{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,1]],"date-time":"2025-06-01T04:12:11Z","timestamp":1748751131726,"version":"3.41.0"},"reference-count":32,"publisher":"SAGE Publications","issue":"12","license":[{"start":{"date-parts":[[2015,12,1]],"date-time":"2015-12-01T00:00:00Z","timestamp":1448928000000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["International Journal of Distributed Sensor Networks"],"published-print":{"date-parts":[[2015,12,1]]},"abstract":"<jats:p>We present a place-history-based activity prediction system called Agatha, in order to enable activity-aware mobile services in smart cities. The system predicts a user's potential subsequent activities that are highly likely to occur given a series of information about activities done before or activity-related contextual information such as visit place and time. To predict the activities, we develop a causality-based activity prediction model using Bayesian networks. The basic idea of the prediction is that where a person has been and what he\/she has done so far influence what he\/she will do next. To show the feasibility, we evaluate the prediction model using the American Time-Use Survey (ATUS) dataset, which includes more than 10,000 people's location and activity history. Our evaluation shows that Agatha can predict users\u2019 potential activities with up to 90% accuracy for the top 3 activities, more than 80% for the top 2 activities, and about 65% for the top 1 activity while considering a relatively large number of daily activities defined in the ATUS dataset, that is, 17 activities.<\/jats:p>","DOI":"10.1155\/2015\/867602","type":"journal-article","created":{"date-parts":[[2015,12,3]],"date-time":"2015-12-03T21:01:09Z","timestamp":1449176469000},"page":"867602","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":6,"title":["Agatha: Predicting Daily Activities from Place Visit History for Activity-Aware Mobile Services in Smart Cities"],"prefix":"10.1177","volume":"11","author":[{"given":"Byoungjip","family":"Kim","sequence":"first","affiliation":[{"name":"Department of Information and Communication Engineering, Sangmyung University, Cheonan 31066, Republic of Korea"}]},{"given":"Seungwoo","family":"Kang","sequence":"additional","affiliation":[{"name":"School of Computer Science and Engineering, KOREATECH, Cheonan 31253, Republic of Korea"}]},{"given":"Jin-Young","family":"Ha","sequence":"additional","affiliation":[{"name":"Department of Computer and Communication Engineering, Kangwon National University (KNU), Chuncheon 24341, Republic of Korea"}]},{"given":"Junehwa","family":"Song","sequence":"additional","affiliation":[{"name":"School of Computing, KAIST, Daejeon 34141, Republic of Korea"}]}],"member":"179","published-online":{"date-parts":[[2015,12,3]]},"reference":[{"key":"B1-2015-867602","doi-asserted-by":"publisher","DOI":"10.1145\/2030112.2030126"},{"key":"B2-2015-867602","doi-asserted-by":"publisher","DOI":"10.1109\/tkde.2012.153"},{"key":"B3-2015-867602","doi-asserted-by":"publisher","DOI":"10.1109\/mprv.2010.21"},{"key":"B4-2015-867602","doi-asserted-by":"publisher","DOI":"10.1145\/2184489.2184492"},{"key":"B5-2015-867602","doi-asserted-by":"publisher","DOI":"10.1145\/1989734.1989742"},{"key":"B7-2015-867602","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-72037-9_5"},{"key":"B8-2015-867602","doi-asserted-by":"publisher","DOI":"10.1126\/science.1177170"},{"key":"B10-2015-867602","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-540-24646-6_1"},{"first-page":"18","volume-title":"Proceedings of the 2nd International Conference on Pervasive Computing (Pervasive \u203204)","author":"Lukowicz P.","key":"B11-2015-867602"},{"key":"B12-2015-867602","doi-asserted-by":"publisher","DOI":"10.1145\/1620545.1620553"},{"key":"B13-2015-867602","doi-asserted-by":"publisher","DOI":"10.1109\/MPRV.2004.7"},{"key":"B14-2015-867602","doi-asserted-by":"publisher","DOI":"10.1007\/s00779-003-0240-0"},{"first-page":"773","volume-title":"Proceedings of the 19th International Joint Conference on Artificial Intelligence (IJCAI \u203205)","author":"Liao L.","key":"B15-2015-867602"},{"key":"B16-2015-867602","doi-asserted-by":"publisher","DOI":"10.1145\/1409635.1409655"},{"first-page":"73","volume-title":"Proceedings of the 5th International Conference on Ubiquitous Computing (UbiComp \u203203)","author":"Patterson D. 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