{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,9]],"date-time":"2024-09-09T13:28:24Z","timestamp":1725888504483},"publisher-location":"Cham","reference-count":19,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319597577"},{"type":"electronic","value":"9783319597584"}],"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"},{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"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":[[2017]]},"DOI":"10.1007\/978-3-319-59758-4_3","type":"book-chapter","created":{"date-parts":[[2017,5,29]],"date-time":"2017-05-29T17:33:42Z","timestamp":1496079222000},"page":"24-36","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["CAREDAS: Context and Activity Recognition Enabling Detection of Anomalous Situation"],"prefix":"10.1007","author":[{"given":"Hela","family":"Sfar","sequence":"first","affiliation":[]},{"given":"Nathan","family":"Ramoly","sequence":"additional","affiliation":[]},{"given":"Amel","family":"Bouzeghoub","sequence":"additional","affiliation":[]},{"given":"Beatrice","family":"Finance","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,5,30]]},"reference":[{"key":"3_CR1","series-title":"Lecture Notes in Computer Science","doi-asserted-by":"publisher","first-page":"465","DOI":"10.1007\/978-3-319-48472-3_28","volume-title":"On the Move to Meaningful Internet Systems","author":"A Jarraya","year":"2016","unstructured":"Jarraya, A., Ramoly, N., Bouzeghoub, A., Arour, K., Borgi, A., Finance, B.: FSCEP: a new model for context perception in smart homes. In: Debruyne, C., et al. (eds.) OTM 2016. LNCS, vol. 10033, pp. 465\u2013484. Springer, Cham (2016). doi:10.1007\/978-3-319-48472-3_28"},{"unstructured":"Jarraya, A., Ramoly, N., Bouzeghoub, A., Arour, K., Borgi, A., Finance, B.: A fuzzy semantic CEP model for situation identification in smart homes. In: ECAI (2016)","key":"3_CR2"},{"doi-asserted-by":"crossref","unstructured":"Sfar, H., Bouzeghoub, A., Ramoly, N., Boudy, J.: AGACY monitoring: a hybrid model for activity recognition and uncertainty handling. In: ESWC (2017)","key":"3_CR3","DOI":"10.1007\/978-3-319-58068-5_16"},{"unstructured":"Melisachew, C., Jakob, H., Christian, M., Heiner, S.: Markov logic networks with numerical constraints. In: ECAI (2016)","key":"3_CR4"},{"key":"3_CR5","doi-asserted-by":"publisher","first-page":"107","DOI":"10.1007\/s10994-006-5833-1","volume":"62","author":"R Matthew","year":"2006","unstructured":"Matthew, R., Pedros, D.: Markov logic networks. Mach. Learn. 62, 107\u2013136 (2006)","journal-title":"Mach. Learn."},{"doi-asserted-by":"crossref","unstructured":"Dubois, D., Lang, J., Prade, H.: Automated reasoning using possibilistic logic: semantics, belief revision, and variable certainty weights. In: TKDE, vol. 6 (1994)","key":"3_CR6","DOI":"10.1109\/69.273026"},{"doi-asserted-by":"crossref","unstructured":"Hoque, E., Dickerson, F.R., Preum, S.M.: Holmes: a comprehensive anomaly detection system for daily in-home activities. In: DCOSS (2016)","key":"3_CR7","DOI":"10.1109\/DCOSS.2015.20"},{"key":"3_CR8","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1016\/j.artmed.2015.12.001","volume":"67","author":"D Riboni","year":"2016","unstructured":"Riboni, D., Bettini, C., Civitares, G., Janjua, Z.H.: SmartFABER: recognizing fine-grained abnormal behaviors for early detection of mild cognitive impairment. Artif. Intell. Med. 67, 57\u201374 (2016)","journal-title":"Artif. Intell. Med."},{"doi-asserted-by":"crossref","unstructured":"Janjua, Z.H., Riboni, D., Bettini, C.: Towards automatic induction of abnormal behavioral patterns for recognizing mild cognitive impairment. In: SAC (2016)","key":"3_CR9","DOI":"10.1145\/2851613.2851687"},{"key":"3_CR10","doi-asserted-by":"publisher","first-page":"36","DOI":"10.1016\/j.pmcj.2011.01.004","volume":"9","author":"J Ye","year":"2012","unstructured":"Ye, J., Dobson, S., McKeever, M.: Situation identification techniques in pervasive computing: a review. Pervasive Mob. Comput. 9, 36\u201366 (2012)","journal-title":"Pervasive Mob. Comput."},{"key":"3_CR11","doi-asserted-by":"publisher","first-page":"71","DOI":"10.1016\/j.knosys.2015.10.014","volume":"92","author":"J Huang","year":"2016","unstructured":"Huang, J., Zhu, Q., Feng, L.Y.J.: A non-parameter outlier detection algorithm based on Natural Neighbor. Knowl.-Based Syst. 92, 71\u201377 (2016)","journal-title":"Knowl.-Based Syst."},{"unstructured":"Jakkula, V., Cook, D.J.: Detecting anomalous sensor events in smart home data for enhancing the living experience. In: AIII (2011)","key":"3_CR12"},{"key":"3_CR13","doi-asserted-by":"publisher","first-page":"5363","DOI":"10.3390\/s120505363","volume":"12","author":"Y Han","year":"2012","unstructured":"Han, Y., Han, M., Lee, S., Sarkar, A.M.J., Lee, Y.K.: A framework for supervising lifestyle diseases using long-term activity monitoring. Sensors 12, 5363\u20135379 (2012)","journal-title":"Sensors"},{"key":"3_CR14","doi-asserted-by":"publisher","first-page":"205","DOI":"10.1007\/s12652-010-0043-x","volume":"3","author":"A Lot","year":"2012","unstructured":"Lot, A., Langensiepen, C., Mahmoud, S.M., Akhlaghinia, M.J.: Smart homes for the elderly dementia suerers: identication and prediction of abnormal behavior. J. Ambient Intell. Humaniz Comput. 3, 205\u2013218 (2012)","journal-title":"J. Ambient Intell. Humaniz Comput."},{"doi-asserted-by":"crossref","unstructured":"Novak, M., Binas, M., Jakab, F.: Unobtrusive anomaly detection in presence of elderly in a smart-home environment. In: ELEKTRO (2012)","key":"3_CR15","DOI":"10.1109\/ELEKTRO.2012.6225617"},{"unstructured":"Novak, M., Jakab, F., Lain, L.: Anomaly detection in user daily patterns in smart-home environment. In: JSHI, vol. 3 (2013)","key":"3_CR16"},{"doi-asserted-by":"crossref","unstructured":"Riboni, D., Bettini, C., Civitarese, G., Janjua, Z.H., Helaoui, R.: Fine-grained recognition of abnormal behaviors for early detection of mild cognitive impairment. In: PerCom (2015)","key":"3_CR17","DOI":"10.1109\/PERCOM.2015.7146521"},{"key":"3_CR18","doi-asserted-by":"publisher","first-page":"733","DOI":"10.1002\/int.21544","volume":"27","author":"DT Anderson","year":"2012","unstructured":"Anderson, D.T., Ros, M., Keller, J.M., Cuellar, M.P., Popescu, M., Delgado, M., Vila, A.: Similarity measure for anomaly detection and comparing human behaviors. Int. J. Intell. Syst. 27, 733\u2013756 (2012)","journal-title":"Int. J. Intell. Syst."},{"doi-asserted-by":"crossref","unstructured":"Chen, H., Ku, W.S., Wang, H., Tang, L., Sun, M.T.: Scaling up Markov logic probabilistic inference for social graphs. In: TKDE, vol. 29 (2016)","key":"3_CR19","DOI":"10.1109\/TKDE.2016.2625251"}],"container-title":["Lecture Notes in Computer Science","Artificial Intelligence in Medicine"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-59758-4_3","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,4,2]],"date-time":"2024-04-02T16:39:14Z","timestamp":1712075954000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-59758-4_3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"ISBN":["9783319597577","9783319597584"],"references-count":19,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-59758-4_3","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2017]]},"assertion":[{"value":"30 May 2017","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"AIME","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Conference on Artificial Intelligence in Medicine in Europe","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Vienna","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Austria","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":"21 June 2017","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"24 June 2017","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":"aime2017","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/aime17.aimedicine.info\/home.html","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}