{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T21:10:22Z","timestamp":1776114622384,"version":"3.50.1"},"publisher-location":"New York, New York, USA","reference-count":14,"publisher":"ACM Press","license":[{"start":{"date-parts":[[2015,1,1]],"date-time":"2015-01-01T00:00:00Z","timestamp":1420070400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1346066"],"award-info":[{"award-number":["1346066"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2015]]},"DOI":"10.1145\/2800835.2801617","type":"proceedings-article","created":{"date-parts":[[2015,10,6]],"date-time":"2015-10-06T15:22:12Z","timestamp":1444144932000},"page":"1463-1472","source":"Crossref","is-referenced-by-count":10,"title":["SuperAD"],"prefix":"10.1145","author":[{"given":"Le T.","family":"Nguyen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Patrick","family":"Tague","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ming","family":"Zeng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Joy","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","reference":[{"key":"key-10.1145\/2800835.2801617-1","doi-asserted-by":"crossref","unstructured":"Hande Alemdar, Tim L. M. van Kasteren, and Cem Ersoy. 2011. Using active learning to allow activity recognition on a large scale. InAmbient Intelligence.Springer, 105--114.","DOI":"10.1007\/978-3-642-25167-2_12"},{"key":"key-10.1145\/2800835.2801617-2","unstructured":"Kerem Altun, Billur Barshan, and Orkun Tunçel. 2010. Comparative study on classifying human activities with miniature inertial and magnetic sensors.Pattern Recognition43, 10 (2010), 3605--3620."},{"key":"key-10.1145\/2800835.2801617-3","unstructured":"Diane J. Cook, Narayanan C. Krishnan, and Parisa Rashidi. 2013. Activity discovery and activity recognition: A new partnership.Cybernetics, IEEE Transactions on43, 3 (2013), 820--828."},{"key":"key-10.1145\/2800835.2801617-4","doi-asserted-by":"crossref","unstructured":"Katherine Ellis, Suneeta Godbole, Jacqueline Kerr, and Gert Lanckriet. 2014. Multi-Sensor physical activity recognition in free-living. InProceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication.ACM, 431--440.","DOI":"10.1145\/2638728.2641673"},{"key":"key-10.1145\/2800835.2801617-5","doi-asserted-by":"crossref","unstructured":"Tâm Huynh, Mario Fritz, and Bernt Schiele. 2008. Discovery of activity patterns using topic models. InProceedings of the 10th international conference on Ubiquitous computing.ACM, 10--19.","DOI":"10.1145\/1409635.1409638"},{"key":"key-10.1145\/2800835.2801617-6","unstructured":"Oscar D. Lara and Miguel A Labrador. 2013. A survey on human activity recognition using wearable sensors.Communications Surveys & Tutorials, IEEE15, 3 (2013), 1192--1209."},{"key":"key-10.1145\/2800835.2801617-7","doi-asserted-by":"crossref","unstructured":"Rong Liu, Ting Chen, and Lu Huang. 2010. Research on human activity recognition based on active learning. InMachine Learning and Cybernetics (ICMLC), 2010 International Conference on, Vol. 1. IEEE, 285--290.","DOI":"10.1109\/ICMLC.2010.5581050"},{"key":"key-10.1145\/2800835.2801617-8","doi-asserted-by":"crossref","unstructured":"Le T. Nguyen, Ming Zeng, Patrick Tague, and Joy Zhang. 2015. Recognizing New Activities with Limited Training Data. InInternational Symposium on Wearable Computers (ISWC).IEEE.","DOI":"10.1145\/2802083.2808388"},{"key":"key-10.1145\/2800835.2801617-9","doi-asserted-by":"crossref","unstructured":"Le T. Nguyen and Joy Zhang. 2014. Unsupervised work knowledge mining through mobility and physical activity sensing. InInternational Conference on Mobile Computing, Applications and Services (MobiCASE).IEEE, 30--39.","DOI":"10.4108\/icst.mobicase.2014.257724"},{"key":"key-10.1145\/2800835.2801617-10","unstructured":"Dan Pelleg and Andrew W Moore. 2004. Active learning for anomaly and rare-category detection. InAdvances in Neural Information Processing Systems.1073--1080."},{"key":"key-10.1145\/2800835.2801617-11","unstructured":"Burr Settles. 2010. Active learning literature survey.University of Wisconsin, Madison52, 55--66 (2010), 11."},{"key":"key-10.1145\/2800835.2801617-12","doi-asserted-by":"crossref","unstructured":"Maja Stikic, Kristof Van Laerhoven, and Bernt Schiele. 2008. Exploring semi-supervised and active learning for activity recognition. InWearable Computers, 2008. ISWC 2008. 12th IEEE International Symposium on.IEEE, 81--88.","DOI":"10.1109\/ISWC.2008.4911590"},{"key":"key-10.1145\/2800835.2801617-13","doi-asserted-by":"crossref","unstructured":"Feng-Tso Sun, Yi-Ting Yeh, Heng-Tze Cheng, Cynthia Kuo, and Martin Griss. 2014. Nonparametric discovery of human routines from sensor data. InPervasive Computing and Communications (PerCom), 2014 IEEE International Conference on.IEEE, 11--19.","DOI":"10.1109\/PerCom.2014.6813938"},{"key":"key-10.1145\/2800835.2801617-14","unstructured":"Alireza Vahdatpour, Navid Amini, and Majid Sarrafzadeh. 2009. Toward Unsupervised Activity Discovery Using Multi-Dimensional Motif Detection in Time Series. InIJCAI, Vol. 9. 1261--1266."}],"event":{"name":"the 2015 ACM International Joint Conference","location":"Osaka, Japan","acronym":"UbiComp '15","number":"2015","sponsor":["Google Inc.","Telef\u00f3nica","SIGCHI, ACM Special Interest Group on Computer-Human Interaction","SIGMOBILE, ACM Special Interest Group on Mobility of Systems, Users, Data and Computing","FX Palo Alto Laboratory, Inc.","ISTC-PC, Intel Science and Technology Center for Pervasive Computing","Panasonic, Panasonic Corporation","Microsoft","Rakuten Institute of Technology"],"start":{"date-parts":[[2015,9,7]]},"end":{"date-parts":[[2015,9,11]]}},"container-title":["Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2015 ACM International Symposium on Wearable Computers - UbiComp '15"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2800835.2801617","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/dl.acm.org\/ft_gateway.cfm?id=2801617&ftid=1628855&dwn=1","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T05:43:12Z","timestamp":1750225392000},"score":1,"resource":{"primary":{"URL":"http:\/\/dl.acm.org\/citation.cfm?doid=2800835.2801617"}},"subtitle":["supervised activity discovery"],"proceedings-subject":"Pervasive and Ubiquitous Computing and Proceedings of the 2015 ACM International Symposium on Wearable Computers","short-title":[],"issued":{"date-parts":[[2015]]},"references-count":14,"URL":"https:\/\/doi.org\/10.1145\/2800835.2801617","relation":{},"subject":[],"published":{"date-parts":[[2015]]}}}