{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T11:26:16Z","timestamp":1777893976268,"version":"3.51.4"},"publisher-location":"Cham","reference-count":76,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783031057595","type":"print"},{"value":"9783031057601","type":"electronic"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2022,5,14]],"date-time":"2022-05-14T00:00:00Z","timestamp":1652486400000},"content-version":"vor","delay-in-days":133,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>In the last years, process mining has significantly matured and has increasingly been applied by companies in industrial contexts. However, with the growing number of process mining methods, practitioners might find it difficult to identify which ones to apply in specific contexts and to understand the specific business value of each process mining technique. This paper\u2019s main objective is to develop a business-oriented framework capturing the main process mining use cases and the business-oriented questions they can answer. We conducted a Systematic Literature Review (SLR) and we used the review and the extracted data to develop a framework that (1) classifies existing process mining use cases connecting them to specific methods implementing them, and (2) identifies business-oriented questions that process mining use cases can answer. Practitioners can use the framework to navigate through the available process mining use cases and to identify the process mining methods suitable for their needs.<\/jats:p>","DOI":"10.1007\/978-3-031-05760-1_16","type":"book-chapter","created":{"date-parts":[[2022,5,13]],"date-time":"2022-05-13T07:03:06Z","timestamp":1652425386000},"page":"265-282","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Process Mining: A Guide for Practitioners"],"prefix":"10.1007","author":[{"given":"Fredrik","family":"Milani","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Katsiaryna","family":"Lashkevich","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Fabrizio Maria","family":"Maggi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chiara","family":"Di Francescomarino","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,5,14]]},"reference":[{"key":"16_CR1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-19345-3","volume-title":"Process Mining: Discovery, Conformance and Enhancement of Business Processes","author":"WMP van der Aalst","year":"2011","unstructured":"van der Aalst, W.M.P.: Process Mining: Discovery, Conformance and Enhancement of Business Processes. Springer, Berlin (2011). https:\/\/doi.org\/10.1007\/978-3-642-19345-3"},{"issue":"6","key":"16_CR2","doi-asserted-by":"publisher","first-page":"549","DOI":"10.1007\/s10606-005-9005-9","volume":"14","author":"WMP van der Aalst","year":"2005","unstructured":"van der Aalst, W.M.P., Reijers, H.A., Song, M.: Discovering social networks from event logs. Comput. Support. Coop. Work 14(6), 549\u2013593 (2005)","journal-title":"Comput. Support. Coop. Work"},{"key":"16_CR3","doi-asserted-by":"crossref","unstructured":"Adriansyah, A., van Dongen, B.F., van der Aalst, W.M.P.: Conformance checking using cost-based fitness analysis. In: Proceedings of the 15th IEEE International Enterprise Distributed Object Computing Conference, EDOC 2011, Helsinki, Finland, pp. 55\u201364. IEEE Computer Society (2011)","DOI":"10.1109\/EDOC.2011.12"},{"key":"16_CR4","doi-asserted-by":"crossref","unstructured":"Arpasat, P., Porouhan, P., Premchaiswadi, W.: Improvement of call center customer service in a thai bank using disco fuzzy mining algorithm. In: 2015 13th International Conference on ICT and Knowledge Engineering (ICT & Knowledge Engineering 2015), pp. 90\u201396. IEEE (2015)","DOI":"10.1109\/ICTKE.2015.7368477"},{"issue":"4","key":"16_CR5","doi-asserted-by":"publisher","first-page":"686","DOI":"10.1109\/TKDE.2018.2841877","volume":"31","author":"A Augusto","year":"2019","unstructured":"Augusto, A., et al.: Automated discovery of process models from event logs: review and benchmark. IEEE Trans. Knowl. Data Eng. 31(4), 686\u2013705 (2019)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"16_CR6","doi-asserted-by":"crossref","unstructured":"Batista, E., Solanas, A.: Process mining in healthcare: a systematic review. In: 9th International Conference on Information, Intelligence, Systems and Applications, IISA 2018, Zakynthos, Greece, 23\u201325 July 2018, pp. 1\u20136. IEEE Computer Society (2018)","DOI":"10.1109\/IISA.2018.8633608"},{"issue":"4","key":"16_CR7","doi-asserted-by":"publisher","first-page":"458","DOI":"10.1108\/MBE-12-2018-0108","volume":"23","author":"E Benevento","year":"2019","unstructured":"Benevento, E., Aloini, D., Squicciarini, N., Dulmin, R., Mininno, V.: Queue-based features for dynamic waiting time prediction in emergency department. Meas. Bus. Excell. 23(4), 458\u2013471 (2019)","journal-title":"Meas. Bus. Excell."},{"key":"16_CR8","unstructured":"Bergami, G., Di Francescomarino, C., Ghidini, C., Maggi, F.M., Puura, J.: Exploring business process deviance with sequential and declarative patterns. CoRR abs\/2111.12454 (2021)"},{"key":"16_CR9","doi-asserted-by":"publisher","first-page":"101438","DOI":"10.1016\/j.is.2019.101438","volume":"90","author":"K B\u00f6hmer","year":"2020","unstructured":"B\u00f6hmer, K., Rinderle-Ma, S.: Mining association rules for anomaly detection in dynamic process runtime behavior and explaining the root cause to users. Inf. Syst. 90, 101438 (2020)","journal-title":"Inf. Syst."},{"key":"16_CR10","doi-asserted-by":"publisher","first-page":"53","DOI":"10.1016\/j.is.2017.12.006","volume":"74","author":"A Bolt","year":"2018","unstructured":"Bolt, A., de Leoni, M., van der Aalst, W.M.P.: Process variant comparison: using event logs to detect differences in behavior and business rules. Inf. Syst. 74, 53\u201366 (2018)","journal-title":"Inf. Syst."},{"key":"16_CR11","series-title":"Lecture Notes in Business Information Processing","doi-asserted-by":"publisher","first-page":"170","DOI":"10.1007\/978-3-642-12186-9_16","volume-title":"Business Process Management Workshops","author":"RPJC Bose","year":"2010","unstructured":"Bose, R.P.J.C., van der Aalst, W.M.P.: Trace clustering based on conserved patterns: towards achieving better process models. In: Rinderle-Ma, S., Sadiq, S., Leymann, F. (eds.) BPM 2009. LNBIP, vol. 43, pp. 170\u2013181. Springer, Heidelberg (2010). https:\/\/doi.org\/10.1007\/978-3-642-12186-9_16"},{"key":"16_CR12","doi-asserted-by":"publisher","first-page":"194","DOI":"10.1016\/j.eswa.2016.08.040","volume":"65","author":"A Burattin","year":"2016","unstructured":"Burattin, A., Maggi, F.M., Sperduti, A.: Conformance checking based on multi-perspective declarative process models. Exp. Syst. Appl. 65, 194\u2013211 (2016)","journal-title":"Exp. Syst. Appl."},{"key":"16_CR13","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-99414-7","volume-title":"Conformance Checking: Relating Processes and Models","author":"J Carmona","year":"2018","unstructured":"Carmona, J., van Dongen, B., Solti, A., Weidlich, M.: Conformance Checking: Relating Processes and Models. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-99414-7"},{"key":"16_CR14","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"116","DOI":"10.1007\/978-3-642-38709-8_8","volume-title":"Advanced Information Systems Engineering","author":"R Conforti","year":"2013","unstructured":"Conforti, R., de Leoni, M., La Rosa, M., van der Aalst, W.M.P.: Supporting risk-informed decisions during business process execution. In: Salinesi, C., Norrie, M.C., Pastor, \u00d3. (eds.) CAiSE 2013. LNCS, vol. 7908, pp. 116\u2013132. Springer, Heidelberg (2013). https:\/\/doi.org\/10.1007\/978-3-642-38709-8_8"},{"issue":"1","key":"16_CR15","first-page":"104","volume":"1","author":"HM Cooper","year":"1988","unstructured":"Cooper, H.M.: Organizing knowledge syntheses: a taxonomy of literature reviews. Knowl. Soc. 1(1), 104 (1988)","journal-title":"Knowl. Soc."},{"issue":"3","key":"16_CR16","doi-asserted-by":"publisher","first-page":"225","DOI":"10.1002\/kpm.1630","volume":"27","author":"A Corallo","year":"2020","unstructured":"Corallo, A., Lazoi, M., Striani, F.: Process mining and industrial applications: a systematic literature review. Knowl. Process. Manag. 27(3), 225\u2013233 (2020)","journal-title":"Knowl. Process. Manag."},{"key":"16_CR17","doi-asserted-by":"crossref","unstructured":"Cuzzocrea, A., Folino, F., Guarascio, M., Pontieri, L.: A predictive learning framework for monitoring aggregated performance indicators over business process events. In: Proceedings of the 22nd International Database Engineering & Applications Symposium, IDEAS 2018, pp. 165\u2013174. ACM (2018)","DOI":"10.1145\/3216122.3216143"},{"key":"16_CR18","doi-asserted-by":"crossref","unstructured":"Dakic, D., Stefanovic, D., Cosic, I., Lolic, T., Medojevic, M., Katalinic, B.: Business process mining application: a literature review. In: Proceedings of the 29th DAAAM International Symposium, pp. 0866\u20130875 (2018)","DOI":"10.2507\/29th.daaam.proceedings.125"},{"key":"16_CR19","doi-asserted-by":"crossref","unstructured":"De Giacomo, G., Maggi, F.M., Marrella, A., Patrizi, F.: On the disruptive effectiveness of automated planning for LTL$$_f$$-based trace alignment. In: Proceedings of the 31st AAAI Conference on Artificial Intelligence, San Francisco, California, USA, 4\u20139 February 2017, pp. 3555\u20133561 (2017)","DOI":"10.1609\/aaai.v31i1.11020"},{"issue":"4","key":"16_CR20","doi-asserted-by":"publisher","first-page":"22","DOI":"10.4018\/ijismd.2014100102","volume":"5","author":"R Deneckere","year":"2014","unstructured":"Deneckere, R., Hug, C., Khodabandelou, G., Salinesi, C.: Intentional process mining: discovering and modeling the goals behind processes using supervised learning. Int. J. Inf. Syst. Model. Des. (IJISMD) 5(4), 22\u201347 (2014)","journal-title":"Int. J. Inf. Syst. Model. Des. (IJISMD)"},{"key":"16_CR21","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"139","DOI":"10.1007\/978-3-319-98648-7_9","volume-title":"Business Process Management","author":"V Denisov","year":"2018","unstructured":"Denisov, V., Fahland, D., van der Aalst, W.M.P.: Unbiased, fine-grained description of processes performance from event data. In: Weske, M., Montali, M., Weber, I., vom Brocke, J. (eds.) BPM 2018. LNCS, vol. 11080, pp. 139\u2013157. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-98648-7_9"},{"key":"16_CR22","doi-asserted-by":"publisher","first-page":"258","DOI":"10.1016\/j.is.2015.06.009","volume":"56","author":"C Di Ciccio","year":"2016","unstructured":"Di Ciccio, C., Maggi, F.M., Mendling, J.: Efficient discovery of target-branched declare constraints. Inf. Syst. 56, 258\u2013283 (2016)","journal-title":"Inf. Syst."},{"key":"16_CR23","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"361","DOI":"10.1007\/978-3-319-39696-5_22","volume-title":"Advanced Information Systems Engineering","author":"C Di Francescomarino","year":"2016","unstructured":"Di Francescomarino, C., Dumas, M., Federici, M., Ghidini, C., Maggi, F.M., Rizzi, W.: Predictive business process monitoring framework with hyperparameter optimization. In: Nurcan, S., Soffer, P., Bajec, M., Eder, J. (eds.) CAiSE 2016. LNCS, vol. 9694, pp. 361\u2013376. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-39696-5_22"},{"key":"16_CR24","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"462","DOI":"10.1007\/978-3-319-98648-7_27","volume-title":"Business Process Management","author":"C Di Francescomarino","year":"2018","unstructured":"Di Francescomarino, C., Ghidini, C., Maggi, F.M., Milani, F.: Predictive process monitoring methods: which one suits me best? In: Weske, M., Montali, M., Weber, I., vom Brocke, J. (eds.) BPM 2018. LNCS, vol. 11080, pp. 462\u2013479. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-98648-7_27"},{"key":"16_CR25","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-662-56509-4","volume-title":"Fundamentals of Business Process Management","author":"M Dumas","year":"2018","unstructured":"Dumas, M., La Rosa, M., Mendling, J., Reijers, H.A.: Fundamentals of Business Process Management, 2nd edn. Springer, Berlin (2018). https:\/\/doi.org\/10.1007\/978-3-662-56509-4","edition":"2"},{"key":"16_CR26","doi-asserted-by":"crossref","unstructured":"Dunzer, S., Stierle, M., Matzner, M., Baier, S.: Conformance checking: a state-of-the-art literature review. In: Proceedings of the 11th International Conference on Subject-Oriented Business Process Management, S-BPM ONE 2019, Seville, Spain, 26\u201328 June 2019, pp. 4:1\u20134:10. ACM (2019)","DOI":"10.1145\/3329007.3329014"},{"key":"16_CR27","unstructured":"Eggers, J., Hein, A.: Turning big data into value: a literature review on business value realization from process mining. In: 28th European Conference on Information Systems, ECIS 2020 (2020)"},{"issue":"3","key":"16_CR28","doi-asserted-by":"publisher","first-page":"577","DOI":"10.1007\/s10257-015-0295-2","volume":"14","author":"R Engel","year":"2016","unstructured":"Engel, R.: Analyzing inter-organizational business processes - process mining and business performance analysis using electronic data interchange messages. Inf. Syst. E Bus. Manag. 14(3), 577\u2013612 (2016)","journal-title":"Inf. Syst. E Bus. Manag."},{"key":"16_CR29","doi-asserted-by":"publisher","first-page":"24543","DOI":"10.1109\/ACCESS.2018.2831244","volume":"6","author":"T Erdogan","year":"2018","unstructured":"Erdogan, T., Tarhan, A.: Systematic mapping of process mining studies in healthcare. IEEE Access 6, 24543\u201324567 (2018)","journal-title":"IEEE Access"},{"key":"16_CR30","doi-asserted-by":"publisher","first-page":"220","DOI":"10.1016\/j.is.2013.12.007","volume":"47","author":"D Fahland","year":"2015","unstructured":"Fahland, D., van der Aalst, W.M.P.: Model repair - aligning process models to reality. Inf. Syst. 47, 220\u2013243 (2015)","journal-title":"Inf. Syst."},{"key":"16_CR31","unstructured":"Fink, A.: Conducting Research Literature Reviews: From the Internet to Paper. Sage Publications (2019)"},{"key":"16_CR32","unstructured":"Franz, P., Kirchmer, M.: Value-Driven Business Process Management: The Value-Switch for Lasting Competitive Advantage. McGraw Hill Professional (2012)"},{"issue":"1","key":"16_CR33","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1504\/IJEH.2016.078745","volume":"9","author":"M Ghasemi","year":"2016","unstructured":"Ghasemi, M., Amyot, D.: Process mining in healthcare: a systematised literature review. Int. J. Electron. Heal. 9(1), 60\u201388 (2016)","journal-title":"Int. J. Electron. Heal."},{"key":"16_CR34","doi-asserted-by":"crossref","unstructured":"Ghazal, M.A., Ibrahim, O., Salama, M.A.: Educational process mining: a systematic literature review. In: 2017 European Conference on Electrical Engineering and Computer Science (EECS), pp. 198\u2013203. IEEE (2017)","DOI":"10.1109\/EECS.2017.45"},{"issue":"3","key":"16_CR35","doi-asserted-by":"publisher","first-page":"277","DOI":"10.1007\/s12599-020-00649-w","volume":"63","author":"T Graafmans","year":"2021","unstructured":"Graafmans, T., Turetken, O., Poppelaars, H., Fahland, D.: Process mining for six sigma: a guideline and tool support. Bus. Inf. Syst. Eng. 63(3), 277\u2013300 (2021). https:\/\/doi.org\/10.1007\/s12599-020-00649-w","journal-title":"Bus. Inf. Syst. Eng."},{"key":"16_CR36","unstructured":"Gr\u00fcger, J., Bergmann, R., Kazik, Y., Kuhn, M.: Process mining for case acquisition in oncology: a systematic literature review. In: Proceedings of the Conference on \u201cLernen, Wissen, Daten, Analysen\u201d, Online, 9\u201311 September 2020, vol. 2738, pp. 162\u2013173. CEUR Workshop Proceedings. CEUR-WS.org (2020)"},{"key":"16_CR37","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"177","DOI":"10.1007\/978-3-319-59536-8_12","volume-title":"Advanced Information Systems Engineering","author":"BFA Hompes","year":"2017","unstructured":"Hompes, B.F.A., Maaradji, A., La Rosa, M., Dumas, M., Buijs, J.C.A.M., van der Aalst, W.M.P.: Discovering causal factors explaining business process performance variation. In: Dubois, E., Pohl, K. (eds.) CAiSE 2017. LNCS, vol. 10253, pp. 177\u2013192. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-59536-8_12"},{"issue":"1","key":"16_CR38","doi-asserted-by":"publisher","first-page":"4","DOI":"10.1109\/JBHI.2013.2274281","volume":"18","author":"Z Huang","year":"2014","unstructured":"Huang, Z., Dong, W., Duan, H., Li, H.: Similarity measure between patient traces for clinical pathway analysis: problem, method, and applications. IEEE J. Biomed. Health Inf. 18(1), 4\u201314 (2014)","journal-title":"IEEE J. Biomed. Health Inf."},{"issue":"7","key":"16_CR39","doi-asserted-by":"publisher","first-page":"6458","DOI":"10.1016\/j.eswa.2011.12.061","volume":"39","author":"Z Huang","year":"2012","unstructured":"Huang, Z., Lu, X., Duan, H.: Resource behavior measure and application in business process management. Exp. Syst. Appl. 39(7), 6458\u20136468 (2012)","journal-title":"Exp. Syst. Appl."},{"key":"16_CR40","doi-asserted-by":"crossref","unstructured":"Jaisook, P., Premchaiswadi, W.: Time performance analysis of medical treatment processes by using disco. In: 2015 13th International Conference on ICT and Knowledge Engineering, ICT & Knowledge Engineering 2015, pp. 110\u2013115. IEEE (2015)","DOI":"10.1109\/ICTKE.2015.7368480"},{"issue":"6","key":"16_CR41","doi-asserted-by":"publisher","first-page":"4626","DOI":"10.11591\/ijece.v8i6.pp4626-4636","volume":"8","author":"B Jokonowo","year":"2018","unstructured":"Jokonowo, B., Claes, J., Sarno, R., Rochimah, S.: Process mining in supply chains: a systematic literature review. Int. J. Electr. Comput. Eng. (IJECE) 8(6), 4626\u20134636 (2018)","journal-title":"Int. J. Electr. Comput. Eng. (IJECE)"},{"key":"16_CR42","series-title":"Lecture Notes in Business Information Processing","doi-asserted-by":"publisher","first-page":"484","DOI":"10.1007\/978-3-319-74030-0_38","volume-title":"Business Process Management Workshops","author":"AA Kalenkova","year":"2018","unstructured":"Kalenkova, A.A., Ageev, A.A., Lomazova, I.A., van\u00a0der Aalst, W.M.P.: E-government services: comparing real and expected user behavior. In: Teniente, E., Weidlich, M. (eds.) BPM 2017. LNBIP, vol. 308, pp. 484\u2013496. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-74030-0_38"},{"issue":"5","key":"16_CR43","doi-asserted-by":"publisher","first-page":"995","DOI":"10.1108\/BPMJ-02-2018-0051","volume":"25","author":"AA Kalenkova","year":"2019","unstructured":"Kalenkova, A.A., Burattin, A., de Leoni, M., van der Aalst, W.M.P., Sperduti, A.: Discovering high-level BPMN process models from event data. Bus. Process. Manag. J. 25(5), 995\u20131019 (2019)","journal-title":"Bus. Process. Manag. J."},{"key":"16_CR44","series-title":"Lecture Notes in Business Information Processing","doi-asserted-by":"publisher","first-page":"224","DOI":"10.1007\/978-3-319-06257-0_18","volume-title":"Business Process Management Workshops","author":"A Kim","year":"2014","unstructured":"Kim, A., Obregon, J., Jung, J.-Y.: Constructing decision trees from process logs for performer recommendation. In: Lohmann, N., Song, M., Wohed, P. (eds.) BPM 2013. LNBIP, vol. 171, pp. 224\u2013236. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-06257-0_18"},{"key":"16_CR45","unstructured":"Kitchenham, B.: Procedures for performing systematic reviews. Keele University, Keele, UK 33(2004), 1\u201326 (2004)"},{"key":"16_CR46","doi-asserted-by":"crossref","unstructured":"de Leoni, M., Marrella, A.: Aligning real process executions and prescriptive process models through automated planning. Exp. Syst. Appl. 82, 162\u2013183 (2017)","DOI":"10.1016\/j.eswa.2017.03.047"},{"key":"16_CR47","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"297","DOI":"10.1007\/978-3-319-23063-4_21","volume-title":"Business Process Management","author":"A Leontjeva","year":"2015","unstructured":"Leontjeva, A., Conforti, R., Di Francescomarino, C., Dumas, M., Maggi, F.M.: Complex symbolic sequence encodings for predictive monitoring of business processes. In: Motahari-Nezhad, H.R., Recker, J., Weidlich, M. (eds.) BPM 2015. LNCS, vol. 9253, pp. 297\u2013313. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-23063-4_21"},{"key":"16_CR48","doi-asserted-by":"publisher","first-page":"209","DOI":"10.1016\/j.is.2015.02.007","volume":"54","author":"LT Ly","year":"2015","unstructured":"Ly, L.T., Maggi, F.M., Montali, M., Rinderle-Ma, S., van der Aalst, W.M.P.: Compliance monitoring in business processes: functionalities, application, and tool-support. Inf. Syst. 54, 209\u2013234 (2015)","journal-title":"Inf. Syst."},{"issue":"10","key":"16_CR49","doi-asserted-by":"publisher","first-page":"2140","DOI":"10.1109\/TKDE.2017.2720601","volume":"29","author":"A Maaradji","year":"2017","unstructured":"Maaradji, A., Dumas, M., La Rosa, M., Ostovar, A.: Detecting sudden and gradual drifts in business processes from execution traces. IEEE Trans. Knowl. Data Eng. 29(10), 2140\u20132154 (2017)","journal-title":"IEEE Trans. Knowl. Data Eng."},{"key":"16_CR50","series-title":"Lecture Notes in Business Information Processing","doi-asserted-by":"publisher","first-page":"182","DOI":"10.1007\/978-3-642-20511-8_16","volume-title":"Business Process Management Workshops","author":"FM Maggi","year":"2011","unstructured":"Maggi, F.M., Corapi, D., Russo, A., Lupu, E., Visaggio, G.: Revising process models through inductive learning. In: zur Muehlen, M., Su, J. (eds.) BPM 2010. LNBIP, vol. 66, pp. 182\u2013193. Springer, Heidelberg (2011). https:\/\/doi.org\/10.1007\/978-3-642-20511-8_16"},{"key":"16_CR51","doi-asserted-by":"publisher","first-page":"136","DOI":"10.1016\/j.is.2017.12.002","volume":"74","author":"FM Maggi","year":"2018","unstructured":"Maggi, F.M., Di Ciccio, C., Di Francescomarino, C., Kala, T.: Parallel algorithms for the automated discovery of declarative process models. Inf. Syst. 74, 136\u2013152 (2018)","journal-title":"Inf. Syst."},{"key":"16_CR52","doi-asserted-by":"crossref","unstructured":"Maggi, F.M., Montali, M., van der Aalst, W.M.P.: An operational decision support framework for monitoring business constraints. In: 15th International Conference on Fundamental Approaches to Software Engineering, FASE 2012, Held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2012, Tallinn, Estonia, pp. 146\u2013162 (2012)","DOI":"10.1007\/978-3-642-28872-2_11"},{"key":"16_CR53","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"392","DOI":"10.1007\/978-3-319-10172-9_27","volume-title":"Business Process Management","author":"FM Maggi","year":"2014","unstructured":"Maggi, F.M., Slaats, T., Reijers, H.A.: The automated discovery of hybrid processes. In: Sadiq, S., Soffer, P., V\u00f6lzer, H. (eds.) BPM 2014. LNCS, vol. 8659, pp. 392\u2013399. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-10172-9_27"},{"issue":"5","key":"16_CR54","doi-asserted-by":"publisher","first-page":"505","DOI":"10.1080\/17517575.2017.1402371","volume":"12","author":"ARC Maita","year":"2018","unstructured":"Maita, A.R.C., Martins, L.C., Paz, C.R.L., Rafferty, L., Hung, P.C.K., Peres, S.M., Fantinato, M.: A systematic mapping study of process mining. Enterp. Inf. Syst. 12(5), 505\u2013549 (2018)","journal-title":"Enterp. Inf. Syst."},{"key":"16_CR55","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"},{"key":"16_CR56","series-title":"Lecture Notes in Business Information Processing","doi-asserted-by":"publisher","first-page":"371","DOI":"10.1007\/978-3-319-93931-5_27","volume-title":"Business Information Systems","author":"F Milani","year":"2018","unstructured":"Milani, F., Maggi, F.M.: A comparative evaluation of log-based process performance analysis techniques. In: Abramowicz, W., Paschke, A. (eds.) BIS 2018. LNBIP, vol. 320, pp. 371\u2013383. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-93931-5_27"},{"issue":"4","key":"16_CR57","doi-asserted-by":"crossref","first-page":"1232","DOI":"10.18421\/TEM84-18","volume":"8","author":"V Naderifar","year":"2019","unstructured":"Naderifar, V., Sahran, S., Shukur, Z.: A review on conformance checking technique for the evaluation of process mining algorithms. TEM J. 8(4), 1232 (2019)","journal-title":"TEM J."},{"key":"16_CR58","doi-asserted-by":"crossref","unstructured":"Navarin, N., Vincenzi, B., Polato, M., Sperduti, A.: LSTM networks for data-aware remaining time prediction of business process instances. In: 2017 IEEE Symposium Series on Computational Intelligence, SSCI 2017, Honolulu, HI, USA, pp. 1\u20137. IEEE (2017)","DOI":"10.1109\/SSCI.2017.8285184"},{"key":"16_CR59","doi-asserted-by":"publisher","first-page":"984","DOI":"10.1016\/j.procs.2019.11.208","volume":"161","author":"I Nuritha","year":"2019","unstructured":"Nuritha, I., Mahendrawathi, E.: Behavioural similarity measurement of business process model to compare process discovery algorithms performance in dealing with noisy event log. Procedia Comput. Sci. 161, 984\u2013993 (2019)","journal-title":"Procedia Comput. Sci."},{"key":"16_CR60","first-page":"43","volume":"37","author":"C Okoli","year":"2015","unstructured":"Okoli, C.: A guide to conducting a standalone systematic literature review. Commun. Assoc. Inf. Syst. 37, 43 (2015)","journal-title":"Commun. Assoc. Inf. Syst."},{"key":"16_CR61","doi-asserted-by":"publisher","first-page":"224","DOI":"10.1016\/j.jbi.2016.04.007","volume":"61","author":"E Rojas","year":"2016","unstructured":"Rojas, E., Munoz-Gama, J., Sep\u00falveda, M., Capurro, D.: Process mining in healthcare: a literature review. J. Biomed. Inf. 61, 224\u2013236 (2016)","journal-title":"J. Biomed. Inf."},{"key":"16_CR62","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":"16_CR63","doi-asserted-by":"publisher","first-page":"260","DOI":"10.1016\/j.eswa.2019.05.003","volume":"133","author":"C dos Santos Garcia","year":"2019","unstructured":"dos Santos Garcia, C., et al.: Process mining techniques and applications - a systematic mapping study. Exp. Syst. Appl. 133, 260\u2013295 (2019)","journal-title":"Exp. Syst. Appl."},{"key":"16_CR64","series-title":"Lecture Notes in Business Information Processing","doi-asserted-by":"publisher","first-page":"230","DOI":"10.1007\/978-3-319-74030-0_17","volume-title":"Business Process Management Workshops","author":"A Seeliger","year":"2018","unstructured":"Seeliger, A., Stein, M., M\u00fchlh\u00e4user, M.: Can we find better process models? Process model improvement using motif-based graph adaptation. In: Teniente, E., Weidlich, M. (eds.) BPM 2017. LNBIP, vol. 308, pp. 230\u2013242. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-74030-0_17"},{"key":"16_CR65","doi-asserted-by":"publisher","first-page":"278","DOI":"10.1016\/j.is.2015.03.010","volume":"53","author":"A Senderovich","year":"2015","unstructured":"Senderovich, A., Weidlich, M., Gal, A., Mandelbaum, A.: Queue mining for delay prediction in multi-class service processes. Inf. Syst. 53, 278\u2013295 (2015)","journal-title":"Inf. Syst."},{"key":"16_CR66","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"477","DOI":"10.1007\/978-3-319-59536-8_30","volume-title":"Advanced Information Systems Engineering","author":"N Tax","year":"2017","unstructured":"Tax, N., Verenich, I., La Rosa, M., Dumas, M.: Predictive business process monitoring with LSTM neural networks. In: Dubois, E., Pohl, K. (eds.) CAiSE 2017. LNCS, vol. 10253, pp. 477\u2013492. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-59536-8_30"},{"key":"16_CR67","doi-asserted-by":"crossref","unstructured":"Taymouri, F., La Rosa, M., Dumas, M., Maggi, F.M.: Business process variant analysis: survey and classification. Knowl. Based Syst. 211, 106557 (2021)","DOI":"10.1016\/j.knosys.2020.106557"},{"key":"16_CR68","doi-asserted-by":"crossref","unstructured":"Teinemaa, I., Dumas, M., La Rosa, M., Maggi, F.M.: Outcome-oriented predictive process monitoring: review and benchmark. ACM Trans. Knowl. Discov. Data 13(2), 17:1\u201317:57 (2019)","DOI":"10.1145\/3301300"},{"key":"16_CR69","doi-asserted-by":"publisher","unstructured":"Teinemaa, I., Tax, N., de Leoni, M., Dumas, M., Maggi, F.M.: Alarm-based prescriptive process monitoring. In: Weske, M., Montali, M., Weber, I., vom Brocke, J. (eds.) BPM 2018. LNBIP, vol. 329, pp. 91\u2013107. Springer, Cham (2018). https:\/\/doi.org\/10.1007\/978-3-319-98651-7_6","DOI":"10.1007\/978-3-319-98651-7_6"},{"issue":"4","key":"16_CR70","doi-asserted-by":"publisher","first-page":"900","DOI":"10.1108\/BPMJ-06-2017-0148","volume":"24","author":"M Thiede","year":"2018","unstructured":"Thiede, M., Fuerstenau, D., Barquet, A.P.B.: How is process mining technology used by organizations? A systematic literature review of empirical studies. Bus. Process. Manag. J. 24(4), 900\u2013922 (2018)","journal-title":"Bus. Process. Manag. J."},{"key":"16_CR71","doi-asserted-by":"crossref","unstructured":"Thomas, L., Kumar, M.M., Annappa, B.: Recommending an alternative path of execution using an online decision support system. In: Proceedings of the 2017 International Conference on Intelligent Systems, Metaheuristics & Swarm Intelligence, pp. 108\u2013112 (2017)","DOI":"10.1145\/3059336.3059361"},{"key":"16_CR72","doi-asserted-by":"crossref","unstructured":"Tu, T.B.H., Song, M.: Analysis and prediction cost of manufacturing process based on process mining. In: 2016 International Conference on Industrial Engineering, Management Science and Application (ICIMSA), pp. 1\u20135. IEEE (2016)","DOI":"10.1109\/ICIMSA.2016.7503993"},{"key":"16_CR73","doi-asserted-by":"crossref","unstructured":"Verenich, I., Dumas, M., La Rosa, M., Maggi, F.M., Teinemaa, I.: Survey and cross-benchmark comparison of remaining time prediction methods in business process monitoring. ACM Trans. Intell. Syst. Technol. 10(4), 34:1\u201334:34 (2019)","DOI":"10.1145\/3331449"},{"key":"16_CR74","doi-asserted-by":"crossref","unstructured":"Yan, J., Hu, D., Liao, S.S.Y., Wang, H.: Mining agents\u2019 goals in agent-oriented business processes. ACM Trans. Manag. Inf. Syst. 5(4), 20:1\u201320:22 (2015)","DOI":"10.1145\/2629448"},{"key":"16_CR75","doi-asserted-by":"crossref","unstructured":"Zhao, W., Liu, H., Dai, W., Ma, J.: An entropy-based clustering ensemble method to support resource allocation in business process management. Knowl. Inf. Syst. 48(2), 305\u2013330 (2016)","DOI":"10.1007\/s10115-015-0879-7"},{"key":"16_CR76","doi-asserted-by":"publisher","unstructured":"Zhao, W., Yang, L., Liu, H., Wu, R.: The optimization of resource allocation based on process mining. In: Huang, D.-S., Han, K. (eds.) ICIC 2015. LNCS (LNAI), vol. 9227, pp. 341\u2013353. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-22053-6_38","DOI":"10.1007\/978-3-319-22053-6_38"}],"container-title":["Lecture Notes in Business Information Processing","Research Challenges in Information Science"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-05760-1_16","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,9,24]],"date-time":"2024-09-24T17:35:42Z","timestamp":1727199342000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-05760-1_16"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9783031057595","9783031057601"],"references-count":76,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-05760-1_16","relation":{},"ISSN":["1865-1348","1865-1356"],"issn-type":[{"value":"1865-1348","type":"print"},{"value":"1865-1356","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"14 May 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"RCIS","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Research Challenges in Information Science","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Barcelona","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Spain","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2022","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 May 2022","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"20 May 2022","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"16","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"rcis2022","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.rcis-conf.com\/rcis2022\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}