{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T15:27:06Z","timestamp":1783610826521,"version":"3.55.0"},"publisher-location":"Cham","reference-count":16,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783319694610","type":"print"},{"value":"9783319694627","type":"electronic"}],"license":[{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"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":[[2017]]},"DOI":"10.1007\/978-3-319-69462-7_28","type":"book-chapter","created":{"date-parts":[[2017,10,19]],"date-time":"2017-10-19T04:13:28Z","timestamp":1508386408000},"page":"429-447","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Big Data Summarisation and Relevance Evaluation for Anomaly Detection in Cyber Physical Systems"],"prefix":"10.1007","author":[{"given":"Ada","family":"Bagozi","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Devis","family":"Bianchini","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Valeria","family":"De Antonellis","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alessandro","family":"Marini","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Davide","family":"Ragazzi","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2017,10,20]]},"reference":[{"key":"28_CR1","doi-asserted-by":"crossref","unstructured":"Aggarwal, C., Han, J., Wang, J., Yu, P.: A framework for clustering evolving data streams. In: Proceedings of 29th International Conference on Very Large Data Bases, pp. 81\u201392 (2003)","DOI":"10.1016\/B978-012722442-8\/50016-1"},{"key":"28_CR2","doi-asserted-by":"crossref","unstructured":"Bagozi, A., Bianchini, D., De Antonellis, V., Marini, A., Ragazzi, D.: Interactive data exploration as a service for the smart factory. In: Proceedings of IEEE International Conference on Web Services (ICWS) (2017)","DOI":"10.1109\/ICWS.2017.129"},{"key":"28_CR3","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"264","DOI":"10.1007\/978-3-319-59536-8_17","volume-title":"Advanced Information Systems Engineering","author":"A Bagozi","year":"2017","unstructured":"Bagozi, A., Bianchini, D., De Antonellis, V., Marini, A., Ragazzi, D.: Summarisation and relevance evaluation techniques for big data exploration: the smart factory case study. In: Dubois, E., Pohl, K. (eds.) CAiSE 2017. LNCS, vol. 10253, pp. 264\u2013279. Springer, Cham (2017). doi:10.1007\/978-3-319-59536-8_17"},{"key":"28_CR4","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"80","DOI":"10.1007\/978-3-319-48472-3_5","volume-title":"On the Move to Meaningful Internet Systems: OTM 2016 Conferences","author":"K B\u00f6hmer","year":"2016","unstructured":"B\u00f6hmer, K., Rinderle-Ma, S.: Multi-perspective anomaly detection in business process execution events. In: Debruyne, C., et al. (eds.) OTM 2016. LNCS, vol. 10033, pp. 80\u201398. Springer, Cham (2016). doi:10.1007\/978-3-319-48472-3_5"},{"key":"28_CR5","doi-asserted-by":"crossref","unstructured":"Gorecky, D., Schmitt, M., Loskyll, M., Zuhlke, D.: Human-machine interaction in the Industry 4.0 era. In: IEEE International Conference on Industrial Informatics, pp. 289\u2013294 (2014)","DOI":"10.1109\/INDIN.2014.6945523"},{"issue":"4","key":"28_CR6","first-page":"23","volume":"52","author":"T Hanamori","year":"2016","unstructured":"Hanamori, T., Nishimura, T.: Real-time monitoring solution to detect symptoms of system anomalies. FUJITSU Sci. Tech. J. 52(4), 23\u201327 (2016)","journal-title":"FUJITSU Sci. Tech. J."},{"key":"28_CR7","unstructured":"Huber, M., Voigt, M., Ngomo, A.: Big data architecture for the semantic analysis of complex events in manufacturing. In: Proceedings of GI Jahrestagung, pp. 353\u2013360 (2016)"},{"key":"28_CR8","doi-asserted-by":"crossref","unstructured":"Khalifa, S., Elshater, Y., Sundaravarathan, K., Bhat, A., Martin, P., Imam, F., Rope, D., Mcroberts, M., Statchuk, C.: The six pillars for building big data analytics ecosystems. ACM Comput. Surv. 49(2) (2016)","DOI":"10.1145\/2963143"},{"key":"28_CR9","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1016\/j.procir.2015.08.026","volume":"38","author":"J Lee","year":"2015","unstructured":"Lee, J., Ardakani, H.D., Yang, S., Bagheri, B.: Industrial big data analytics and cyber-physical systems for future maintenance and service innovation. Procedia CIRP 38, 3\u20137 (2015)","journal-title":"Procedia CIRP"},{"key":"28_CR10","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1016\/j.mfglet.2014.12.001","volume":"3","author":"J Lee","year":"2015","unstructured":"Lee, J., Bagheri, B., Kao, H.: A cyber-physical systems architecture for Industry 4.0-based manufacturing systems. Manuf. Lett. 3, 18\u201323 (2015)","journal-title":"Manuf. Lett."},{"issue":"1","key":"28_CR11","doi-asserted-by":"publisher","first-page":"38","DOI":"10.1016\/j.mfglet.2013.09.005","volume":"1","author":"J Lee","year":"2013","unstructured":"Lee, J., Lapira, E., Bagheri, B., Kao, H.: Recent advances and trends in predictive manufacturing systems in big data environment. Manuf. Letters 1(1), 38\u201341 (2013)","journal-title":"Manuf. Letters"},{"key":"28_CR12","doi-asserted-by":"crossref","unstructured":"Marini, A., Bianchini, D.: Big data as a service for monitoring cyber-physical production systems. In: Proceedings of 30th European Conference on Modelling and Simulation (ECMS), pp. 579\u2013586 (2016)","DOI":"10.7148\/2016-0579"},{"key":"28_CR13","doi-asserted-by":"publisher","first-page":"92","DOI":"10.1016\/j.ress.2013.11.006","volume":"124","author":"R Moghaddass","year":"2014","unstructured":"Moghaddass, R., Zuo, M.J.: An integrated framework for online diagnostic and prognostic health monitoring using a multistate deterioration process. Reliabil. Eng. Syst. Saf. 124, 92\u2013104 (2014)","journal-title":"Reliabil. Eng. Syst. Saf."},{"key":"28_CR14","unstructured":"Pelleg, D., Moore, A.: X-means: extending k-means with efficient estimation of the number of clusters. In: Proceedings of 17th International Conference on Machine Learning (ICML), pp. 727\u2013734 (2000)"},{"key":"28_CR15","doi-asserted-by":"crossref","unstructured":"Stojanovic, L., Dinic, M., Stojanovic, N., Stojadinovic, A: Big-data-driven anomaly detection in Industry (4.0): an approach and a case study. In: Proceedings of IEEE International Conference on Big Data, pp. 1647\u20131652 (2016)","DOI":"10.1109\/BigData.2016.7840777"},{"key":"28_CR16","doi-asserted-by":"crossref","unstructured":"Wang, F., Agrawal, G.: Effective and efficient sampling methods for deep web aggregation queries. In: Proceedings of Conference on Extending Database Technology (EDBT), pp. 425\u2013436 (2011)","DOI":"10.1145\/1951365.1951416"}],"container-title":["Lecture Notes in Computer Science","On the Move to Meaningful Internet Systems. OTM 2017 Conferences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-69462-7_28","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T18:05:51Z","timestamp":1710266751000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-69462-7_28"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"ISBN":["9783319694610","9783319694627"],"references-count":16,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-69462-7_28","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017]]},"assertion":[{"value":"20 October 2017","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"OTM","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"OTM Confederated International Conferences \"On the Move to Meaningful Internet Systems\"","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Rhodes","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Greece","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2017","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 October 2017","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"28 October 2017","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"otm2017","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/www.otmconferences.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}