{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,21]],"date-time":"2026-03-21T09:15:49Z","timestamp":1774084549814,"version":"3.50.1"},"reference-count":44,"publisher":"Springer Science and Business Media LLC","issue":"9","license":[{"start":{"date-parts":[[2024,2,7]],"date-time":"2024-02-07T00:00:00Z","timestamp":1707264000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,2,7]],"date-time":"2024-02-07T00:00:00Z","timestamp":1707264000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Supercomput"],"published-print":{"date-parts":[[2024,6]]},"DOI":"10.1007\/s11227-023-05874-0","type":"journal-article","created":{"date-parts":[[2024,2,7]],"date-time":"2024-02-07T06:02:20Z","timestamp":1707285740000},"page":"12102-12122","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Ontology-based recommender system: a deep learning approach"],"prefix":"10.1007","volume":"80","author":[{"given":"Seyed Jalalaldin","family":"Gharibi","sequence":"first","affiliation":[]},{"given":"Karamollah","family":"BagheriFard","sequence":"additional","affiliation":[]},{"given":"Hamid","family":"Parvin","sequence":"additional","affiliation":[]},{"given":"Samad","family":"Nejatian","sequence":"additional","affiliation":[]},{"given":"S. Hadi","family":"Yaghoubyan","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,2,7]]},"reference":[{"key":"5874_CR1","doi-asserted-by":"crossref","unstructured":"Obeid C, Lahoud I, El Khoury H, Champin PA (2018) Ontology-based recommender system in higher education. In Companion Proceedings of the Web Conference pp 1031\u20131034","DOI":"10.1145\/3184558.3191533"},{"key":"5874_CR2","doi-asserted-by":"publisher","first-page":"103642","DOI":"10.1016\/j.compedu.2019.103642","volume":"142","author":"G George","year":"2019","unstructured":"George G, Lal AM (2019) Review of ontology-based recommender systems in e-learning. Comput Educ 142:103642","journal-title":"Comput Educ"},{"key":"5874_CR3","doi-asserted-by":"publisher","first-page":"769","DOI":"10.1016\/j.future.2020.09.030","volume":"115","author":"M Arafeh","year":"2021","unstructured":"Arafeh M, Ceravolo P, Mourad A, Damiani E, Bellini E (2021) Ontology based recommender system using social network data. Futur Gener Comput Syst 115:769\u2013779","journal-title":"Futur Gener Comput Syst"},{"issue":"6","key":"5874_CR4","doi-asserted-by":"publisher","first-page":"1410","DOI":"10.1109\/TKDE.2011.263","volume":"25","author":"CD Wang","year":"2011","unstructured":"Wang CD, Lai JH, Huang D, Zheng WS (2011) SVStream: a support vector-based algorithm for clustering data streams. IEEE Trans Knowl Data Eng 25(6):1410\u20131424","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"5874_CR5","doi-asserted-by":"crossref","unstructured":"Abdelwahab A, Sekiya H, Matsuba I, Horiuchi Y, Kuroiwa S, Nishida M (2009) An efficient collaborative filtering algorithm using SVD-free latent semantic indexing and particle swarm optimization. In International Conference on Natural Language Processing and Knowledge Engineering. pp 1\u20134. IEEE","DOI":"10.1109\/NLPKE.2009.5313754"},{"key":"5874_CR6","doi-asserted-by":"crossref","unstructured":"El Aissaoui O, Oughdir L (2020) A learning style-based ontology matching to enhance learning resources recommendation. In 1st International Conference on Innovative Research in Applied Science, Engineering and Technology (IRASET) pp 1\u20137. IEEE","DOI":"10.1109\/IRASET48871.2020.9092142"},{"key":"5874_CR7","doi-asserted-by":"crossref","unstructured":"Assami S, Daoudi N, Ajhoun R (2019) Ontology-based modeling for a personalized MOOC recommender system. In Information systems and technologies to support learning: proceedings of EMENA-ISTL 2018 2 pp 21\u201328. Springer international publishing","DOI":"10.1007\/978-3-030-03577-8_3"},{"issue":"7","key":"5874_CR8","doi-asserted-by":"publisher","first-page":"749","DOI":"10.1117\/12.7977031","volume":"28","author":"YS Fong","year":"1989","unstructured":"Fong YS, Pomalaza-Raez CA, Wang XH (1989) Comparison study of nonlinear filters in image processing applications. Opt Eng 28(7):749\u2013760","journal-title":"Opt Eng"},{"issue":"16","key":"5874_CR9","doi-asserted-by":"publisher","first-page":"7370","DOI":"10.1016\/j.eswa.2014.06.007","volume":"41","author":"J Borr\u00e0s","year":"2014","unstructured":"Borr\u00e0s J, Moreno A, Valls A (2014) Intelligent tourism recommender systems: a survey. Expert Syst Appl 41(16):7370\u20137389","journal-title":"Expert Syst Appl"},{"key":"5874_CR10","doi-asserted-by":"crossref","unstructured":"Su P, Ye H (2009) An item based collaborative filtering recommendation algorithm using rough set prediction. In International Joint Conference on Artificial Intelligence. pp 308\u2013311 IEEE","DOI":"10.1109\/JCAI.2009.155"},{"issue":"8","key":"5874_CR11","doi-asserted-by":"publisher","first-page":"7319","DOI":"10.1016\/j.eswa.2012.01.086","volume":"39","author":"M Batet","year":"2012","unstructured":"Batet M, Moreno A, S\u00e1nchez D, Isern D, Valls A (2012) Turist@: agent-based personalised recommendation of tourist activities. Expert Syst Appl 39(8):7319\u20137329","journal-title":"Expert Syst Appl"},{"issue":"4","key":"5874_CR12","doi-asserted-by":"publisher","first-page":"285","DOI":"10.1023\/A:1022850703159","volume":"19","author":"M Montaner","year":"2003","unstructured":"Montaner M, L\u00f3pez B, De La Rosa JL (2003) A taxonomy of recommender agents on the internet. Artif Intell Rev 19(4):285\u2013330","journal-title":"Artif Intell Rev"},{"issue":"4","key":"5874_CR13","doi-asserted-by":"publisher","first-page":"2065","DOI":"10.1016\/j.eswa.2013.09.005","volume":"41","author":"B Lika","year":"2014","unstructured":"Lika B, Kolomvatsos K, Hadjiefthymiades S (2014) Facing the cold start problem in recommender systems. Expert Syst Appl 41(4):2065\u20132073","journal-title":"Expert Syst Appl"},{"issue":"2","key":"5874_CR14","doi-asserted-by":"publisher","first-page":"105","DOI":"10.2498\/cit.1002223","volume":"22","author":"MH Nadimi-Shahraki","year":"2014","unstructured":"Nadimi-Shahraki MH, Bahadorpour M (2014) Cold-start problem in collaborative recommender systems: efficient methods based on ask-to-rate technique. J Comput Inf Technol 22(2):105\u2013113","journal-title":"J Comput Inf Technol"},{"key":"5874_CR15","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1016\/j.eswa.2016.02.013","volume":"56","author":"C He","year":"2016","unstructured":"He C, Parra D, Verbert K (2016) Interactive recommender systems: a survey of the state of the art and future research challenges and opportunities. Expert Syst Appl 56:9\u201327","journal-title":"Expert Syst Appl"},{"key":"5874_CR16","doi-asserted-by":"publisher","first-page":"113248","DOI":"10.1016\/j.eswa.2020.113248","volume":"149","author":"S Natarajan","year":"2020","unstructured":"Natarajan S, Vairavasundaram S, Natarajan S, Gandomi AH (2020) Resolving data sparsity and cold start problem in collaborative filtering recommender system using linked open data. Expert Syst Appl 149:113248","journal-title":"Expert Syst Appl"},{"issue":"4","key":"5874_CR17","doi-asserted-by":"publisher","first-page":"529","DOI":"10.1016\/j.ipm.2018.03.004","volume":"54","author":"LAG Camacho","year":"2018","unstructured":"Camacho LAG, Alves-Souza SN (2018) Social network data to alleviate cold-start in recommender system: a systematic review. Inf Process Manage 54(4):529\u2013544","journal-title":"Inf Process Manage"},{"key":"5874_CR18","doi-asserted-by":"publisher","first-page":"87","DOI":"10.1016\/j.is.2014.10.001","volume":"58","author":"LH Son","year":"2016","unstructured":"Son LH (2016) Dealing with the new user cold-start problem in recommender systems: a comparative review. Inf Syst 58:87\u2013104","journal-title":"Inf Syst"},{"issue":"1","key":"5874_CR19","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s13278-020-0626-2","volume":"10","author":"N Idrissi","year":"2020","unstructured":"Idrissi N, Zellou A (2020) A systematic literature review of sparsity issues in recommender systems. Soc Netw Anal Min 10(1):1\u201323","journal-title":"Soc Netw Anal Min"},{"issue":"3","key":"5874_CR20","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3073565","volume":"50","author":"MM Khan","year":"2017","unstructured":"Khan MM, Ibrahim R, Ghani I (2017) Cross domain recommender systems: a systematic literature review. ACM Comput Surv (CSUR) 50(3):1\u201334","journal-title":"ACM Comput Surv (CSUR)"},{"issue":"1","key":"5874_CR21","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3158369","volume":"52","author":"S Zhang","year":"2019","unstructured":"Zhang S, Yao L, Sun A, Tay Y (2019) Deep learning based recommender system: a survey and new perspectives. ACM Comput Surv (CSUR) 52(1):1\u201338","journal-title":"ACM Comput Surv (CSUR)"},{"issue":"12","key":"5874_CR22","doi-asserted-by":"publisher","first-page":"1211","DOI":"10.3390\/app7121211","volume":"7","author":"K Haruna","year":"2017","unstructured":"Haruna K, Akmar Ismail M, Suhendroyono S, Damiasih D, Pierewan AC, Chiroma H, Herawan T (2017) Context-aware recommender system: a review of recent developmental process and future research direction. Appl Sci 7(12):1211","journal-title":"Appl Sci"},{"key":"5874_CR23","doi-asserted-by":"crossref","unstructured":"Xu B, Bu J, Chen C, Cai D (2012) An exploration of improving collaborative recommender systems via user-item subgroups. In Proceedings of the 21st International Conference on World Wide Web pp 21\u201330","DOI":"10.1145\/2187836.2187840"},{"key":"5874_CR24","doi-asserted-by":"crossref","unstructured":"McAuley J, Targett C, Shi Q, Van Den Hengel A (2015) Image-based recommendations on styles and substitutes. In Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval pp 43\u201352","DOI":"10.1145\/2766462.2767755"},{"key":"5874_CR25","unstructured":"Gorunescu F (2011) Data mining: concepts, models and techniques Vol. 12 Springer Science and Business Media"},{"issue":"1","key":"5874_CR26","first-page":"17","volume":"2","author":"S Vijiyarani","year":"2013","unstructured":"Vijiyarani S, Sudha S (2013) Disease prediction in data mining technique\u2013a survey. Int J Comput Appl Inf Technol 2(1):17\u201321","journal-title":"Int J Comput Appl Inf Technol"},{"key":"5874_CR27","doi-asserted-by":"crossref","unstructured":"Lemnaru C, Firte AA, Potolea R (2011) Static and dynamic user type identification in adaptive e-learning with unsupervised methods. In 2011 IEEE 7th International Conference on Intelligent Computer Communication and Processing pp 11\u201318 IEEE","DOI":"10.1109\/ICCP.2011.6047838"},{"key":"5874_CR28","doi-asserted-by":"crossref","unstructured":"Sarwar B, Karypis G, Konstan J, Riedl J (2000) Analysis of recommendation algorithms for e-commerce. In Proceedings of the 2nd ACM Conference on Electronic Commerce pp 158\u2013167","DOI":"10.1145\/352871.352887"},{"key":"5874_CR29","doi-asserted-by":"crossref","unstructured":"Schafer JB, Konstan J, Riedl J (1999) Recommender systems in e-commerce. In Proceedings of the 1st ACM Conference on Electronic Commerce pp 158\u2013166","DOI":"10.1145\/336992.337035"},{"issue":"6","key":"5874_CR30","doi-asserted-by":"publisher","first-page":"734","DOI":"10.1109\/TKDE.2005.99","volume":"17","author":"G Adomavicius","year":"2005","unstructured":"Adomavicius G, Tuzhilin A (2005) Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions. IEEE Trans Knowl Data Eng 17(6):734\u2013749","journal-title":"IEEE Trans Knowl Data Eng"},{"issue":"11","key":"5874_CR31","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1007\/s10916-022-01867-3","volume":"46","author":"R Lebre","year":"2022","unstructured":"Lebre R, Pinho E, Jesus R, Basti\u00e3o L, Costa C (2022) Dicoogle open source: the establishment of a new paradigm in medical imaging. J Med Syst 46(11):77","journal-title":"J Med Syst"},{"key":"5874_CR32","doi-asserted-by":"crossref","unstructured":"Mizuochi M, Kanezaki A, Harada T (2014) Clothing retrieval based on local similarity with multiple images. In Proceedings of the 22nd ACM International Conference on Multimedia pp 1165\u20131168","DOI":"10.1145\/2647868.2655021"},{"key":"5874_CR33","doi-asserted-by":"crossref","unstructured":"Azodinia MR, Hajdu A (2015) A recommender system that deals with items having an image as well as quantitative features. In IEEE 9th international symposium on intelligent signal processing (WISP) proceedings pp 1\u20136 IEEE","DOI":"10.1109\/WISP.2015.7139167"},{"key":"5874_CR34","unstructured":"Boutemedjet S, Ziou D (2010) Using images in context-aware recommender systems. In 1 st International workshop on adaptation, personalization and recommendation in the social-semantic web (APRESW 2010)"},{"key":"5874_CR35","doi-asserted-by":"publisher","first-page":"3757","DOI":"10.1007\/s10489-020-01939-2","volume":"51","author":"O Mabrouk","year":"2021","unstructured":"Mabrouk O, Hlaoua L, Omri MN (2021) Exploiting ontology information in fuzzy SVM social media profile classification. Appl Intell 51:3757\u20133774","journal-title":"Appl Intell"},{"issue":"1","key":"5874_CR36","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1007\/s13278-023-01066-z","volume":"13","author":"I Fadhli","year":"2023","unstructured":"Fadhli I, Hlaoua L, Omri MN (2023) Deep learning-based credibility conversation detection approaches from social network. Soc Netw Anal Min 13(1):57","journal-title":"Soc Netw Anal Min"},{"issue":"8","key":"5874_CR37","doi-asserted-by":"publisher","first-page":"6043","DOI":"10.1007\/s00521-022-07986-9","volume":"35","author":"O Haddad","year":"2023","unstructured":"Haddad O, Fkih F, Omri MN (2023) Toward a prediction approach based on deep learning in big data analytics. Neural Comput Appl 35(8):6043\u20136063","journal-title":"Neural Comput Appl"},{"issue":"1","key":"5874_CR38","doi-asserted-by":"publisher","first-page":"40","DOI":"10.1007\/s13278-023-01042-7","volume":"13","author":"MA Jassim","year":"2023","unstructured":"Jassim MA, Abd DH, Omri MN (2023) Machine learning-based new approach to films review. Soc Netw Anal Min 13(1):40","journal-title":"Soc Netw Anal Min"},{"issue":"13","key":"5874_CR39","doi-asserted-by":"publisher","first-page":"9437","DOI":"10.1007\/s00521-023-08359-6","volume":"35","author":"MA Jassim","year":"2023","unstructured":"Jassim MA, Abd DH, Omri MN (2023) A survey of sentiment analysis from film critics based on machine learning, lexicon and hybridization. Neural Comput Appl 35(13):9437\u20139461","journal-title":"Neural Comput Appl"},{"key":"5874_CR40","first-page":"1","volume":"18","author":"S Ouni","year":"2023","unstructured":"Ouni S, Fkih F, Omri MN (2023) A survey of machine learning-based author profiling from texts analysis in social networks. Multimed Tools Appl 18:1\u201334","journal-title":"Multimed Tools Appl"},{"issue":"1","key":"5874_CR41","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1007\/s10462-017-9539-5","volume":"50","author":"JK Tarus","year":"2018","unstructured":"Tarus JK, Niu Z, Mustafa G (2018) Knowledge-based recommendation: a review of ontology-based recommender systems for e-learning. Artif Intell Rev 50(1):21\u201348","journal-title":"Artif Intell Rev"},{"issue":"9","key":"5874_CR42","first-page":"7645","volume":"34","author":"F Fkih","year":"2022","unstructured":"Fkih F (2022) Similarity measures for collaborative filtering-based recommender systems: review and experimental comparison. J King Saud Uni-Comput Inf Sci 34(9):7645\u20137669","journal-title":"J King Saud Uni-Comput Inf Sci"},{"key":"5874_CR43","doi-asserted-by":"crossref","unstructured":"Zhang T, Cheng D, He Y, Chen Z, Dai X, Xiong L, Wen W (2023) NASRec: weight sharing neural architecture search for recommender systems. In Proceedings of the ACM Web Conference pp 1199\u20131207)","DOI":"10.1145\/3543507.3583446"},{"key":"5874_CR44","doi-asserted-by":"publisher","first-page":"222","DOI":"10.1016\/j.ins.2022.02.045","volume":"596","author":"J Zhao","year":"2022","unstructured":"Zhao J, Li H, Qu L, Zhang Q, Sun Q, Huo H, Gong M (2022) DCFGAN: an adversarial deep reinforcement learning framework with improved negative sampling for session-based recommender systems. Inf Sci 596:222\u2013235","journal-title":"Inf Sci"}],"container-title":["The Journal of Supercomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-023-05874-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11227-023-05874-0\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-023-05874-0.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,4]],"date-time":"2024-06-04T10:37:32Z","timestamp":1717497452000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11227-023-05874-0"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,2,7]]},"references-count":44,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2024,6]]}},"alternative-id":["5874"],"URL":"https:\/\/doi.org\/10.1007\/s11227-023-05874-0","relation":{},"ISSN":["0920-8542","1573-0484"],"issn-type":[{"value":"0920-8542","type":"print"},{"value":"1573-0484","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,2,7]]},"assertion":[{"value":"21 December 2023","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 February 2024","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"All of the authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"This article does not contain any studies with human participants or animals performed by any of the authors.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}}]}}