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Mining Heterogeneous Data for Semantic Understanding of Mobility Data
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| 자료유형 | 학위논문 |
|---|---|
| 서명/저자사항 | Mining Heterogeneous Data for Semantic Understanding of Mobility Data. |
| 개인저자 | Wu, Fei. |
| 단체저자명 | The Pennsylvania State University. Information Sciences and Technology. |
| 발행사항 | [S.l.]: The Pennsylvania State University., 2018. |
| 발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2018. |
| 형태사항 | 121 p. |
| 기본자료 저록 | Dissertation Abstracts International 79-12B(E). Dissertation Abstract International |
| ISBN | 9780438136137 |
| 학위논문주기 | Thesis (Ph.D.)--The Pennsylvania State University, 2018. |
| 일반주기 |
Source: Dissertation Abstracts International, Volume: 79-12(E), Section: B.
|
| 요약 | With the prevalence of positioning technology, an increasing amount of human mobility data becomes available nowadays, including geotagged social media data, location records collected by mobile phone applications, and GPS traces collected by na |
| 요약 | This dissertation describes several recent attempts in fusing external context data for understanding the human mobility data. I will motivate the problem by presenting one key limitation of conventional mobility pattern mining approaches. A fun |
| 일반주제명 | Computer science. |
| 언어 | 영어 |
| 바로가기 | 
: 이 자료의 원문은 한국교육학술정보원에서 제공합니다. |
