{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,4]],"date-time":"2026-05-04T10:26:18Z","timestamp":1777890378919,"version":"3.51.4"},"publisher-location":"Cham","reference-count":25,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031610561","type":"print"},{"value":"9783031610578","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[[2024]]},"DOI":"10.1007\/978-3-031-61057-8_5","type":"book-chapter","created":{"date-parts":[[2024,6,2]],"date-time":"2024-06-02T20:17:29Z","timestamp":1717359449000},"page":"71-86","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Enhancing Predictive Process Monitoring with\u00a0Time-Related Feature Engineering"],"prefix":"10.1007","author":[{"given":"Rafael Seidi","family":"Oyamada","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gabriel Marques","family":"Tavares","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sylvio Barbon","family":"Junior","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Paolo","family":"Ceravolo","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,6,3]]},"reference":[{"key":"5_CR1","doi-asserted-by":"crossref","unstructured":"van\u00a0der Aalst, W.M.P.: Process Mining - Data Science in Action, 2nd edn. (2016)","DOI":"10.1007\/978-3-662-49851-4"},{"key":"5_CR2","unstructured":"Alcoba\u00e7a, E., Siqueira, F., Rivolli, A., Garcia, L.P.F., Oliva, J.T., de\u00a0Carvalho, A.C.P.L.F.: MFE: towards reproducible meta-feature extraction. J. Mach. Learn. Res. (2020)"},{"key":"5_CR3","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"286","DOI":"10.1007\/978-3-030-26619-6_19","volume-title":"Business Process Management","author":"M Camargo","year":"2019","unstructured":"Camargo, M., Dumas, M., Gonz\u00e1lez-Rojas, O.: Learning accurate LSTM models of business processes. In: Hildebrandt, T., van Dongen, B.F., R\u00f6glinger, M., Mendling, J. (eds.) BPM 2019. LNCS, vol. 11675, pp. 286\u2013302. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-26619-6_19"},{"key":"5_CR4","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"55","DOI":"10.1007\/978-3-031-07472-1_4","volume-title":"Advanced Information Systems Engineering","author":"M Camargo","year":"2022","unstructured":"Camargo, M., Dumas, M., Gonz\u00e1lez-Rojas, O.: Learning accurate business process simulation models from event logs via automated process discovery and deep learning. In: Franch, X., Poels, G., Gailly, F., Snoeck, M. (eds.) CAiSE 2022. LNCS, vol. 13295, pp. 55\u201371. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-07472-1_4"},{"key":"5_CR5","doi-asserted-by":"crossref","unstructured":"Ceravolo, P., Tavares, G.M., Junior, S.B., Damiani, E.: Evaluation goals for online process mining: a concept drift perspective. IEEE Trans. Serv. Comput. (2022)","DOI":"10.1109\/SERVICES55459.2022.00040"},{"key":"5_CR6","doi-asserted-by":"crossref","unstructured":"Galanti, R., et al.: An explainable decision support system for predictive process analytics. Eng. Appl. Artif. Intell. (2023)","DOI":"10.1016\/j.engappai.2023.105904"},{"key":"5_CR7","unstructured":"Grinsztajn, L., Oyallon, E., Varoquaux, G.: Why do tree-based models still outperform deep learning on typical tabular data? In: NIPS (2022)"},{"key":"5_CR8","doi-asserted-by":"crossref","unstructured":"Hancock, J.T., Khoshgoftaar, T.M.: Catboost for big data: an interdisciplinary review. J. Big Data (2020)","DOI":"10.21203\/rs.3.rs-54646\/v2"},{"key":"5_CR9","doi-asserted-by":"crossref","unstructured":"Kim, J., Comuzzi, M., Dumas, M., Maggi, F.M., Teinemaa, I.: Encoding resource experience for predictive process monitoring. Decis. Support Syst. (2022)","DOI":"10.1016\/j.dss.2021.113669"},{"key":"5_CR10","doi-asserted-by":"crossref","unstructured":"Krishna, S., et al.: The disagreement problem in explainable machine learning: a practitioner\u2019s perspective. CoRR (2022)","DOI":"10.21203\/rs.3.rs-2963888\/v1"},{"key":"5_CR11","unstructured":"Liu, Y., Khandagale, S., White, C., Neiswanger, W.: Synthetic benchmarks for scientific research in explainable machine learning. In: Vanschoren, J., Yeung, S. (eds.) NIPS (2021)"},{"key":"5_CR12","unstructured":"Lundberg, S.M., Lee, S.: A unified approach to interpreting model predictions. In: Guyon, I., et al. (eds.) NIPS (2017)"},{"key":"5_CR13","doi-asserted-by":"crossref","unstructured":"Mozafari Mehr, A.S., de Carvalho, R.M., van Dongen, B.: Explainable conformance checking: understanding patterns of anomalous behavior. Eng. Appl. Artif. Intell. (2023)","DOI":"10.1016\/j.engappai.2023.106827"},{"key":"5_CR14","doi-asserted-by":"crossref","unstructured":"Munappy, A., Bosch, J., Olsson, H.H., Arpteg, A., Brinne, B.: Data management challenges for deep learning. In: SEAA (2019)","DOI":"10.1109\/SEAA.2019.00030"},{"key":"5_CR15","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: SSCI (2017)","DOI":"10.1109\/SSCI.2017.8285184"},{"key":"5_CR16","doi-asserted-by":"crossref","unstructured":"Polato, M., Sperduti, A., Burattin, A., de\u00a0Leoni, M.: Time and activity sequence prediction of business process instances. Computing (2018)","DOI":"10.1007\/s00607-018-0593-x"},{"key":"5_CR17","doi-asserted-by":"crossref","unstructured":"Rama-Maneiro, E., Vidal, J., Lama, M.: Deep learning for predictive business process monitoring: review and benchmark. IEEE TSC (2021)","DOI":"10.1109\/TSC.2021.3139807"},{"key":"5_CR18","series-title":"Lecture Notes in Business Information Processing","doi-asserted-by":"publisher","first-page":"141","DOI":"10.1007\/978-3-030-58638-6_9","volume-title":"Business Process Management Forum","author":"W Rizzi","year":"2020","unstructured":"Rizzi, W., Di Francescomarino, C., Maggi, F.M.: Explainability in predictive process monitoring: when understanding helps improving. In: Fahland, D., Ghidini, C., Becker, J., Dumas, M. (eds.) BPM 2020. LNBIP, vol. 392, pp. 141\u2013158. Springer, Cham (2020). https:\/\/doi.org\/10.1007\/978-3-030-58638-6_9"},{"key":"5_CR19","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"306","DOI":"10.1007\/978-3-319-65000-5_18","volume-title":"Business Process Management","author":"A Senderovich","year":"2017","unstructured":"Senderovich, A., Di Francescomarino, C., Ghidini, C., Jorbina, K., Maggi, F.M.: Intra and inter-case features in predictive process monitoring: a tale of two dimensions. In: Carmona, J., Engels, G., Kumar, A. (eds.) BPM 2017. LNCS, vol. 10445, pp. 306\u2013323. Springer, Cham (2017). https:\/\/doi.org\/10.1007\/978-3-319-65000-5_18"},{"key":"5_CR20","doi-asserted-by":"crossref","unstructured":"Tavares, G.M., Oyamada, R.S., Barbon, S., Ceravolo, P.: Trace encoding in process mining: a survey and benchmarking. Eng. Appl. Artif. Intell. (2023)","DOI":"10.1016\/j.engappai.2023.107028"},{"key":"5_CR21","doi-asserted-by":"crossref","unstructured":"Tavares, G.M., Barbon\u00a0Junior, S., Damiani, E., Ceravolo, P.: Selecting optimal trace clustering pipelines with meta-learning. Intell. Syst. (2022)","DOI":"10.1007\/978-3-031-21686-2_11"},{"key":"5_CR22","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":"5_CR23","doi-asserted-by":"crossref","unstructured":"Teinemaa, I., Dumas, M., Rosa, M.L., Maggi, F.M.: Outcome-oriented predictive process monitoring: review and benchmark. ACM Trans. Knowl. Discov. Data (2019)","DOI":"10.1145\/3301300"},{"key":"5_CR24","doi-asserted-by":"crossref","unstructured":"Verenich, I., Dumas, M., Rosa, M.L., Maggi, F.M., Teinemaa, I.: Survey and cross-benchmark comparison of remaining time prediction methods in business process monitoring. ACM Trans. Intell. Syst. Technol. (2019)","DOI":"10.1145\/3331449"},{"key":"5_CR25","series-title":"Lecture Notes in Business Information Processing","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1007\/978-3-030-94343-1_2","volume-title":"Business Process Management Workshops","author":"H Weytjens","year":"2022","unstructured":"Weytjens, H., De Weerdt, J.: Creating unbiased public benchmark datasets with data leakage prevention for predictive process monitoring. In: Marrella, A., Weber, B. (eds.) BPM 2021. LNBIP, vol. 436, pp. 18\u201329. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-030-94343-1_2"}],"container-title":["Lecture Notes in Computer Science","Advanced Information Systems Engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-61057-8_5","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,2]],"date-time":"2024-06-02T20:18:10Z","timestamp":1717359490000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-61057-8_5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031610561","9783031610578"],"references-count":25,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-61057-8_5","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"3 June 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this article.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"value":"CAiSE","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Advanced Information Systems Engineering","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Limassol","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Cyprus","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"3 June 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"7 June 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"36","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"caise2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/cyprusconferences.org\/caise2024\/#","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}