C., Hong, T., & Lee, H.-Y. (2014) · Applied Intelligence · doi:10.1007/s10489-014-0530-4 · Cited by 45
A hybrid approach of topic model and matrix factorization based on two-step recommendation framework
Zhao, X., Niu, Z., Chen, W., Shi, C., Niu, K., & Liu, D. (2014) · Journal of Intelligent Information Systems · doi:10.1007/s10844-014-0334-3 · Cited by 42
Self-citationThe development of an Ontology-Based Adaptive Personalized Recommender System
Pan, P.-Y., Wang, C.-H., Horng, G.-J., & Cheng, S.-T. (2010) · International Conference on Electronics and Information Engineering · doi:10.1109/iceie.2010.5559842 · Cited by 31
Towards Guided Personal Learning Environments: Concept, Theory, and Practice
Shaikh, Z. A., & Khoja, S. A. (2014) · IEEE International Conference on Advanced Learning Technologies (ICALT) · doi:10.1109/icalt.2014.230 · Cited by 14
Ahmad, I., Qazi, W. M., Khurshid, A., Ahmad, M., Hoessli, D. C., Khawaja, I., Choudhary, M. I., Shakoori, A. R., & Nasir‐ud‐Din (2008) · PROTEOMICS · doi:10.1002/pmic.200700657 · Cited by 11
Project-Based Collaborative Learning Environment with Context-Aware Educational Services
Jeremić, Z., Jovanović, J., Gašević, D., & Hatala, M. (2009) · Lecture notes in computer science · doi:10.1007/978-3-642-04636-0_42 · Cited by 10
Mota, D., de Carvalho, C. V., & Reis, L. P. (2014) · IEEE Frontiers in Education Conference (FIE) · doi:10.1109/fie.2014.7044479 · Cited by 9
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
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.