{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T13:30:17Z","timestamp":1742995817764,"version":"3.40.3"},"publisher-location":"Cham","reference-count":31,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030109271"},{"type":"electronic","value":"9783030109288"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"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":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-10928-8_24","type":"book-chapter","created":{"date-parts":[[2019,1,24]],"date-time":"2019-01-24T08:19:39Z","timestamp":1548317979000},"page":"396-413","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":6,"title":["Online Learning of Weighted Relational Rules for Complex Event Recognition"],"prefix":"10.1007","author":[{"given":"Nikos","family":"Katzouris","sequence":"first","affiliation":[]},{"given":"Evangelos","family":"Michelioudakis","sequence":"additional","affiliation":[]},{"given":"Alexander","family":"Artikis","sequence":"additional","affiliation":[]},{"given":"Georgios","family":"Paliouras","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,1,23]]},"reference":[{"key":"24_CR1","doi-asserted-by":"crossref","unstructured":"Alevizos, E., Skarlatidis, A., Artikis, A., Paliourasm, G.: Probabilistic complex event recognition: a survey. ACM Computing Surveys (2018) (to appear)","DOI":"10.1145\/3117809"},{"issue":"4","key":"24_CR2","doi-asserted-by":"publisher","first-page":"895","DOI":"10.1109\/TKDE.2014.2356476","volume":"27","author":"A Artikis","year":"2015","unstructured":"Artikis, A., Sergot, M., Paliouras, G.: An event calculus for event recognition. IEEE Trans. Knowl. Data Eng. 27(4), 895\u2013908 (2015)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"issue":"4","key":"24_CR3","doi-asserted-by":"publisher","first-page":"469","DOI":"10.1017\/S0269888912000264","volume":"27","author":"A Artikis","year":"2012","unstructured":"Artikis, A., Skarlatidis, A., Portet, F., Paliouras, G.: Logic-based event recognition. Knowl. Eng. Rev. 27(4), 469\u2013506 (2012)","journal-title":"Knowl. Eng. Rev."},{"key":"24_CR4","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"31","DOI":"10.1007\/978-3-662-44923-3_3","volume-title":"Inductive Logic Programming","author":"D Athakravi","year":"2014","unstructured":"Athakravi, D., Corapi, D., Broda, K., Russo, A.: Learning through hypothesis refinement using answer set programming. In: Zaverucha, G., Santos Costa, V., Paes, A. (eds.) ILP 2013. LNCS (LNAI), vol. 8812, pp. 31\u201346. Springer, Heidelberg (2014). https:\/\/doi.org\/10.1007\/978-3-662-44923-3_3"},{"key":"24_CR5","unstructured":"Corapi, D., Russo, A., Lupu, E.: Inductive logic programming as abductive search. In ICLP-2010, pp. 54\u201363 (2010)"},{"key":"24_CR6","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"243","DOI":"10.1007\/978-3-642-22359-4_17","volume-title":"Computational Logic in Multi-Agent Systems","author":"D Corapi","year":"2011","unstructured":"Corapi, D., Sykes, D., Inoue, K., Russo, A.: Probabilistic rule learning in nonmonotonic domains. In: Leite, J., Torroni, P., \u00c5gotnes, T., Boella, G., van der Torre, L. (eds.) CLIMA 2011. LNCS (LNAI), vol. 6814, pp. 243\u2013258. Springer, Heidelberg (2011). https:\/\/doi.org\/10.1007\/978-3-642-22359-4_17"},{"issue":"3","key":"24_CR7","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1145\/2187671.2187677","volume":"44","author":"G Cugola","year":"2012","unstructured":"Cugola, G., Margara, A.: Processing flows of information: from data stream to complex event processing. ACM Comput. Surv. (CSUR) 44(3), 15 (2012)","journal-title":"ACM Comput. Surv. (CSUR)"},{"key":"24_CR8","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-68856-3","volume-title":"Logical and Relational Learning","author":"L De Raedt","year":"2008","unstructured":"De Raedt, L.: Logical and Relational Learning. Springer, Heidelberg (2008). https:\/\/doi.org\/10.1007\/978-3-540-68856-3"},{"issue":"2","key":"24_CR9","doi-asserted-by":"publisher","first-page":"1","DOI":"10.2200\/S00692ED1V01Y201601AIM032","volume":"10","author":"L De Raedt","year":"2016","unstructured":"De Raedt, L., Kersting, K., Natarajan, S., Poole, D.: Statistical relational artificial intelligence: logic, probability, and computation. Synth. Lect. Artif. Intell. Mach. Learn. 10(2), 1\u2013189 (2016)","journal-title":"Synth. Lect. Artif. Intell. Mach. Learn."},{"key":"24_CR10","doi-asserted-by":"crossref","unstructured":"Domingos, P., Hulten, G.: Mining high-speed data streams. In: ACM SIGKDD, pp. 71\u201380. ACM (2000)","DOI":"10.1145\/347090.347107"},{"key":"24_CR11","unstructured":"Dragiev, S., Russo, A., Broda, K., Law, M., Turliuc, C.: An abductive-inductive algorithm for probabilistic inductive logic programming. In: Proceedings of the 26th International Conference on Inductive Logic Programming (Short papers), London, UK, 2016, pp. 20\u201326 (2016)"},{"key":"24_CR12","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1007\/978-3-642-13840-9_2","volume-title":"Inductive Logic Programming","author":"A Dries","year":"2010","unstructured":"Dries, A., De Raedt, L.: Towards clausal discovery for stream mining. In: De Raedt, L. (ed.) ILP 2009. LNCS (LNAI), vol. 5989, pp. 9\u201316. Springer, Heidelberg (2010). https:\/\/doi.org\/10.1007\/978-3-642-13840-9_2"},{"key":"24_CR13","first-page":"2121","volume":"12","author":"J Duchi","year":"2011","unstructured":"Duchi, J., Hazan, E., Singer, Y.: Adaptive subgradient methods for online learning and stochastic optimization. J. Mach. Learn. Res. 12, 2121\u20132159 (2011)","journal-title":"J. Mach. Learn. Res."},{"key":"24_CR14","doi-asserted-by":"publisher","DOI":"10.1201\/EBK1439826119","volume-title":"Knowledge Discovery from Data Streams","author":"J Gama","year":"2010","unstructured":"Gama, J.: Knowledge Discovery from Data Streams. CRC Press, Boca Raton (2010)"},{"issue":"3","key":"24_CR15","doi-asserted-by":"publisher","first-page":"317","DOI":"10.1007\/s10994-012-5320-9","volume":"90","author":"J Gama","year":"2013","unstructured":"Gama, J., Sebasti\u00e3o, R., Rodrigues, P.P.: On evaluating stream learning algorithms. Mach. Learn. 90(3), 317\u2013346 (2013)","journal-title":"Mach. Learn."},{"issue":"301","key":"24_CR16","doi-asserted-by":"publisher","first-page":"13","DOI":"10.1080\/01621459.1963.10500830","volume":"58","author":"W Hoeffding","year":"1963","unstructured":"Hoeffding, W.: Probability inequalities for sums of bounded random variables. J. Am. Stat. Assoc. 58(301), 13\u201330 (1963)","journal-title":"J. Am. Stat. Assoc."},{"key":"24_CR17","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"564","DOI":"10.1007\/978-3-642-04180-8_54","volume-title":"Machine Learning and Knowledge Discovery in Databases","author":"TN Huynh","year":"2009","unstructured":"Huynh, T.N., Mooney, R.J.: Max-Margin weight learning for markov logic networks. In: Buntine, W., Grobelnik, M., Mladeni\u0107, D., Shawe-Taylor, J. (eds.) ECML PKDD 2009, Part I. LNCS (LNAI), vol. 5781, pp. 564\u2013579. Springer, Heidelberg (2009). https:\/\/doi.org\/10.1007\/978-3-642-04180-8_54"},{"key":"24_CR18","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"81","DOI":"10.1007\/978-3-642-23783-6_6","volume-title":"Machine Learning and Knowledge Discovery in Databases","author":"TN Huynh","year":"2011","unstructured":"Huynh, T.N., Mooney, R.J.: Online structure learning for markov logic networks. In: Gunopulos, D., Hofmann, T., Malerba, D., Vazirgiannis, M. (eds.) ECML PKDD 2011, Part II. LNCS (LNAI), vol. 6912, pp. 81\u201396. Springer, Heidelberg (2011). https:\/\/doi.org\/10.1007\/978-3-642-23783-6_6"},{"key":"24_CR19","unstructured":"Katzouris, N.: Scalable relational learning for event recognition. PhD Thesis, University of Athens (2017). http:\/\/users.iit.demokritos.gr\/nkatz\/papers\/nkatz-phd.pdf"},{"issue":"2\u20133","key":"24_CR20","doi-asserted-by":"publisher","first-page":"555","DOI":"10.1007\/s10994-015-5512-1","volume":"100","author":"N Katzouris","year":"2015","unstructured":"Katzouris, N., Artikis, A., Paliouras, G.: Incremental learning of event definitions with inductive logic programming. Mach. Learn. 100(2\u20133), 555\u2013585 (2015)","journal-title":"Mach. Learn."},{"issue":"5\u20136","key":"24_CR21","doi-asserted-by":"publisher","first-page":"817","DOI":"10.1017\/S1471068416000260","volume":"16","author":"N Katzouris","year":"2016","unstructured":"Katzouris, N., Artikis, A., Paliouras, G.: Online learning of event definitions. Theory Pract. Log. Program. 16(5\u20136), 817\u2013833 (2016)","journal-title":"Theory Pract. Log. Program."},{"key":"24_CR22","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"78","DOI":"10.1007\/978-3-319-78090-0_6","volume-title":"Inductive Logic Programming","author":"N Katzouris","year":"2018","unstructured":"Katzouris, N., Artikis, A., Paliouras, G.: Parallel Online Learning of Event Definitions. In: Lachiche, N., Vrain, C. (eds.) ILP 2017. LNCS (LNAI), vol. 10759, pp. 78\u201393. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-78090-0_6"},{"issue":"1","key":"24_CR23","doi-asserted-by":"publisher","first-page":"67","DOI":"10.1007\/BF03037383","volume":"4","author":"R Kowalski","year":"1986","unstructured":"Kowalski, R., Sergot, M.: A logic-based calculus of events. New Gener. Comput. 4(1), 67\u201395 (1986)","journal-title":"New Gener. Comput."},{"issue":"5\u20136","key":"24_CR24","doi-asserted-by":"publisher","first-page":"834","DOI":"10.1017\/S1471068416000351","volume":"16","author":"M Law","year":"2016","unstructured":"Law, M., Russo, A., Broda, K.: Iterative learning of answer set programs from context dependent examples. Theory Pract. Log. Program. 16(5\u20136), 834\u2013848 (2016)","journal-title":"Theory Pract. Log. Program."},{"issue":"4","key":"24_CR25","first-page":"285","volume":"2","author":"N Littlestone","year":"1988","unstructured":"Littlestone, N.: Learning quickly when irrelevant attributes abound: a new linear-threshold algorithm. Mach. Learn. 2(4), 285\u2013318 (1988)","journal-title":"Mach. Learn."},{"key":"24_CR26","doi-asserted-by":"crossref","unstructured":"Margara, A., Cugola, G., Tamburrelli, G.: Learning from the past: automated rule generation for complex event processing. In: Proceedings of the 8th ACM International Conference on Distributed Event-Based Systems, pp. 47\u201358. ACM (2014)","DOI":"10.1145\/2611286.2611289"},{"key":"24_CR27","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"232","DOI":"10.1007\/978-3-319-46128-1_15","volume-title":"Machine Learning and Knowledge Discovery in Databases","author":"E Michelioudakis","year":"2016","unstructured":"Michelioudakis, E., Skarlatidis, A., Paliouras, G., Artikis, A.: OSL$$\\alpha $$: online structure learning using background knowledge axiomatization. In: Frasconi, P., Landwehr, N., Manco, G., Vreeken, J. (eds.) ECML PKDD 2016, Part I. LNCS (LNAI), vol. 9851, pp. 232\u2013247. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46128-1_15"},{"issue":"3","key":"24_CR28","doi-asserted-by":"publisher","first-page":"329","DOI":"10.1016\/j.jal.2008.10.007","volume":"7","author":"O Ray","year":"2009","unstructured":"Ray, O.: Nonmonotonic abductive inductive learning. J. Appl. Log. 7(3), 329\u2013340 (2009)","journal-title":"J. Appl. Log."},{"issue":"1\u20132","key":"24_CR29","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1007\/s10994-006-5833-1","volume":"62","author":"M Richardson","year":"2006","unstructured":"Richardson, M., Domingos, P.: Markov logic networks. Mach. Learn. 62(1\u20132), 107\u2013136 (2006)","journal-title":"Mach. Learn."},{"issue":"2","key":"24_CR30","first-page":"11","volume":"16","author":"A Skarlatidis","year":"2015","unstructured":"Skarlatidis, A., Paliouras, G., Artikis, A., Vouros, G.: Probabilistic event calculus for event recognition. ACM Trans. Comput. Log. (TOCL) 16(2), 11 (2015)","journal-title":"ACM Trans. Comput. Log. (TOCL)"},{"issue":"2","key":"24_CR31","doi-asserted-by":"publisher","first-page":"243","DOI":"10.1007\/s10994-016-5596-2","volume":"106","author":"A Srinivasan","year":"2017","unstructured":"Srinivasan, A., Bain, M.: An empirical study of on-line models for relational data streams. Mach. Learn. 106(2), 243\u2013276 (2017)","journal-title":"Mach. Learn."}],"container-title":["Lecture Notes in Computer Science","Machine Learning and Knowledge Discovery in Databases"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-10928-8_24","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,22]],"date-time":"2024-01-22T01:06:19Z","timestamp":1705885579000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-10928-8_24"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030109271","9783030109288"],"references-count":31,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-10928-8_24","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"23 January 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECML PKDD","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Joint European Conference on Machine Learning and Knowledge Discovery in Databases","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Dublin","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Ireland","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2018","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 September 2018","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14 September 2018","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ecml2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.ecmlpkdd2018.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":"CMT","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"535","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":"131","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":"17","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":"24% - 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":"3","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":"3","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":"No","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}]}}