{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,31]],"date-time":"2026-03-31T00:06:27Z","timestamp":1774915587422,"version":"3.50.1"},"publisher-location":"Cham","reference-count":21,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783319986500","type":"print"},{"value":"9783319986517","type":"electronic"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-319-98651-7_6","type":"book-chapter","created":{"date-parts":[[2018,8,11]],"date-time":"2018-08-11T08:06:20Z","timestamp":1533974780000},"page":"91-107","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["Alarm-Based Prescriptive Process Monitoring"],"prefix":"10.1007","author":[{"given":"Irene","family":"Teinemaa","sequence":"first","affiliation":[]},{"given":"Niek","family":"Tax","sequence":"additional","affiliation":[]},{"given":"Massimiliano","family":"de Leoni","sequence":"additional","affiliation":[]},{"given":"Marlon","family":"Dumas","sequence":"additional","affiliation":[]},{"given":"Fabrizio Maria","family":"Maggi","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,8,12]]},"reference":[{"key":"6_CR1","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"457","DOI":"10.1007\/978-3-319-07881-6_31","volume-title":"Advanced Information Systems Engineering","author":"FM Maggi","year":"2014","unstructured":"Maggi, F.M., Di Francescomarino, C., Dumas, M., Ghidini, C.: Predictive monitoring of business processes. In: Jarke, M., et al. (eds.) CAiSE 2014. LNCS, vol. 8484, pp. 457\u2013472. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-07881-6_31"},{"issue":"2","key":"6_CR2","doi-asserted-by":"publisher","first-page":"276","DOI":"10.1109\/TSMC.2014.2347265","volume":"45","author":"A Metzger","year":"2015","unstructured":"Metzger, A., et al.: Comparing and combining predictive business process monitoring techniques. IEEE Trans. Syst. Man Cybern. Syst. 45(2), 276\u2013290 (2015)","journal-title":"IEEE Trans. Syst. Man Cybern. Syst."},{"key":"6_CR3","unstructured":"Teinemaa, I., Dumas, M., La Rosa, M., Maggi, F.M.: Outcome-oriented predictive process monitoring: review and benchmark. arXiv preprint arXiv:1707.06766 (2017)"},{"key":"6_CR4","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"232","DOI":"10.1007\/978-3-319-69462-7_15","volume-title":"On the Move to Meaningful Internet Systems","author":"M Dees","year":"2017","unstructured":"Dees, M., de Leoni, M., Mannhardt, F.: Enhancing process models to improve business performance: a methodology and case studies. In: Panetto, H., et al. (eds.) OTM 2017. LNCS, vol. 10573, pp. 232\u2013251. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-69462-7_15"},{"key":"6_CR5","unstructured":"Elkan, C.: The foundations of cost-sensitive learning. In: Proceedings of IJCAI, vol. 17, pp. 973\u2013978. Lawrence Erlbaum Associates Ltd. (2001)"},{"key":"6_CR6","unstructured":"Sheng, V.S., Ling, C.X.: Thresholding for making classifiers cost-sensitive. In: AAAI, pp. 476\u2013481 (2006)"},{"key":"6_CR7","unstructured":"Bergstra, J.S., Bardenet, R., Bengio, Y., K\u00e9gl, B.: Algorithms for hyper-parameter optimization. In: Proceedings of NIPS, pp. 2546\u20132554 (2011)"},{"issue":"1","key":"6_CR8","first-page":"3133","volume":"15","author":"M Fern\u00e1ndez-Delgado","year":"2014","unstructured":"Fern\u00e1ndez-Delgado, M., Cernadas, E., Barro, S., Amorim, D.: Do we need hundreds of classifiers to solve real world classification problems. JMLR 15(1), 3133\u20133181 (2014)","journal-title":"JMLR"},{"key":"6_CR9","doi-asserted-by":"crossref","unstructured":"Olson, R.S., La Cava, W., Mustahsan, Z., Varik, A., Moore, J.H.: Data-driven advice for applying machine learning to bioinformatics problems. In: Proceedings of Biocomputing. World Scientific (2017)","DOI":"10.1142\/9789813235533_0018"},{"key":"6_CR10","doi-asserted-by":"publisher","first-page":"235","DOI":"10.1016\/j.is.2015.07.003","volume":"56","author":"M de Leoni","year":"2016","unstructured":"de Leoni, M., van der Aalst, W.M.P., Dees, M.: A general process mining framework for correlating, predicting and clustering dynamic behavior based on event logs. Inf. Syst. 56, 235\u2013257 (2016)","journal-title":"Inf. Syst."},{"key":"6_CR11","doi-asserted-by":"crossref","unstructured":"Zadrozny, B., Elkan, C.: Learning and making decisions when costs and probabilities are both unknown. In: Proceedings of KDD, pp. 204\u2013213. ACM (2001)","DOI":"10.1145\/502512.502540"},{"issue":"3","key":"6_CR12","first-page":"61","volume":"10","author":"J Platt","year":"1999","unstructured":"Platt, J., et al.: Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods. Adv. Large Margin Classif. 10(3), 61\u201374 (1999)","journal-title":"Adv. Large Margin Classif."},{"key":"6_CR13","unstructured":"Turney, P.D.: Types of cost in inductive concept learning. In: Proceedings of the Cost-Sensitive Learning Workshop (2002)"},{"issue":"1","key":"6_CR14","first-page":"105","volume":"31","author":"Z Xing","year":"2012","unstructured":"Xing, Z., Pei, J., Philip, S.Y.: Early classification on time series. KAIS 31(1), 105\u2013127 (2012)","journal-title":"KAIS"},{"key":"6_CR15","doi-asserted-by":"publisher","unstructured":"Mori, U., Mendiburu, A., Dasgupta, S., Lozano, J.A.: Early classification of time series by simultaneously optimizing the accuracy and earliness. IEEE Trans. Neural Netw. Learn. Syst. (2017). https:\/\/doi.org\/10.1109\/TNNLS.2017.2764939","DOI":"10.1109\/TNNLS.2017.2764939"},{"key":"6_CR16","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"433","DOI":"10.1007\/978-3-319-23528-8_27","volume-title":"Machine Learning and Knowledge Discovery in Databases","author":"A Dachraoui","year":"2015","unstructured":"Dachraoui, A., Bondu, A., Cornu\u00e9jols, A.: Early classification of time series as a non myopic sequential decision making problem. In: Appice, A., Rodrigues, P.P., Santos Costa, V., Soares, C., Gama, J., Jorge, A. (eds.) ECML PKDD 2015. LNCS (LNAI), vol. 9284, pp. 433\u2013447. Springer, Cham (2015). https:\/\/doi.org\/10.1007\/978-3-319-23528-8_27"},{"key":"6_CR17","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"632","DOI":"10.1007\/978-3-319-46128-1_40","volume-title":"Machine Learning and Knowledge Discovery in Databases","author":"R Tavenard","year":"2016","unstructured":"Tavenard, R., Malinowski, S.: Cost-aware early classification of time series. In: Frasconi, P., Landwehr, N., Manco, G., Vreeken, J. (eds.) ECML PKDD 2016. LNCS (LNAI), vol. 9851, pp. 632\u2013647. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46128-1_40"},{"key":"6_CR18","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"445","DOI":"10.1007\/978-3-319-59536-8_28","volume-title":"Advanced Information Systems Engineering","author":"A Metzger","year":"2017","unstructured":"Metzger, A., F\u00f6cker, F.: Predictive business process monitoring considering reliability estimates. In: Dubois, E., Pohl, K. (eds.) CAiSE 2017. LNCS, vol. 10253, pp. 445\u2013460. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-59536-8_28"},{"key":"6_CR19","doi-asserted-by":"publisher","unstructured":"Di Francescomarino, C., Dumas, M., Maggi, F.M., Teinemaa, I.: Clustering-based predictive process monitoring. IEEE Trans. Serv. Comput. (2017). https:\/\/doi.org\/10.1109\/TSC.2016.2645153","DOI":"10.1109\/TSC.2016.2645153"},{"key":"6_CR20","series-title":"Lecture Notes in Business Information Processing","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1007\/978-3-319-06695-0_3","volume-title":"Business Information Systems","author":"C Gr\u00f6ger","year":"2014","unstructured":"Gr\u00f6ger, C., Schwarz, H., Mitschang, B.: Prescriptive analytics for recommendation-based business process optimization. In: Abramowicz, W., Kokkinaki, A. (eds.) BIS 2014. LNBIP, vol. 176, pp. 25\u201337. Springer, Cham (2014). https:\/\/doi.org\/10.1007\/978-3-319-06695-0_3"},{"key":"6_CR21","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.dss.2014.10.006","volume":"69","author":"R Conforti","year":"2015","unstructured":"Conforti, R., de Leoni, M., La Rosa, M., van der Aalst, W.M.P., ter Hofstede, A.H.M.: A recommendation system for predicting risks across multiple business process instances. Decis. Support Syst. 69, 1\u201319 (2015)","journal-title":"Decis. Support Syst."}],"container-title":["Lecture Notes in Business Information Processing","Business Process Management Forum"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-98651-7_6","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,7]],"date-time":"2024-03-07T15:06:36Z","timestamp":1709823996000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-98651-7_6"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783319986500","9783319986517"],"references-count":21,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-98651-7_6","relation":{},"ISSN":["1865-1348","1865-1356"],"issn-type":[{"value":"1865-1348","type":"print"},{"value":"1865-1356","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018]]},"assertion":[{"value":"12 August 2018","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"BPM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Business Process Management","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Sydney, NSW","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Australia","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":"9 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":"16","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"bpm2018","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/bpm2018.web.cse.unsw.edu.au\/","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":"113","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":"14","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":"12% - 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)"}}]}}