{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,28]],"date-time":"2025-03-28T03:45:02Z","timestamp":1743133502330,"version":"3.40.3"},"publisher-location":"Cham","reference-count":19,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319178752"},{"type":"electronic","value":"9783319178769"}],"license":[{"start":{"date-parts":[[2015,1,1]],"date-time":"2015-01-01T00:00:00Z","timestamp":1420070400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2015,1,1]],"date-time":"2015-01-01T00:00:00Z","timestamp":1420070400000},"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":[[2015]]},"DOI":"10.1007\/978-3-319-17876-9_11","type":"book-chapter","created":{"date-parts":[[2015,4,27]],"date-time":"2015-04-27T07:15:34Z","timestamp":1430118934000},"page":"164-178","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Learning Complex Activity Preconditions in Process Mining"],"prefix":"10.1007","author":[{"given":"Stefano","family":"Ferilli","sequence":"first","affiliation":[]},{"given":"Berardina","family":"De Carolis","sequence":"additional","affiliation":[]},{"given":"Floriana","family":"Esposito","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2015,4,28]]},"reference":[{"key":"11_CR1","series-title":"Lecture Notes in Computer Science","first-page":"469","volume-title":"Advances in Database Technology - EDBT \u201998","author":"R Agrawal","year":"1998","unstructured":"Agrawal, R., Gunopulos, D., Leymann, F.: Mining process models from workflow logs. In: Schek, H.-J., Saltor, F., Ramos, I., Alonso, G. (eds.) EDBT 1998. LNCS, vol. 1377, pp. 469\u2013483. Springer, Heidelberg (1998)"},{"key":"11_CR2","doi-asserted-by":"crossref","unstructured":"Anderson, C.R., Domingos, P., Weld, D.S.: Relational markov models and their application to adaptive web navigation. In: Hand, D., Keim, D., Ng, R. (eds.) Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2002), pp. 143\u2013152. ACM Press (2002)","DOI":"10.1145\/775047.775068"},{"key":"11_CR3","unstructured":"Cook, J.E., Wolf, A.L.: Discovering models of software processes from event-based data. Technical report CU-CS-819-96, Department of Computer Science, University of Colorado (1996)"},{"issue":"1","key":"11_CR4","first-page":"23","volume":"89","author":"F Esposito","year":"2008","unstructured":"Esposito, F., Di Mauro, N., Basile, T.M.A., Ferilli, S.: Multi-dimensional relational sequence mining. Fundamenta Informaticae 89(1), 23\u201343 (2008)","journal-title":"Fundamenta Informaticae"},{"issue":"1\/2","key":"11_CR5","doi-asserted-by":"publisher","first-page":"133","DOI":"10.1023\/A:1007638124237","volume":"38","author":"F Esposito","year":"2000","unstructured":"Esposito, F., Semeraro, G., Fanizzi, N., Ferilli, S.: Multistrategy theory revision: induction and abduction in inthelex. Mach. Learn. J. 38(1\/2), 133\u2013156 (2000)","journal-title":"Mach. Learn. J."},{"key":"11_CR6","doi-asserted-by":"publisher","first-page":"744","DOI":"10.1109\/TSMC.2013.2273310","volume":"44","author":"S Ferilli","year":"2014","unstructured":"Ferilli, S.: Woman: logic-based workflow learning and management. IEEE Trans. Syst. Man Cybern.: Syst. 44, 744\u2013756 (2014)","journal-title":"IEEE Trans. Syst. Man Cybern.: Syst."},{"issue":"1\u20132","key":"11_CR7","doi-asserted-by":"crossref","first-page":"43","DOI":"10.3233\/FI-2009-0004","volume":"90","author":"S Ferilli","year":"2009","unstructured":"Ferilli, S., Basile, T.M.A., Biba, M., Di Mauro, N., Esposito, F.: A general similarity framework for horn clause logic. Fundamenta Informatic\u00e6 90(1\u20132), 43\u201346 (2009)","journal-title":"Fundamenta Informatic\u00e6"},{"key":"11_CR8","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"392","DOI":"10.1007\/978-3-642-38577-3_40","volume-title":"Recent Trends in Applied Artificial Intelligence","author":"S Ferilli","year":"2013","unstructured":"Ferilli, S., De Carolis, B., Redavid, D.: Logic-based incremental process mining in smart environments. In: Ali, M., Bosse, T., Hindriks, K.V., Hoogendoorn, M., Jonker, C.M., Treur, J. (eds.) IEA\/AIE 2013. LNCS, vol. 7906, pp. 392\u2013401. Springer, Heidelberg (2013)"},{"key":"11_CR9","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"109","DOI":"10.1007\/978-3-319-03524-6_10","volume-title":"AI*IA 2013: Advances in Artificial Intelligence","author":"S Ferilli","year":"2013","unstructured":"Ferilli, S., Esposito, F.: A heuristic approach to handling sequential information in incremental ILP. In: Baldoni, M., Baroglio, C., Boella, G., Micalizio, R. (eds.) AI*IA 2013. LNCS, vol. 8249, pp. 109\u2013120. Springer, Heidelberg (2013)"},{"key":"11_CR10","doi-asserted-by":"crossref","first-page":"413","DOI":"10.3233\/FI-2013-951","volume":"128","author":"S Ferilli","year":"2013","unstructured":"Ferilli, S., Esposito, F.: A logic framework for incremental learning of process models. Fundamenta Informaticae 128, 413\u2013443 (2013)","journal-title":"Fundamenta Informaticae"},{"key":"11_CR11","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"174","DOI":"10.1007\/11871842_20","volume-title":"Machine Learning: ECML 2006","author":"B Gutmann","year":"2006","unstructured":"Gutmann, B., Kersting, K.: TildeCRF: conditional random fields for logical sequences. In: F\u00fcrnkranz, J., Scheffer, T., Spiliopoulou, M. (eds.) ECML 2006. LNCS (LNAI), vol. 4212, pp. 174\u2013185. Springer, Heidelberg (2006)"},{"key":"11_CR12","unstructured":"Herbst, J., Karagiannis, D.: An inductive approach to the acquisition and adaptation of workflow models. In: Proceedings of the IJCAI 1999 Workshop on Intelligent Workflow and Process Management: The New Frontier for AI in Business, pp. 52\u201357 (1999)"},{"key":"11_CR13","unstructured":"Jacobs, N.: Relational sequence learning and user modelling (2004)"},{"key":"11_CR14","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"28","DOI":"10.1007\/978-3-540-78652-8_2","volume-title":"Probabilistic Inductive Logic Programming","author":"K Kersting","year":"2008","unstructured":"Kersting, K., De Raedt, L., Gutmann, B., Karwath, A., Landwehr, N.: Relational sequence learning. In: De Raedt, L., Frasconi, P., Kersting, K., Muggleton, S.H. (eds.) Probabilistic ILP 2007. LNCS (LNAI), vol. 4911, pp. 28\u201355. Springer, Heidelberg (2008)"},{"key":"11_CR15","doi-asserted-by":"crossref","unstructured":"Kersting, K., Raiko, T., Kramer, S., De Raedt, L.: Towards discovering structural signatures of protein folds based on logical hidden markov models. Technical report report00175, Institut fur Informatik, Universit at Freiburg, 13 June 2002","DOI":"10.1142\/9789812776303_0019"},{"key":"11_CR16","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"154","DOI":"10.1007\/978-3-540-44497-8_8","volume-title":"Database Support for Data Mining Applications","author":"S Dan Lee","year":"2004","unstructured":"Dan Lee, S., De Raedt, L.: Constraint based mining of first order sequences in SeqLog. In: Meo, R., Lanzi, P.L., Klemettinen, M. (eds.) Database Support for Data Mining Applications. LNCS (LNAI), vol. 2682, pp. 154\u2013173. Springer, Heidelberg (2004)"},{"issue":"4","key":"11_CR17","doi-asserted-by":"publisher","first-page":"295","DOI":"10.1007\/BF03037089","volume":"8","author":"S Muggleton","year":"1991","unstructured":"Muggleton, S.: Inductive logic programming. New Gener. Comput. 8(4), 295\u2013318 (1991)","journal-title":"New Gener. Comput."},{"key":"11_CR18","doi-asserted-by":"publisher","first-page":"21","DOI":"10.1142\/S0218126698000043","volume":"8","author":"WMP van der Aalst","year":"1998","unstructured":"van der Aalst, W.M.P.: The application of Petri Nets to workflow management. J. Circuits, Syst. Comput. 8, 21\u201366 (1998)","journal-title":"J. Circuits, Syst. Comput."},{"key":"11_CR19","unstructured":"Weijters, A.J.M.M., van der Aalst, W.M.P.: Rediscovering workflow models from event-based data. In: Hoste, V., De Pauw, G. (eds.) Proceedings of the 11th Dutch-Belgian Conference of Machine Learning (Benelearn 2001), pp. 93\u2013100 (2001)"}],"container-title":["Lecture Notes in Computer Science","New Frontiers in Mining Complex Patterns"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-17876-9_11","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,2,21]],"date-time":"2023-02-21T00:49:44Z","timestamp":1676940584000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-17876-9_11"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015]]},"ISBN":["9783319178752","9783319178769"],"references-count":19,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-17876-9_11","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2015]]},"assertion":[{"value":"28 April 2015","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}}]}}