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Intell. Syst. Technol."],"published-print":{"date-parts":[[2020,8,31]]},"abstract":"<jats:p>\n            In this article, we propose a novel temporal pattern mining problem, named\n            <jats:italic>high-utility temporal pattern mining<\/jats:italic>\n            , to fulfill the needs of various applications. Different from classical temporal pattern mining aimed at discovering frequent temporal patterns, high-utility temporal pattern mining is to find each temporal pattern whose utility is greater than or equal to the minimum-utility threshold. To facilitate efficient high-utility temporal pattern mining, several extension and pruning strategies are proposed to reduce the search space. Algorithm\u00a0HUTPMiner is then proposed to efficiently mine high-utility temporal patterns with the aid of the proposed extension and pruning strategies. Experimental results show that HUTPMiner is able to prune a large number of candidates, thereby achieving high mining efficiency.\n          <\/jats:p>","DOI":"10.1145\/3391230","type":"journal-article","created":{"date-parts":[[2020,5,26]],"date-time":"2020-05-26T00:05:14Z","timestamp":1590451514000},"page":"1-31","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Mining High-utility Temporal Patterns on Time Interval\u2013based Data"],"prefix":"10.1145","volume":"11","author":[{"given":"Jun-Zhe","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Computer Science, National Chiao Tung University, Hsinchu, Taiwan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7153-0410","authenticated-orcid":false,"given":"Yi-Cheng","family":"Chen","sequence":"additional","affiliation":[{"name":"Department of Information Management, National Central University, Taoyuan City, Taiwan"}]},{"given":"Wen-Yueh","family":"Shih","sequence":"additional","affiliation":[{"name":"Department of Computer Science, National Chiao Tung University, Hsinchu, Taiwan"}]},{"given":"Lin","family":"Yang","sequence":"additional","affiliation":[{"name":"Department of Computer Science, National Chiao Tung University, Hsinchu, Taiwan"}]},{"given":"Yu-Shao","family":"Liu","sequence":"additional","affiliation":[{"name":"Department of Computer Science, National Chiao Tung University, Hsinchu, Taiwan"}]},{"given":"Jiun-Long","family":"Huang","sequence":"additional","affiliation":[{"name":"Department of Computer Science, National Chiao Tung University, Hsinchu, Taiwan"}]}],"member":"320","published-online":{"date-parts":[[2020,5,25]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"American Sign Language Linguistic Research Project. http:\/\/www.bu.edu\/asl  American Sign Language Linguistic Research Project. http:\/\/www.bu.edu\/asl"},{"key":"e_1_2_1_2_1","unstructured":"Sensor Signal Data Set for Exploring Context Recognition of Mobile Devices. http:\/\/www.cis.hut.fi\/jhimberg\/contextdata\/index.shtml.  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