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Inf. Syst."],"published-print":{"date-parts":[[2018,7,31]]},"abstract":"<jats:p>\n            User-generated trajectories (UGTs), such as travel records from bus companies, capture rich information of human mobility in the offline world. However, some interesting applications of these raw footprints have not been exploited well due to the lack of textual information to infer the subject\u2019s personal interests. Although there is rich semantic information contained in the spatial- and temporal-aware user-generated contents (STUGC) published in the online world, such as Twitter, less effort has been made to utilize this information to facilitate the interest discovery process. In this article, we design an effective probabilistic framework named CO\n            <jats:sup>2<\/jats:sup>\n            to &lt;underline&gt;c&lt;\/underline&gt;onnect the &lt;underline&gt;o&lt;\/underline&gt;ffline world with the &lt;underline&gt;o&lt;\/underline&gt;nline world in order to discover users\u2019 interests directly from their raw footprints in UGT. CO\n            <jats:sup>2<\/jats:sup>\n            first infers trip intentions by utilizing the semantic information in STUGC and then discovers user interests by aggregating the intentions. To evaluate the effectiveness of CO\n            <jats:sup>2<\/jats:sup>\n            , we use two large-scale real-world datasets as a case study and further conduct a questionnaire survey to show the superior performance of CO\n            <jats:sup>2<\/jats:sup>\n            .\n          <\/jats:p>","DOI":"10.1145\/3182164","type":"journal-article","created":{"date-parts":[[2018,3,14]],"date-time":"2018-03-14T12:34:20Z","timestamp":1521030860000},"page":"1-29","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":6,"title":["CO\n            <sup>2<\/sup>"],"prefix":"10.1145","volume":"36","author":[{"given":"Long","family":"Guo","sequence":"first","affiliation":[{"name":"Peking University, Beijing, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dongxiang","family":"Zhang","sequence":"additional","affiliation":[{"name":"University of Electronic Science and Technology of China, Chengdu, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuan","family":"Wang","sequence":"additional","affiliation":[{"name":"National University of Singapore, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huayu","family":"Wu","sequence":"additional","affiliation":[{"name":"Nanyang Technological University, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Bin","family":"Cui","sequence":"additional","affiliation":[{"name":"Peking University, Shenzhen, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kian-Lee","family":"Tan","sequence":"additional","affiliation":[{"name":"National University of Singapore, Singapore"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2018,3,13]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Exchangeability and related topics. \u00c9cole d\u2019\u00c9t\u00e9 de Probabilit\u00e9s de Saint-Flour XIII","author":"Aldous David J.","year":"1983","unstructured":"David J. Aldous . 1985. Exchangeability and related topics. \u00c9cole d\u2019\u00c9t\u00e9 de Probabilit\u00e9s de Saint-Flour XIII 1983 . Springer Berlin Heidelberg , 1--198. David J. Aldous. 1985. Exchangeability and related topics. \u00c9cole d\u2019\u00c9t\u00e9 de Probabilit\u00e9s de Saint-Flour XIII 1983. Springer Berlin Heidelberg, 1--198."},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/1341012.1341041"},{"key":"e_1_2_1_3_1","volume-title":"Jordan","author":"Blei David M.","year":"2003","unstructured":"David M. Blei , Andrew Y. Ng , and Michael I . Jordan . 2003 . Latent Dirichlet allocation. J.ournal of Machine Learning Research 3, 993--1022. http:\/\/dl.acm.org\/citation.cfm?id&equals;944919.944937 David M. Blei, Andrew Y. Ng, and Michael I. Jordan. 2003. Latent Dirichlet allocation. 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