{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,30]],"date-time":"2026-03-30T14:26:52Z","timestamp":1774880812651,"version":"3.50.1"},"publisher-location":"Cham","reference-count":31,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783030869595","type":"print"},{"value":"9783030869601","type":"electronic"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021]]},"DOI":"10.1007\/978-3-030-86960-1_33","type":"book-chapter","created":{"date-parts":[[2021,9,10]],"date-time":"2021-09-10T07:02:59Z","timestamp":1631257379000},"page":"471-482","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Inference Engines Performance in Reasoning Tasks for Intelligent Tutoring Systems"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7296-2538","authenticated-orcid":false,"given":"Oleg A.","family":"Sychev","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0661-4284","authenticated-orcid":false,"given":"Anton","family":"Anikin","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1216-610X","authenticated-orcid":false,"given":"Mikhail","family":"Denisov","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,9,11]]},"reference":[{"key":"33_CR1","unstructured":"ARQ - A SPARQL Processor for Jena. https:\/\/jena.apache.org\/documentation\/\/query\/. Accessed 30 Apr 2021"},{"key":"33_CR2","unstructured":"DLV System. http:\/\/www.dlvsystem.com\/dlv\/. Accessed 30 Apr 2021"},{"key":"33_CR3","unstructured":"Jena - a free and open source Java framework for building Semantic Web and Linked Data applications. https:\/\/jena.apache.org. Accessed 30 Apr 2021"},{"key":"33_CR4","unstructured":"library(semweb\/rdf11): The RDF database. https:\/\/www.swi-prolog.org\/pldoc\/man?section=semweb-rdf11. Accessed 30 Apr 2021"},{"key":"33_CR5","unstructured":"SPARQL Update. A language for updating RDF graphs. W3C Member Submission 15 July 2008. https:\/\/www.w3.org\/Submission\/SPARQL-Update\/. Accessed 30 Apr 2021"},{"key":"33_CR6","unstructured":"SWRL: A Semantic Web Rule Language Combining OWL and RuleML. W3C Member Submission 21 May 2004. https:\/\/www.w3.org\/Submission\/SWRL\/. Accessed 30 Apr 2021"},{"key":"33_CR7","doi-asserted-by":"publisher","unstructured":"Adrian, W.T., et al.: The ASP System DLV: Advancements and Applications. KI - K\u00fcnstliche Intelligenz, pp. 177\u2013179 (2018). https:\/\/doi.org\/10.1007\/s13218-018-0533-0","DOI":"10.1007\/s13218-018-0533-0"},{"key":"33_CR8","unstructured":"Berners-Lee, T.: Cwm: General-purpose data processor for the semantic web. http:\/\/www.w3.org\/2000\/10\/swap\/doc\/cwm (2000). Accessed 30 Apr 2021"},{"key":"33_CR9","doi-asserted-by":"publisher","unstructured":"Brewka, G., Eiter, T., Truszczy\u0144ski, M.: Answer set programming at a glance. Commun. ACM 54(12), 93\u2013103 (2011). https:\/\/doi.org\/10.1145\/2043174.2043195","DOI":"10.1145\/2043174.2043195"},{"key":"33_CR10","doi-asserted-by":"publisher","unstructured":"Calegari, R., Ciatto, G., Mascardi, V., Omicini, A.: Logic-based technologies for multi-agent systems: a systematic literature review. Autonomous Agents Multi-Agent Syst. 35(1), 1\u201367 (2020). https:\/\/doi.org\/10.1007\/s10458-020-09478-3","DOI":"10.1007\/s10458-020-09478-3"},{"key":"33_CR11","doi-asserted-by":"publisher","unstructured":"Chang, M., D\u2019Aniello, G., Gaeta, M., Orciuoli, F., Sampson, D., Simonelli, C.: Building ontology-driven tutoring models for intelligent tutoring systems using data mining. IEEE Access 8, 48151\u201348162 (2020). https:\/\/doi.org\/10.1109\/access.2020.2979281","DOI":"10.1109\/access.2020.2979281"},{"key":"33_CR12","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"145","DOI":"10.1007\/11546207_12","volume-title":"Logic Programming and Nonmonotonic Reasoning","author":"A Cort\u00e9s-Calabuig","year":"2005","unstructured":"Cort\u00e9s-Calabuig, A., Denecker, M., Arieli, O., Van Nuffelen, B., Bruynooghe, M.: On the local closed-world assumption of data-sources. In: Baral, C., Greco, G., Leone, N., Terracina, G. (eds.) LPNMR 2005. LNCS (LNAI), vol. 3662, pp. 145\u2013157. Springer, Heidelberg (2005). https:\/\/doi.org\/10.1007\/11546207_12"},{"key":"33_CR13","doi-asserted-by":"crossref","unstructured":"Demaidi, M.N., Gaber, M.M., Filer, N.: OntoPeFeGe: ontology-based personalized feedback generator. IEEE Access 6, 31644\u201331664 (2018)","DOI":"10.1109\/ACCESS.2018.2846398"},{"key":"33_CR14","doi-asserted-by":"publisher","unstructured":"Dermeval, D., Albuquerque, J., Bittencourt, I.I., Isotani, S., Silva, A.P., Vassileva, J.: GaTO: An ontological model to apply gamification in intelligent tutoring systems. Frontiers Artif. Intell. 2, July 2019. https:\/\/doi.org\/10.3389\/frai.2019.00013. https:\/\/doi.org\/10.3389\/frai.2019.00013","DOI":"10.3389\/frai.2019.00013"},{"key":"33_CR15","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"270","DOI":"10.1007\/978-3-030-49663-0_31","volume-title":"Intelligent Tutoring Systems","author":"A Dougalis","year":"2020","unstructured":"Dougalis, A., Plexousakis, D.: AFFLOG: A Logic Based Affective Tutoring System. In: Kumar, V., Troussas, C. (eds.) ITS 2020. LNCS, vol. 12149, pp. 270\u2013274. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-49663-0_31"},{"key":"33_CR16","doi-asserted-by":"crossref","unstructured":"Franzoni, V., Biondi, G., Milani, A.: Emotional sounds of crowds: spectrogram-based analysis using deep learning. Multimed. Tools Appl. 79(47\u201348), 36063\u201336075 (2020)","DOI":"10.1007\/s11042-020-09428-x"},{"key":"33_CR17","doi-asserted-by":"crossref","unstructured":"Franzoni, V., Milani, A., Mengoni, P., Piccinato, F.: Artificial intelligence visual metaphors in e-learning interfaces for learning analytics. Appl. Sci. 10(20), 7195 (2020)","DOI":"10.3390\/app10207195"},{"key":"33_CR18","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"293","DOI":"10.1007\/978-3-030-58802-1_22","volume-title":"Computational Science and Its Applications \u2013 ICCSA 2020","author":"V Franzoni","year":"2020","unstructured":"Franzoni, V., Pallottelli, S., Milani, A.: Reshaping higher education with e-studium, a 10-years capstone in academic computing. In: Gervasi, O., et al. (eds.) ICCSA 2020. LNCS, vol. 12250, pp. 293\u2013303. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58802-1_22"},{"key":"33_CR19","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"260","DOI":"10.1007\/978-3-540-72200-7_23","volume-title":"Logic Programming and Nonmonotonic Reasoning","author":"M Gebser","year":"2007","unstructured":"Gebser, M., Kaufmann, B., Neumann, A., Schaub, T.: clasp: a conflict-driven answer set solver. In: Baral, C., Brewka, G., Schlipf, J. (eds.) LPNMR 2007. LNCS (LNAI), vol. 4483, pp. 260\u2013265. Springer, Heidelberg (2007). https:\/\/doi.org\/10.1007\/978-3-540-72200-7_23"},{"key":"33_CR20","unstructured":"Gebser, M., Kaminski, R., Kaufmann, B., Schaub, T.: Multi-shot ASP solving with clingo. CoRR abs\/1705.09811 (2017)"},{"key":"33_CR21","doi-asserted-by":"publisher","unstructured":"Janhunen, T.: Cross-Translating Answer Set Programs Using the ASPTOOLS Collection. KI - K\u00fcnstliche Intelligenz 32(2-3), 183\u2013184 (2018). https:\/\/doi.org\/10.1007\/s13218-018-0529-9","DOI":"10.1007\/s13218-018-0529-9"},{"key":"33_CR22","doi-asserted-by":"publisher","unstructured":"Kultsova, M., Anikin, A., Zhukova, I., Dvoryankin, A.: Ontology-based learning content management system in programming languages domain. Commun. Comput. Inf. Sci. 535, 767\u2013777 (2015). https:\/\/doi.org\/10.1007\/978-3-319-23766-4_61","DOI":"10.1007\/978-3-319-23766-4_61"},{"key":"33_CR23","doi-asserted-by":"publisher","unstructured":"Lamy, J.B.: Owlready: ontology-oriented programming in Python with automatic classification and high level constructs for biomedical ontologies. Artif. Intell. Med. 80 (2017). https:\/\/doi.org\/10.1016\/j.artmed.2017.07.002","DOI":"10.1016\/j.artmed.2017.07.002"},{"key":"33_CR24","doi-asserted-by":"publisher","unstructured":"Liang, S., Fodor, P., Wan, H., Kifer, M.: OpenRuleBench. In: Proceedings of the 18th International Conference on World Wide Web - WWW 2009. ACM Press (2009). https:\/\/doi.org\/10.1145\/1526709.1526790","DOI":"10.1145\/1526709.1526790"},{"key":"33_CR25","doi-asserted-by":"publisher","unstructured":"Rattanasawad, T., Buranarach, M., Saikaew, K.R., Supnithi, T.: A comparative study of rule-based inference engines for the semantic web. IEICE Trans. Inf. Syst. E101.D(1), 82\u201389 (2018). https:\/\/doi.org\/10.1587\/transinf.2017swp0004. https:\/\/doi.org\/10.1587\/transinf.2017swp0004","DOI":"10.1587\/transinf.2017swp0004"},{"key":"33_CR26","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1007\/978-3-030-62466-8_6","volume-title":"The Semantic Web \u2013 ISWC 2020","author":"G Singh","year":"2020","unstructured":"Singh, G., Bhatia, S., Mutharaju, R.: OWL2Bench: a benchmark for OWL 2 reasoners. In: Pan, J.Z., Tamma, V., d\u2019Amato, C., Janowicz, K., Fu, B., Polleres, A., Seneviratne, O., Kagal, L. (eds.) ISWC 2020. LNCS, vol. 12507, pp. 81\u201396. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-62466-8_6"},{"key":"33_CR27","doi-asserted-by":"publisher","unstructured":"Sirin, E., Parsia, B., Grau, B.C., Kalyanpur, A., Katz, Y.: Pellet: a practical OWL-DL reasoner. J. Web Semantics 5(2), 51\u201353 (2007). https:\/\/doi.org\/10.1016\/j.websem.2007.03.004. https:\/\/www.sciencedirect.com\/science\/article\/pii\/S1570826807000169, software Engineering and the Semantic Web","DOI":"10.1016\/j.websem.2007.03.004"},{"key":"33_CR28","unstructured":"Sychev, O., Denisov, M., Anikin, A.: Verifying algorithm traces and fault reason determining using ontology reasoning. In: 19th International Semantic Web Conference on Demos and Industry Tracks: From Novel Ideas to Industrial Practice, ISWC-Posters 2020, vol. 2721, pp. 49\u201353 (2020). http:\/\/ceur-ws.org\/Vol-2721\/paper495.pdf"},{"key":"33_CR29","unstructured":"Sychev, O., Penskoy, N.: Ontology-based determining of evaluation order of c expressions and the fault reason for incorrect answers. In: 19th International Semantic Web Conference on Demos and Industry Tracks: From Novel Ideas to Industrial Practice, ISWC-Posters 2020, vol. 2721, pp. 44\u201348 (2020). http:\/\/ceur-ws.org\/Vol-2721\/paper494.pdf"},{"key":"33_CR30","doi-asserted-by":"publisher","unstructured":"Sychev, O., Denisov, M., Terekhov, G.: How it works: Algorithms - a tool for developing an understanding of control structures. In: Proceedings of the 26th ACM Conference on Innovation and Technology in Computer Science Education V. 2. ACM, June 2021. https:\/\/doi.org\/10.1145\/3456565.3460032","DOI":"10.1145\/3456565.3460032"},{"key":"33_CR31","doi-asserted-by":"publisher","unstructured":"Wielemaker, J., Schrijvers, T., Triska, M., Lager, T.: Swi-prolog. Theory and Practice of Logic Programming 12(1\u20132), 67\u201396 (2012). https:\/\/doi.org\/10.1017\/S1471068411000494","DOI":"10.1017\/S1471068411000494"}],"container-title":["Lecture Notes in Computer Science","Computational Science and Its Applications \u2013 ICCSA 2021"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-86960-1_33","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,9,10]],"date-time":"2021-09-10T07:13:13Z","timestamp":1631257993000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-86960-1_33"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030869595","9783030869601"],"references-count":31,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-86960-1_33","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"11 September 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICCSA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Computational Science and Its Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Cagliari","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 September 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16 September 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"iccsa2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/iccsa.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Customed version of CyberChair 4","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"1588","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"466","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"18","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"29% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"2,5","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"8","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}