{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,22]],"date-time":"2025-02-22T05:26:27Z","timestamp":1740201987470,"version":"3.37.3"},"reference-count":0,"publisher":"IOS Press","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2011]]},"abstract":"<jats:p>We have designed a framework for Bayesian Statistical Anomaly Detection, called ISC, or Incremental Stream Clustering. It learns the normal situation incrementally, and can on the fly detect anomalous cases. When this happens, a new cluster can be created, so similar cases can be detected in the future. In this way, the framework performs incremental clustering, while at the same time either classifying a new case as belonging to one of the known clusters or indicating that it is from a previously unseen situation.<\/jats:p>","DOI":"10.3233\/978-1-60750-754-3-100","type":"book-chapter","created":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T10:27:05Z","timestamp":1740133625000},"source":"Crossref","is-referenced-by-count":0,"title":["Incremental Stream Clustering for Anomaly Detection and Classification"],"prefix":"10.3233","author":[{"family":"Holst Anders","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"family":"Ekman Jan","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Eleventh Scandinavian Conference on Artificial Intelligence"],"original-title":[],"deposited":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T10:36:55Z","timestamp":1740134215000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.medra.org\/servlet\/aliasResolver?alias=iospressISSNISBN&issn=0922-6389&volume=227&spage=100"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2011]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/978-1-60750-754-3-100","relation":{},"ISSN":["0922-6389"],"issn-type":[{"value":"0922-6389","type":"print"}],"subject":[],"published":{"date-parts":[[2011]]}}}