{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,2]],"date-time":"2025-08-02T14:31:33Z","timestamp":1754145093692,"version":"3.41.2"},"publisher-location":"New York, NY, USA","reference-count":34,"publisher":"ACM","funder":[{"name":"European Commission","award":["CREXDATA? Critical Action Planning over Extreme-Scale Data 101092749"],"award-info":[{"award-number":["CREXDATA? Critical Action Planning over Extreme-Scale Data 101092749"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2025,6,10]]},"DOI":"10.1145\/3701717.3730539","type":"proceedings-article","created":{"date-parts":[[2025,7,16]],"date-time":"2025-07-16T13:52:43Z","timestamp":1752673963000},"page":"9-20","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Run-Time Adaptation of Complex Event Forecasting"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2959-2022","authenticated-orcid":false,"given":"Manolis","family":"Pitsikalis","sequence":"first","affiliation":[{"name":"NCSR Demokritos, Athens, Greece"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9260-0024","authenticated-orcid":false,"given":"Elias","family":"Alevizos","sequence":"additional","affiliation":[{"name":"NCSR Demokritos, Athens, Greece and The American College of Greece, Athens, Greece"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8218-707X","authenticated-orcid":false,"given":"Nikos","family":"Giatrakos","sequence":"additional","affiliation":[{"name":"Technical University of Crete, Chania, Greece"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6899-4599","authenticated-orcid":false,"given":"Alexander","family":"Artikis","sequence":"additional","affiliation":[{"name":"NCSR Demokritos, Athens, Greece and University of Piraeus, Piraeus, Greece"}]}],"member":"320","published-online":{"date-parts":[[2025,6,9]]},"reference":[{"key":"e_1_3_3_3_2_2","volume-title":"LPAR","author":"Alevizos Elias","year":"2018","unstructured":"Elias Alevizos, Alexander Artikis, and George Paliouras. 2018. Wayeb: a Tool for Complex Event Forecasting. In LPAR."},{"key":"e_1_3_3_3_3_2","doi-asserted-by":"crossref","unstructured":"Elias Alevizos Alexander Artikis and Georgios Paliouras. 2022. Complex event forecasting with prediction suffix trees. VLDB J. 31 1 (2022) 157\u2013180.","DOI":"10.1007\/s00778-021-00698-x"},{"key":"e_1_3_3_3_4_2","doi-asserted-by":"publisher","DOI":"10.1145\/3093742.3093912"},{"key":"e_1_3_3_3_5_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-61852-0"},{"key":"e_1_3_3_3_6_2","doi-asserted-by":"crossref","unstructured":"Ron Begleiter Ran El-Yaniv and Golan Yona. 2004. On Prediction Using Variable Order Markov Models. J. Artif. Intell. Res. 22 (2004) 385\u2013421.","DOI":"10.1613\/jair.1491"},{"key":"e_1_3_3_3_7_2","unstructured":"Eric Brochu Vlad\u00a0M. Cora and Nando de Freitas. 2010. A Tutorial on Bayesian Optimization of Expensive Cost Functions with Application to Active User Modeling and Hierarchical Reinforcement Learning."},{"key":"e_1_3_3_3_8_2","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/458"},{"key":"e_1_3_3_3_9_2","doi-asserted-by":"publisher","DOI":"10.1109\/EDOCW.2016.7584363"},{"key":"e_1_3_3_3_10_2","doi-asserted-by":"publisher","DOI":"10.1145\/2002259.2002279"},{"key":"e_1_3_3_3_11_2","doi-asserted-by":"crossref","unstructured":"Matthias Feurer Jost Springenberg and Frank Hutter. 2015. Initializing Bayesian Hyperparameter Optimization via Meta-Learning. AAAI 29 (2015).","DOI":"10.1609\/aaai.v29i1.9354"},{"key":"e_1_3_3_3_12_2","doi-asserted-by":"publisher","DOI":"10.1145\/3340531.3412706"},{"key":"e_1_3_3_3_13_2","doi-asserted-by":"crossref","unstructured":"Ioannis Flouris Nikos Giatrakos Antonios Deligiannakis Minos\u00a0N. Garofalakis Michael Kamp and Michael Mock. 2017. Issues in complex event processing: Status and prospects in the Big Data era. J. Syst. Softw. 127 (2017) 217\u2013236.","DOI":"10.1016\/j.jss.2016.06.011"},{"key":"e_1_3_3_3_14_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-98648-7_27"},{"key":"e_1_3_3_3_15_2","doi-asserted-by":"crossref","unstructured":"Peter\u00a0I. Frazier. 2018. A Tutorial on Bayesian Optimization.","DOI":"10.1287\/educ.2018.0188"},{"key":"e_1_3_3_3_16_2","doi-asserted-by":"publisher","DOI":"10.1145\/2371316.2371323"},{"key":"e_1_3_3_3_17_2","doi-asserted-by":"crossref","unstructured":"Jo\u00e3o Gama Indrundefined \u017dliobaitundefined Albert Bifet Mykola Pechenizkiy and Abdelhamid Bouchachia. 2014. A survey on concept drift adaptation. ACM Comput. Surv. 46 (2014) 189:1\u2013189:38.","DOI":"10.1145\/2523813"},{"key":"e_1_3_3_3_18_2","doi-asserted-by":"crossref","unstructured":"Nikos Giatrakos Elias Alevizos Alexander Artikis Antonios Deligiannakis and Minos\u00a0N. Garofalakis. 2020. Complex event recognition in the Big Data era: a survey. VLDB J. 29 1 (2020) 313\u2013352.","DOI":"10.1007\/s00778-019-00557-w"},{"key":"e_1_3_3_3_19_2","doi-asserted-by":"publisher","DOI":"10.1145\/3459637.3482094"},{"key":"e_1_3_3_3_20_2","doi-asserted-by":"crossref","unstructured":"Herodotos Herodotou Yuxing Chen and Jiaheng Lu. 2020. A Survey on Automatic Parameter Tuning for Big Data Processing Systems. ACM Comput. Surv. 53 2 (2020) 43:1\u201343:37.","DOI":"10.1145\/3381027"},{"key":"e_1_3_3_3_21_2","doi-asserted-by":"crossref","unstructured":"Yan Li Tingjian Ge and Cindy\u00a0X. Chen. 2020. Data Stream Event Prediction Based on Timing Knowledge and State Transitions. Proc. VLDB Endow. 13 10 (2020) 1779\u20131792.","DOI":"10.14778\/3401960.3401973"},{"key":"e_1_3_3_3_22_2","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2018\/584"},{"key":"e_1_3_3_3_23_2","doi-asserted-by":"publisher","DOI":"10.1145\/2002259.2002307"},{"key":"e_1_3_3_3_24_2","doi-asserted-by":"crossref","unstructured":"Alfonso\u00a0Eduardo M\u00e1rquez-Chamorro Manuel Resinas and Antonio Ruiz-Cort\u00e9s. 2018. Predictive Monitoring of Business Processes: A Survey. IEEE Trans. Services Computing 11 6 (2018) 962\u2013977.","DOI":"10.1109\/TSC.2017.2772256"},{"key":"e_1_3_3_3_25_2","volume-title":"Introduction to time series analysis and forecasting","author":"Montgomery Douglas\u00a0C","year":"2015","unstructured":"Douglas\u00a0C Montgomery, Cheryl\u00a0L Jennings, and Murat Kulahci. 2015. Introduction to time series analysis and forecasting. John Wiley & Sons."},{"key":"e_1_3_3_3_26_2","doi-asserted-by":"publisher","DOI":"10.1145\/1827418.1827423"},{"key":"e_1_3_3_3_27_2","doi-asserted-by":"publisher","DOI":"10.4108\/icst.collaboratecom.2011.247129"},{"key":"e_1_3_3_3_28_2","volume-title":"EDBT","author":"Patroumpas Kostas","year":"2015","unstructured":"Kostas Patroumpas, Alexander Artikis, Nikos Katzouris, Marios Vodas, Yannis Theodoridis, and Nikos Pelekis. 2015. Event Recognition for Maritime Surveillance. In EDBT."},{"key":"e_1_3_3_3_29_2","doi-asserted-by":"publisher","DOI":"10.1145\/3328905.3329762"},{"key":"e_1_3_3_3_30_2","doi-asserted-by":"crossref","unstructured":"Cyril Ray Richard Dr\u00e9o Elena Camossi Anne-Laure Jousselme and Cl\u00e9ment Iphar. 2019. Heterogeneous integrated dataset for Maritime Intelligence surveillance and reconnaissance. Data in Brief 25 (2019) 104141.","DOI":"10.1016\/j.dib.2019.104141"},{"key":"e_1_3_3_3_31_2","volume-title":"NIPS","author":"Ron Dana","year":"1993","unstructured":"Dana Ron, Yoram Singer, and Naftali Tishby. 1993. The Power of Amnesia. In NIPS."},{"key":"e_1_3_3_3_32_2","doi-asserted-by":"crossref","unstructured":"Dana Ron Yoram Singer and Naftali Tishby. 1996. The Power of Amnesia: Learning Probabilistic Automata with Variable Memory Length. Machine Learning 25 2-3 (1996) 117\u2013149.","DOI":"10.1023\/A:1026490906255"},{"key":"e_1_3_3_3_33_2","doi-asserted-by":"publisher","DOI":"10.1145\/3524860.3539810"},{"key":"e_1_3_3_3_34_2","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-19345-3"},{"key":"e_1_3_3_3_35_2","doi-asserted-by":"crossref","unstructured":"Li Yang and Abdallah Shami. 2020. On hyperparameter optimization of machine learning algorithms: Theory and practice. Neurocomputing 415 (2020) 295\u2013316.","DOI":"10.1016\/j.neucom.2020.07.061"}],"event":{"name":"DEBS '25: The 19th ACM International Conference on Distributed and Event-based Systems","sponsor":["SIGMOD ACM Special Interest Group on Management of Data","SIGSOFT ACM Special Interest Group on Software Engineering"],"location":"Gothenburg Sweden","acronym":"DEBS '25"},"container-title":["Proceedings of the 19th ACM International Conference on Distributed and Event-based Systems"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3701717.3730539","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,7,16]],"date-time":"2025-07-16T13:52:46Z","timestamp":1752673966000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3701717.3730539"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,6,9]]},"references-count":34,"alternative-id":["10.1145\/3701717.3730539","10.1145\/3701717"],"URL":"https:\/\/doi.org\/10.1145\/3701717.3730539","relation":{},"subject":[],"published":{"date-parts":[[2025,6,9]]},"assertion":[{"value":"2025-06-09","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}