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ACM Interact. Mob. Wearable Ubiquitous Technol."],"published-print":{"date-parts":[[2017,9,11]]},"abstract":"<jats:p>Personalized semantic place label recognition is a promising research issue in ubiquitous computing. However, there are some problems existed in the current methods: 1) They use trajectory data to learn recognition model and ignore other context data that could reflect human behaviors over places. 2) They tend to maximize accuracy and ignore the imbalanced costs caused by the similarity between semantic place labels. 3) They use supervised learning, which cannot achieve a good performance when the number of labeled places is limited. In this paper, we exploit multi-context data to construct effective features and propose a method called CEMENT (Cost-sensitive sEmi-supervised personalized seMantic place labEl recogNiTion). On one hand, CEMENT is cost-sensitive, and it calculates misclassification costs according to the semantic similarity between place labels. On the other hand, CEMENT utilizes ensemble semi-supervised learning to leverage the unlabeled data to improve the performance. Experimental results show that the proposed method has superiority over state-of-the-art methods.<\/jats:p>","DOI":"10.1145\/3131903","type":"journal-article","created":{"date-parts":[[2017,9,11]],"date-time":"2017-09-11T12:12:26Z","timestamp":1505131946000},"page":"1-14","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["Cost-Sensitive Semi-Supervised Personalized Semantic Place Label Recognition Using Multi-Context Data"],"prefix":"10.1145","volume":"1","author":[{"given":"Xiaojie","family":"Wu","sequence":"first","affiliation":[{"name":"Zhejiang University"}]},{"given":"Ling","family":"Chen","sequence":"additional","affiliation":[{"name":"Zhejiang University 8 Alibaba-Zhejiang University Joint Institute of Frontier Technologies"}]},{"given":"Mingqi","family":"Lv","sequence":"additional","affiliation":[{"name":"Zhejiang University of Technology"}]},{"given":"Mingrui","family":"Han","sequence":"additional","affiliation":[{"name":"Zhejiang University"}]},{"given":"Gencai","family":"Chen","sequence":"additional","affiliation":[{"name":"Zhejiang University"}]}],"member":"320","published-online":{"date-parts":[[2017,9,11]]},"reference":[{"doi-asserted-by":"publisher","key":"e_1_2_1_1_1","DOI":"10.1080\/02693799608902110"},{"doi-asserted-by":"publisher","key":"e_1_2_1_2_1","DOI":"10.1145\/1054972.1054985"},{"doi-asserted-by":"publisher","key":"e_1_2_1_3_1","DOI":"10.1145\/1124772.1124903"},{"doi-asserted-by":"publisher","key":"e_1_2_1_4_1","DOI":"10.1145\/2020408.2020491"},{"doi-asserted-by":"publisher","key":"e_1_2_1_5_1","DOI":"10.1145\/2093973.2093989"},{"doi-asserted-by":"publisher","key":"e_1_2_1_6_1","DOI":"10.1137\/1.9781611972832.19"},{"doi-asserted-by":"publisher","key":"e_1_2_1_7_1","DOI":"10.1145\/1864349.1864362"},{"doi-asserted-by":"publisher","key":"e_1_2_1_8_1","DOI":"10.1145\/2396761.2398471"},{"doi-asserted-by":"publisher","key":"e_1_2_1_9_1","DOI":"10.1016\/j.pmcj.2013.07.004"},{"volume-title":"Proceedings of Nokia Mobile Data Challenge 2012 Workshop","year":"2012","author":"Huang C. 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