{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T00:08:02Z","timestamp":1774915682364,"version":"3.50.1"},"publisher-location":"Cham","reference-count":32,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031336195","type":"print"},{"value":"9783031336201","type":"electronic"}],"license":[{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,1,1]],"date-time":"2023-01-01T00:00:00Z","timestamp":1672531200000},"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":[[2023]]},"DOI":"10.1007\/978-3-031-33620-1_5","type":"book-chapter","created":{"date-parts":[[2023,5,27]],"date-time":"2023-05-27T08:02:05Z","timestamp":1685174525000},"page":"77-98","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Modelling Data-Aware Stochastic Processes - Discovery and\u00a0Conformance Checking"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-1733-777X","authenticated-orcid":false,"given":"Felix","family":"Mannhardt","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5201-7125","authenticated-orcid":false,"given":"Sander J. J.","family":"Leemans","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3215-7251","authenticated-orcid":false,"given":"Christopher T.","family":"Schwanen","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8447-5374","authenticated-orcid":false,"given":"Massimiliano","family":"de Leoni","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,5,28]]},"reference":[{"issue":"2","key":"5_CR1","doi-asserted-by":"publisher","first-page":"182","DOI":"10.1002\/widm.1045","volume":"2","author":"WMP van der Aalst","year":"2012","unstructured":"van der Aalst, W.M.P., Adriansyah, A., van Dongen, B.F.: Replaying history on process models for conformance checking and performance analysis. WIREs Data Mining Knowl. Discov. 2(2), 182\u2013192 (2012)","journal-title":"WIREs Data Mining Knowl. Discov."},{"key":"5_CR2","doi-asserted-by":"crossref","unstructured":"Acampora, G., Vitiello, A., Stefano, B.N.D., van der Aalst, W.M.P., G\u00fcnther, C.W., Verbeek, E.: IEEE 1849: the XES standard: the second IEEE standard sponsored by IEEE computational intelligence society [society briefs]. IEEE Comput. Intell. Mag. 12(2), 4\u20138 (2017). https:\/\/doi.org\/10.1109\/MCI.2017.2670420","DOI":"10.1109\/MCI.2017.2670420"},{"key":"5_CR3","doi-asserted-by":"publisher","DOI":"10.1016\/j.is.2022.102033","volume":"109","author":"A Alman","year":"2022","unstructured":"Alman, A., Maggi, F.M., Montali, M., Pe\u00f1aloza, R.: Probabilistic declarative process mining. Inf. Syst. 109, 102033 (2022)","journal-title":"Inf. Syst."},{"key":"5_CR4","unstructured":"Baier, C., Katoen, J.: Principles of Model Checking. MIT Press, Cambridge (2008)"},{"key":"5_CR5","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"349","DOI":"10.1007\/978-3-319-19069-3_22","volume-title":"Advanced Information Systems Engineering","author":"K Batoulis","year":"2015","unstructured":"Batoulis, K., Meyer, A., Bazhenova, E., Decker, G., Weske, M.: Extracting decision logic from process models. In: Zdravkovic, J., Kirikova, M., Johannesson, P. (eds.) CAiSE 2015. LNCS, vol. 9097, pp. 349\u2013366. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-19069-3_22"},{"key":"5_CR6","series-title":"Lecture Notes in Business Information Processing","doi-asserted-by":"publisher","first-page":"237","DOI":"10.1007\/978-3-319-39426-8_19","volume-title":"Business Information Systems","author":"E Bazhenova","year":"2016","unstructured":"Bazhenova, E., Buelow, S., Weske, M.: Discovering decision models from event logs. In: Abramowicz, W., Alt, R., Franczyk, B. (eds.) BIS 2016. LNBIP, vol. 255, pp. 237\u2013251. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-39426-8_19"},{"key":"5_CR7","doi-asserted-by":"crossref","unstructured":"Bergami, G., Maggi, F.M., Montali, M., Pe\u00f1aloza, R.: Probabilistic trace alignment. In: ICPM, pp. 9\u201316. IEEE (2021)","DOI":"10.1109\/ICPM53251.2021.9576856"},{"key":"5_CR8","series-title":"Lecture Notes in Business Information Processing","doi-asserted-by":"publisher","first-page":"260","DOI":"10.1007\/978-3-030-72693-5_20","volume-title":"Process Mining Workshops","author":"A Burke","year":"2021","unstructured":"Burke, A., Leemans, S.J.J., Wynn, M.T.: Stochastic process discovery by weight estimation. In: Leemans, S., Leopold, H. (eds.) ICPM 2020. LNBIP, vol. 406, pp. 260\u2013272. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-72693-5_20"},{"key":"5_CR9","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"312","DOI":"10.1007\/978-3-030-76983-3_16","volume-title":"Application and Theory of Petri Nets and Concurrency","author":"A Burke","year":"2021","unstructured":"Burke, A., Leemans, S.J.J., Wynn, M.T.: Discovering stochastic process models by reduction and abstraction. In: Buchs, D., Carmona, J. (eds.) PETRI NETS 2021. LNCS, vol. 12734, pp. 312\u2013336. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-76983-3_16"},{"key":"5_CR10","doi-asserted-by":"crossref","unstructured":"Camargo, M., Dumas, M., Gonz\u00e1lez-Rojas, O.: Automated discovery of business process simulation models from event logs. Decis. Support Syst. 134, 113284 (2020). https:\/\/www.sciencedirect.com\/science\/article\/pii\/S0167923620300397","DOI":"10.1016\/j.dss.2020.113284"},{"issue":"1","key":"5_CR11","doi-asserted-by":"publisher","first-page":"191","DOI":"10.2307\/2347628","volume":"41","author":"S le Cessie","year":"1992","unstructured":"le Cessie, S., van Houwelingen, J.: Ridge estimators in logistic regression. Appl. Stat. 41(1), 191\u2013201 (1992)","journal-title":"Appl. Stat."},{"key":"5_CR12","doi-asserted-by":"publisher","unstructured":"Di Francescomarino, C., Ghidini, C.: Predictive process monitoring. In: van der Aalst, W.M.P., Carmona, J. (eds.) Process Mining Handbook. LNBIP, vol. 448, pp. 320\u2013346. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-08848-3_10","DOI":"10.1007\/978-3-031-08848-3_10"},{"key":"5_CR13","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"217","DOI":"10.1007\/978-3-030-85469-0_15","volume-title":"Business Process Management","author":"P Felli","year":"2021","unstructured":"Felli, P., Gianola, A., Montali, M., Rivkin, A., Winkler, S.: CoCoMoT: conformance checking of multi-perspective processes via SMT. In: Polyvyanyy, A., Wynn, M.T., Van Looy, A., Reichert, M. (eds.) BPM 2021. LNCS, vol. 12875, pp. 217\u2013234. Springer, Cham (2021). https:\/\/doi.org\/10.1007\/978-3-030-85469-0_15"},{"key":"5_CR14","doi-asserted-by":"crossref","unstructured":"Gibbs, A.L., Su, F.E.: On choosing and bounding probability metrics. Int. Stat. Rev. 70(3), 419\u2013435 (2002). https:\/\/onlinelibrary.wiley.com\/doi\/abs\/10.1111\/j.1751-5823.2002.tb00178.x","DOI":"10.1111\/j.1751-5823.2002.tb00178.x"},{"key":"5_CR15","doi-asserted-by":"publisher","unstructured":"Hensel, C., Junges, S., Katoen, J., Quatmann, T., Volk, M.: The probabilistic model checker storm. Int. J. Softw. Tools Technol. Transf. 24(4), 589\u2013610 (2022). https:\/\/doi.org\/10.1007\/s10009-021-00633-z","DOI":"10.1007\/s10009-021-00633-z"},{"key":"5_CR16","doi-asserted-by":"publisher","unstructured":"Leemans, S.J.J., van der Aalst, W.M.P., Brockhoff, T., Polyvyanyy, A.: Stochastic process mining: earth movers\u2019 stochastic conformance. Inf. Syst. 102, 101724 (2021). https:\/\/doi.org\/10.1016\/j.is.2021.101724","DOI":"10.1016\/j.is.2021.101724"},{"key":"5_CR17","series-title":"Lecture Notes in Business Information Processing","doi-asserted-by":"publisher","first-page":"66","DOI":"10.1007\/978-3-319-06257-0_6","volume-title":"Business Process Management Workshops","author":"SJJ Leemans","year":"2014","unstructured":"Leemans, S.J.J., Fahland, D., van der Aalst, W.M.P.: Discovering Block-Structured Process Models from Event Logs Containing Infrequent Behaviour. In: Lohmann, N., Song, M., Wohed, P. (eds.) BPM 2013. LNBIP, vol. 171, pp. 66\u201378. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-06257-0_6"},{"key":"5_CR18","doi-asserted-by":"publisher","unstructured":"Leemans, S.J.J., Maggi, F.M., Montali, M.: Reasoning on labelled petri nets and their dynamics in a stochastic setting. In: Di Ciccio, C., Dijkman, R., del R\u0131o Ortega, A., Rinderle-Ma, S. (eds.) BPM 2022. LNCS, vol. 13420, pp. 324\u2013342. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-16103-2_22","DOI":"10.1007\/978-3-031-16103-2_22"},{"key":"5_CR19","doi-asserted-by":"publisher","unstructured":"Leemans, S.J.J., Poppe, E., Wynn, M.T.: Directly follows-based process mining: exploration & a case study. In: International Conference on Process Mining, ICPM 2019, Aachen, Germany, 24\u201326 June 2019, pp. 25\u201332. IEEE (2019). https:\/\/doi.org\/10.1109\/ICPM.2019.00015","DOI":"10.1109\/ICPM.2019.00015"},{"key":"5_CR20","series-title":"Lecture Notes in Business Information Processing","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1007\/978-3-030-26643-1_8","volume-title":"Business Process Management Forum","author":"SJJ Leemans","year":"2019","unstructured":"Leemans, S.J.J., Syring, A.F., van der Aalst, W.M.P.: Earth movers\u2019 stochastic conformance checking. In: Hildebrandt, T., van Dongen, B.F., R\u00f6glinger, M., Mendling, J. (eds.) BPM 2019. LNBIP, vol. 360, pp. 127\u2013143. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-26643-1_8"},{"key":"5_CR21","doi-asserted-by":"publisher","unstructured":"Leemans, S.J.J., Tax, N.: Causal reasoning over control-flow decisions in process models. In: Franch, X., Poels, G., Gailly, F., Snoeck, M. (eds.) CAiSE 2022. LNCS, vol. 13295, pp. 183\u2013200. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-07472-1_11","DOI":"10.1007\/978-3-031-07472-1_11"},{"key":"5_CR22","doi-asserted-by":"publisher","unstructured":"Mannhardt, F., de Leoni, M., Reijers, H.A., van der Aalst, W.M.P.: Balanced multi-perspective checking of process conformance. Computing 98(4), 407\u2013437 (2016). https:\/\/doi.org\/10.1007\/s00607-015-0441-1","DOI":"10.1007\/s00607-015-0441-1"},{"key":"5_CR23","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"377","DOI":"10.1007\/978-3-319-39696-5_23","volume-title":"Advanced Information Systems Engineering","author":"F Mannhardt","year":"2016","unstructured":"Mannhardt, F., de Leoni, M., Reijers, H.A., van der Aalst, W.M.P.: Decision mining revisited - discovering overlapping rules. In: Nurcan, S., Soffer, P., Bajec, M., Eder, J. (eds.) CAiSE 2016. LNCS, vol. 9694, pp. 377\u2013392. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-39696-5_23"},{"key":"5_CR24","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"545","DOI":"10.1007\/978-3-319-59536-8_34","volume-title":"Advanced Information Systems Engineering","author":"F Mannhardt","year":"2017","unstructured":"Mannhardt, F., de Leoni, M., Reijers, H.A., van der Aalst, W.M.P.: Data-driven process discovery - revealing conditional infrequent behavior from event logs. In: Dubois, E., Pohl, K. (eds.) CAiSE 2017. LNCS, vol. 10253, pp. 545\u2013560. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-59536-8_34"},{"issue":"6","key":"5_CR25","doi-asserted-by":"publisher","first-page":"962","DOI":"10.1109\/TSC.2017.2772256","volume":"11","author":"AE M\u00e1rquez-Chamorro","year":"2018","unstructured":"M\u00e1rquez-Chamorro, A.E., Resinas, M., Ruiz-Cort\u00e9s, A.: Predictive monitoring of business processes: a survey. IEEE Trans. Serv. Comput. 11(6), 962\u2013977 (2018)","journal-title":"IEEE Trans. Serv. Comput."},{"issue":"1","key":"5_CR26","doi-asserted-by":"publisher","first-page":"2","DOI":"10.1057\/palgrave.jors.2601477","volume":"54","author":"N Mel\u00e3o","year":"2003","unstructured":"Mel\u00e3o, N., Pidd, M.: Use of business process simulation: a survey of practitioners. J. Oper. Res. Soc. 54(1), 2\u201310 (2003)","journal-title":"J. Oper. Res. Soc."},{"key":"5_CR27","doi-asserted-by":"crossref","unstructured":"Park, G., Song, M.: Prediction-based resource allocation using LSTM and minimum cost and maximum flow algorithm. In: International Conference on Process Mining (ICPM), pp. 121\u2013128 (2019)","DOI":"10.1109\/ICPM.2019.00027"},{"key":"5_CR28","doi-asserted-by":"crossref","unstructured":"Polyvyanyy, A., Moffat, A., Garc\u00eda-Ba\u00f1uelos, L.: An entropic relevance measure for stochastic conformance checking in process mining. In: ICPM, pp. 97\u2013104. IEEE (2020)","DOI":"10.1109\/ICPM49681.2020.00024"},{"key":"5_CR29","series-title":"Lecture Notes in Business Information Processing","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1007\/978-3-319-06257-0_2","volume-title":"Business Process Management Workshops","author":"A Rogge-Solti","year":"2014","unstructured":"Rogge-Solti, A., van der Aalst, W.M.P., Weske, M.: Discovering stochastic petri nets with arbitrary delay distributions from event logs. In: Lohmann, N., Song, M., Wohed, P. (eds.) BPM 2013. LNBIP, vol. 171, pp. 15\u201327. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-06257-0_2"},{"key":"5_CR30","doi-asserted-by":"publisher","unstructured":"Rogge-Solti, A., Weske, M.: Prediction of business process durations using non-Markovian stochastic petri nets. Inf. Syst. 54, 1\u201314 (2015). https:\/\/doi.org\/10.1016\/j.is.2015.04.004","DOI":"10.1016\/j.is.2015.04.004"},{"key":"5_CR31","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"420","DOI":"10.1007\/11841760_33","volume-title":"Business Process Management","author":"A Rozinat","year":"2006","unstructured":"Rozinat, A., van der Aalst, W.M.P.: Decision mining in ProM. In: Dustdar, S., Fiadeiro, J.L., Sheth, A.P. (eds.) BPM 2006. LNCS, vol. 4102, pp. 420\u2013425. Springer, Heidelberg (2006). https:\/\/doi.org\/10.1007\/11841760_33"},{"key":"5_CR32","volume-title":"Data Mining: Practical Machine Learning Tools and Techniques","author":"IH Witten","year":"2011","unstructured":"Witten, I.H., Frank, E., Hall, M.A.: Data Mining: Practical Machine Learning Tools and Techniques, 3rd edn. Morgan Kaufmann, Elsevier, Amsterdam (2011)","edition":"3"}],"container-title":["Lecture Notes in Computer Science","Application and Theory of Petri Nets and Concurrency"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-33620-1_5","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,6,17]],"date-time":"2023-06-17T23:08:24Z","timestamp":1687043304000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-33620-1_5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023]]},"ISBN":["9783031336195","9783031336201"],"references-count":32,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-33620-1_5","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023]]},"assertion":[{"value":"28 May 2023","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"PETRI NETS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Applications and Theory of Petri Nets and Concurrency","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Lisbon","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Portugal","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25 June 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"30 June 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"44","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"apn2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/petrinets2023.deec.fct.unl.pt\/","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":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"47","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":"21","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":"0","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":"45% - 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":"4","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":"5","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)"}}]}}