DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Byoungjip | ko |
dc.contributor.author | Kang, Seungwoo | ko |
dc.contributor.author | Ha, Jin-Young | ko |
dc.contributor.author | Song, Junehwa | ko |
dc.date.accessioned | 2016-04-20T07:03:15Z | - |
dc.date.available | 2016-04-20T07:03:15Z | - |
dc.date.created | 2016-01-04 | - |
dc.date.created | 2016-01-04 | - |
dc.date.created | 2016-01-04 | - |
dc.date.issued | 2015 | - |
dc.identifier.citation | INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS | - |
dc.identifier.issn | 1550-1329 | - |
dc.identifier.uri | http://hdl.handle.net/10203/205660 | - |
dc.description.abstract | 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' 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. | - |
dc.language | English | - |
dc.publisher | HINDAWI PUBLISHING CORP | - |
dc.title | Agatha: Predicting Daily Activities from Place Visit History for Activity-Aware Mobile Services in Smart Cities | - |
dc.type | Article | - |
dc.identifier.wosid | 000366424900001 | - |
dc.identifier.scopusid | 2-s2.0-84950132659 | - |
dc.type.rims | ART | - |
dc.citation.publicationname | INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS | - |
dc.identifier.doi | 10.1155/2015/867602 | - |
dc.contributor.localauthor | Song, Junehwa | - |
dc.contributor.nonIdAuthor | Kim, Byoungjip | - |
dc.contributor.nonIdAuthor | Kang, Seungwoo | - |
dc.contributor.nonIdAuthor | Ha, Jin-Young | - |
dc.description.isOpenAccess | Y | - |
dc.type.journalArticle | Article | - |
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