{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,13]],"date-time":"2026-01-13T21:25:14Z","timestamp":1768339514556,"version":"3.49.0"},"reference-count":27,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2019,11,8]],"date-time":"2019-11-08T00:00:00Z","timestamp":1573171200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>The growth of the Internet has increased the amount of data and information available to any person at any time. Recommendation Systems help users find the items that meet their preferences, among the large number of items available. Techniques such as collaborative filtering and content-based recommenders have played an important role in the implementation of recommendation systems. In the last few years, other techniques, such as, ontology-based recommenders, have gained significance when reffering better active user recommendations; however, building an ontology-based recommender is an expensive process, which requires considerable skills in Knowledge Engineering. This paper presents a new hybrid approach that combines the simplicity of collaborative filtering with the efficiency of the ontology-based recommenders. The experimental evaluation demonstrates that the proposed approach presents higher quality recommendations when compared to collaborative filtering. The main improvement is verified on the results regarding the products, which, in spite of belonging to unknown categories to the users, still match their preferences and become recommended.<\/jats:p>","DOI":"10.3390\/a12110239","type":"journal-article","created":{"date-parts":[[2019,11,8]],"date-time":"2019-11-08T11:30:19Z","timestamp":1573212619000},"page":"239","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["A Hybrid Ontology-Based Recommendation System in e-Commerce"],"prefix":"10.3390","volume":"12","author":[{"given":"M\u00e1rcio","family":"Guia","sequence":"first","affiliation":[{"name":"Coimbra Polytechnic \u2013Instituto Superior de Engenharia de Coimbra (ISEC), 3030-190 Coimbra, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5741-6897","authenticated-orcid":false,"given":"Rodrigo Rocha","family":"Silva","sequence":"additional","affiliation":[{"name":"FATEC Mogi das Cruzes, S\u00e3o Paulo Technological College, Mogi das Cruzes 08773-600, Brazil"},{"name":"Centre of Informatics and Systems of University of Coimbra (CISUC), 3030-290 Coimbra, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9660-2011","authenticated-orcid":false,"given":"Jorge","family":"Bernardino","sequence":"additional","affiliation":[{"name":"Coimbra Polytechnic \u2013Instituto Superior de Engenharia de Coimbra (ISEC), 3030-190 Coimbra, Portugal"},{"name":"Centre of Informatics and Systems of University of Coimbra (CISUC), 3030-290 Coimbra, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2019,11,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"126","DOI":"10.1016\/j.engappai.2019.03.020","article-title":"The state-of-the-art in expert recommendation systems","volume":"82","author":"Balafar","year":"2019","journal-title":"Eng. Appl. Artif. Intell."},{"key":"ref_2","unstructured":"Cutolo, A., Aniello, G.D., Orciuoli, F., Salerno, U., Pettinati, F., and Sansonetti, G. (2013, January 12\u201316). An Ontology-Based Recommender System in E-Commerce. Proceedings of the 2nd International Workshop on Recommender Systems meet Big Data & Semantic Technologies, Hong Kong, China."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Feng, J., Feng, X., Zhang, N., and Peng, J. (2018). An improved collaborative filtering method based on similarity. PLoS ONE, 13.","DOI":"10.1371\/journal.pone.0204003"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"21","DOI":"10.1007\/s10462-017-9539-5","article-title":"Knowledge-based recommendation: A review of ontology-based recommender systems for e-learning","volume":"50","author":"Tarus","year":"2018","journal-title":"Artif. Intell. Rev."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"199","DOI":"10.1006\/knac.1993.1008","article-title":"A translation approach to portable ontology specifications","volume":"5","author":"Gruber","year":"1993","journal-title":"Knowl. Acquis."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"103642","DOI":"10.1016\/j.compedu.2019.103642","article-title":"Review of ontology-based recommender systems in e-learning","volume":"142","author":"George","year":"2019","journal-title":"Comput. Educ."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Obeid, C., Lahoud, I., el Khoury, H., and Champin, P.-A. (2018, January 23\u201327). Ontology-Based Recommender System in Higher Education. Proceedings of the Companion Proceedings of The Web Conference 2018, Lyon, France.","DOI":"10.1145\/3184558.3191533"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"012020","DOI":"10.1088\/1742-6596\/1192\/1\/012020","article-title":"Ontology-based conversational recommender system for recommending laptop","volume":"1192","author":"Ayundhita","year":"2019","journal-title":"J. Phys. Conf. Ser."},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Zehra, S., Wasi, S., Jami, I., Nazir, A., Khan, A., and Waheed, N. (2017, January 1\u20133). Ontology-Based Sentiment Analysis Model for Recommendation Systems. Proceedings of the 9th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2017), Funchal, Portugal.","DOI":"10.5220\/0006491101550160"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Rodrigues, M., Silva, R.R., and Bernardino, J. (2018). Linking Open Descriptions of Social Events (LODSE): A new ontology for social event classification. Information, 9.","DOI":"10.3390\/info9070164"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1007\/978-3-642-10871-6_11","article-title":"LODE: Linking open descriptions of events","volume":"5926","author":"Shaw","year":"2009","journal-title":"Asian Semant. Web Conf."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"331","DOI":"10.1023\/A:1021240730564","article-title":"Hybrid Recommender Systems: Survey and Experiments","volume":"12","author":"Burke","year":"2002","journal-title":"User Model. User Adapt. Interact."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1487","DOI":"10.3233\/IDA-163209","article-title":"Hybrid recommender systems: A systematic literature review","volume":"21","author":"Morisio","year":"2017","journal-title":"Intell. Data Anal."},{"key":"ref_14","first-page":"1","article-title":"A trust-based collaborative filtering algorithm for E-commerce recommendation system","volume":"10","author":"Jiang","year":"2018","journal-title":"J. Ambient Intell. Humaniz. Comput."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Deng, F. (2015, January 1\u20133). Utility-Based Recommender Systems Using Implicit Utility and Genetic Algorithm. Proceedings of the International Conference on Mechatronics, Electronic, Industrial and Control Engineering (MEIC 2015), Beijing, China.","DOI":"10.2991\/meic-15.2015.197"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"963","DOI":"10.32628\/CSEIT1952268","article-title":"Nearby Product Recommendation System Based on Users Rating","volume":"5","author":"Jyoti","year":"2019","journal-title":"Int. J. Sci. Res. Comput. Sci. Eng. Inf. Technol."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Liu, Y., Nie, J., Xu, L., Chen, Y., and Xu, B. (2018, January 19). Clothing Recommendation System Based on Advanced User-Based Collaborative Filtering Algorithm. Proceedings of the International Conference on Signal and Information Processing, Networking and Computers, Springer, Singapore.","DOI":"10.1007\/978-981-10-7521-6_53"},{"key":"ref_18","first-page":"3258916","article-title":"Developing a Contextually Personalized Hybrid Recommender System","volume":"2018","author":"Bozanta","year":"2018","journal-title":"Mob. Inf. Syst."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"507","DOI":"10.1016\/j.eswa.2017.09.058","article-title":"A recommender system based on collaborative filtering using ontology and dimensionality reduction techniques","volume":"92","author":"Nilashi","year":"2018","journal-title":"Expert Syst. Appl."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"14","DOI":"10.1016\/j.dss.2019.02.008","article-title":"Explaining customer ratings and recommendations by combining qualitative and quantitative user generated contents","volume":"119","author":"Chatterjee","year":"2019","journal-title":"Decis. Support Syst."},{"key":"ref_21","unstructured":"McAuley, J. (2019, April 10). Amazon Review Data. Available online: http:\/\/jmcauley.ucsd.edu\/data\/amazon\/."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Sharma, S. (2015). An extended classification and comparison of NoSQL big data models. arXiv.","DOI":"10.1504\/IJBDI.2015.070602"},{"key":"ref_23","first-page":"17","article-title":"Which NoSQL Database? A Performance Overview","volume":"1","author":"Abramova","year":"2014","journal-title":"Open J. Databases"},{"key":"ref_24","unstructured":"Noy, N., and McGuinness, D.L. (2011). Ontology Development 101: A Guide to Creating Your First Ontology, Technical Report for Stanford Knowledge Systems Laboratory and Stanford Medical Informatics."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"93","DOI":"10.1017\/S0269888900007797","article-title":"Ontologies: Principles, methods and applications","volume":"11","author":"Uschold","year":"1996","journal-title":"Knowl. Eng. Rev."},{"key":"ref_26","first-page":"1930","article-title":"A Comparative Study of Stemming Algorithms","volume":"2","author":"Jivani","year":"2011","journal-title":"Int. J. Comput. Technol. Appl."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"262","DOI":"10.7763\/LNSE.2014.V2.134","article-title":"Stemming and Lemmatization: A Comparison of Retrieval Performances","volume":"2","author":"Balakrishnan","year":"2014","journal-title":"Lect. Notes Softw. Eng."}],"container-title":["Algorithms"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1999-4893\/12\/11\/239\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:32:51Z","timestamp":1760189571000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1999-4893\/12\/11\/239"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,11,8]]},"references-count":27,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2019,11]]}},"alternative-id":["a12110239"],"URL":"https:\/\/doi.org\/10.3390\/a12110239","relation":{},"ISSN":["1999-4893"],"issn-type":[{"value":"1999-4893","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,11,8]]}}}