{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,1]],"date-time":"2025-11-01T16:46:44Z","timestamp":1762015604757,"version":"3.41.0"},"reference-count":51,"publisher":"Association for Computing Machinery (ACM)","issue":"2","license":[{"start":{"date-parts":[[2016,12,3]],"date-time":"2016-12-03T00:00:00Z","timestamp":1480723200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"EU Horizon 2020 OrganiCity grant"},{"name":"EU-FP7 SOCIOTAL grant"},{"name":"Australian Research Council (ARC) Linkage Project","award":["LP120100529"],"award-info":[{"award-number":["LP120100529"]}]},{"name":"ARC Linkage Infrastructure"},{"name":"Equipment and Facilities scheme","award":["LF120100129"],"award-info":[{"award-number":["LF120100129"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Knowl. Discov. Data"],"published-print":{"date-parts":[[2017,5,31]]},"abstract":"<jats:p>The growth in pervasive network infrastructure called the Internet of Things (IoT) enables a wide range of physical objects and environments to be monitored in fine spatial and temporal detail. The detailed, dynamic data that are collected in large quantities from sensor devices provide the basis for a variety of applications. Automatic interpretation of these evolving large data is required for timely detection of interesting events. This article develops and exemplifies two new relatives of the visual assessment of tendency (VAT) and improved visual assessment of tendency (iVAT) models, which uses cluster heat maps to visualize structure in static datasets. One new model is initialized with a static VAT\/iVAT image, and then incrementally (hence inc-VAT\/inc-iVAT) updates the current minimal spanning tree (MST) used by VAT with an efficient edge insertion scheme. Similarly, dec-VAT\/dec-iVAT efficiently removes a node from the current VAT MST. A sequence of inc-iVAT\/dec-iVAT images can be used for (visual) anomaly detection in evolving data streams and for sliding window based cluster assessment for time series data. The method is illustrated with four real datasets (three of them being smart city IoT data). The evaluation demonstrates the algorithms\u2019 ability to successfully isolate anomalies and visualize changing cluster structure in the streaming data.<\/jats:p>","DOI":"10.1145\/2997656","type":"journal-article","created":{"date-parts":[[2016,12,5]],"date-time":"2016-12-05T16:47:16Z","timestamp":1480956436000},"page":"1-40","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":21,"title":["Adaptive Cluster Tendency Visualization and Anomaly Detection for Streaming Data"],"prefix":"10.1145","volume":"11","author":[{"given":"Dheeraj","family":"Kumar","sequence":"first","affiliation":[{"name":"The University of Melbourne, Australia"}]},{"given":"James C.","family":"Bezdek","sequence":"additional","affiliation":[{"name":"The University of Melbourne, Australia"}]},{"given":"Sutharshan","family":"Rajasegarar","sequence":"additional","affiliation":[{"name":"The University of Melbourne, Australia"}]},{"given":"Marimuthu","family":"Palaniswami","sequence":"additional","affiliation":[{"name":"The University of Melbourne, Australia"}]},{"given":"Christopher","family":"Leckie","sequence":"additional","affiliation":[{"name":"The University of Melbourne, Australia"}]},{"given":"Jeffrey","family":"Chan","sequence":"additional","affiliation":[{"name":"The University of Melbourne, Australia"}]},{"given":"Jayavardhana","family":"Gubbi","sequence":"additional","affiliation":[{"name":"The University of Melbourne, Australia"}]}],"member":"320","published-online":{"date-parts":[[2016,12,3]]},"reference":[{"volume-title":"Proceedings of the International Conference on Very Large Data Bases (VLDB). 81--92","author":"Aggarwal C. C.","key":"e_1_2_2_1_1"},{"key":"e_1_2_2_2_1","first-page":"2","article-title":"The irises of the Gaspe peninsula","volume":"59","author":"Anderson E.","year":"1935","journal-title":"Bulletin of American Iris Society"},{"volume-title":"Evolving Intelligent Systems: Methodology and Applications","author":"Angelov P.","key":"e_1_2_2_3_1","doi-asserted-by":"crossref","DOI":"10.1002\/9780470569962"},{"key":"e_1_2_2_4_1","unstructured":"ARUP. 2015. http:\/\/www.arup.com\/Global_locations\/Australia.aspx.  ARUP. 2015. http:\/\/www.arup.com\/Global_locations\/Australia.aspx."},{"key":"e_1_2_2_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/773153.773176"},{"key":"e_1_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.1016\/0020-0190(76)90071-5"},{"volume-title":"Proceedings of the International Joint Conference on Neural Networks (IJCNN)","year":"2002","author":"Bezdek J.","key":"e_1_2_2_7_1"},{"key":"e_1_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/TFUZZ.2006.889956"},{"key":"e_1_2_2_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/MCI.2011.940751"},{"volume-title":"Classe des sciences math\u00e9matiques et naturelles 6","year":"1934","author":"Delaunay B.","key":"e_1_2_2_10_1"},{"volume-title":"ACM-SIAM Symposium on Discrete Algorithms (SODA). 743--752","author":"Demaine E. D.","key":"e_1_2_2_11_1"},{"key":"e_1_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1007\/BF01386390"},{"key":"e_1_2_2_13_1","doi-asserted-by":"crossref","unstructured":"N. Elmqvist P. Dragicevic and J. D. Fekete. 2008. Rolling the dice: Multidimensional visual exploration using scatterplot matrix navigation. IEEE Trans. Vis. Comput. Graphics 14(6) (2008) 1539--1548.  N. Elmqvist P. Dragicevic and J. D. Fekete. 2008. Rolling the dice: Multidimensional visual exploration using scatterplot matrix navigation. IEEE Trans. Vis. Comput. Graphics 14(6) (2008) 1539--1548.","DOI":"10.1109\/TVCG.2008.153"},{"key":"e_1_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.1145\/146370.146381"},{"key":"e_1_2_2_15_1","unstructured":"D. Greene D. Archambault V. Bel\u00e1k and P. Cunningham. 2015. TextLuas: Tracking and visualizing document and term clusters in dynamic text data. CoRR abs\/1502.04609 (2015).  D. Greene D. Archambault V. Bel\u00e1k and P. Cunningham. 2015. TextLuas: Tracking and visualizing document and term clusters in dynamic text data. CoRR abs\/1502.04609 (2015)."},{"key":"e_1_2_2_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.future.2013.01.010"},{"key":"e_1_2_2_17_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2006.02.011"},{"key":"e_1_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2011.33"},{"key":"e_1_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10472-009-9157-2"},{"key":"e_1_2_2_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0167-8655(03)00003-5"},{"volume-title":"Australia.","year":"2015","key":"e_1_2_2_21_1"},{"volume-title":"O jist\u00e9m probl\u00e9mu minim\u00e1ln\u00edm. Pr\u00e1ce Moravsk\u00e9 P\u0159\u00edrodov\u011bdeck\u00e9 Spole\u010dnosti 6","year":"1930","author":"Jarn\u00edk V.","key":"e_1_2_2_22_1"},{"key":"e_1_2_2_23_1","doi-asserted-by":"publisher","DOI":"10.1137\/0215021"},{"key":"e_1_2_2_24_1","doi-asserted-by":"publisher","DOI":"10.1090\/S0002-9939-1956-0078686-7"},{"key":"e_1_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCYB.2015.2477416"},{"key":"e_1_2_2_26_1","unstructured":"D. Kumar J. C. Bezdek S. Rajasegarar C. Leckie and M. Palaniswami. 2015. A visual-numeric approach to clustering and anomaly detection for trajectory data. Vis. Comput. (2015) 1--17.  D. Kumar J. C. Bezdek S. Rajasegarar C. Leckie and M. Palaniswami. 2015. A visual-numeric approach to clustering and anomaly detection for trajectory data. Vis. Comput. (2015) 1--17."},{"volume-title":"Proceedings of the IEEE International Conference on Big Data. 112--117","author":"Kumar D.","key":"e_1_2_2_27_1"},{"volume-title":"Proceedings of the IEEE Pacific Visualization Symposium (PACIFICVIS). 171--178","author":"Lampe O. D.","key":"e_1_2_2_28_1"},{"key":"e_1_2_2_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/1835804.1835882"},{"key":"e_1_2_2_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/TFUZZ.2014.2322385"},{"key":"e_1_2_2_31_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.enpol.2013.07.090"},{"key":"e_1_2_2_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/505241.505243"},{"key":"e_1_2_2_33_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4612-1098-6"},{"key":"e_1_2_2_34_1","doi-asserted-by":"publisher","DOI":"10.1002\/j.1538-7305.1957.tb01515.x"},{"key":"e_1_2_2_35_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2014.04.006"},{"volume-title":"Proceedings of the IEEE International Conference on Communication Systems (ICCS)","year":"2006","author":"Rajasegarar S.","key":"e_1_2_2_36_1"},{"volume-title":"Proceedings of the IEEE International Conference on Communications (ICC). 3864--3869","author":"Rajasegarar S.","key":"e_1_2_2_37_1"},{"key":"e_1_2_2_38_1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-8659.2011.01955.x"},{"volume-title":"Reshaping Energy Demands Using ICT","year":"2013","author":"REDUCE","key":"e_1_2_2_39_1"},{"key":"e_1_2_2_40_1","doi-asserted-by":"publisher","DOI":"10.1109\/SFCS.1975.8"},{"key":"e_1_2_2_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/1754414.1754419"},{"volume-title":"Proceedings of the International Conference on Recent Advances in Internet of Things (RIoT). 1--6.","author":"Shilton A.","key":"e_1_2_2_42_1"},{"key":"e_1_2_2_43_1","doi-asserted-by":"publisher","DOI":"10.1080\/07474940802446236"},{"key":"e_1_2_2_44_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2009.192"},{"volume-title":"Proceedings of the Annual IEEE Conference on Information Visualization (INFOVIS). 97--104","author":"Wong P. C.","key":"e_1_2_2_45_1"},{"volume-title":"Retrieved","year":"2016","key":"e_1_2_2_46_1"},{"key":"e_1_2_2_47_1","doi-asserted-by":"publisher","DOI":"10.1145\/2109196.2109201"},{"key":"e_1_2_2_48_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.is.2012.08.001"},{"key":"e_1_2_2_49_1","doi-asserted-by":"publisher","DOI":"10.14778\/2536274.2536312"},{"key":"e_1_2_2_50_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.peva.2010.08.018"},{"key":"e_1_2_2_51_1","doi-asserted-by":"publisher","DOI":"10.5555\/3225662.3225976"}],"container-title":["ACM Transactions on Knowledge Discovery from Data"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2997656","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/2997656","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T03:50:12Z","timestamp":1750218612000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2997656"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,12,3]]},"references-count":51,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2017,5,31]]}},"alternative-id":["10.1145\/2997656"],"URL":"https:\/\/doi.org\/10.1145\/2997656","relation":{},"ISSN":["1556-4681","1556-472X"],"issn-type":[{"type":"print","value":"1556-4681"},{"type":"electronic","value":"1556-472X"}],"subject":[],"published":{"date-parts":[[2016,12,3]]},"assertion":[{"value":"2015-06-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2016-09-01","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2016-12-03","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}