DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Lee, Dongman | - |
dc.contributor.advisor | 이동만 | - |
dc.contributor.author | Park, Kinam | - |
dc.date.accessioned | 2021-05-13T19:32:17Z | - |
dc.date.available | 2021-05-13T19:32:17Z | - |
dc.date.issued | 2020 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=910989&flag=dissertation | en_US |
dc.identifier.uri | http://hdl.handle.net/10203/284663 | - |
dc.description | 학위논문(석사) - 한국과학기술원 : 전산학부, 2020.2,[iv, 27 p. :] | - |
dc.description.abstract | Point of interest (POI) in a urban space represents the perception of city dwellers and visitors with respect to a certain place. Among many physical data sources, LTE mobile traffic patterns are used to derive POIs. In this paper, we propose a POI discovery scheme that can extract not only diachronic POIs in a given place but also how they are exploited everyday from LTE cell tower access data. We extract meaningful features from LTE cell tower access data and build a machine learning based model which is fitted to our domain. Our model shows better performance compared to existing works. We show that LTE data is a very powerful data source for interpreting places, and this model will be very helpful for building urban space-based services in the future. | - |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.subject | LTE cell tower access traces▼aPOI▼aMachine learning▼aClassification▼aRegression | - |
dc.subject | LTE 셀 타워 접속 추적 데이터▼a관심지점▼a기계학습▼a분류▼a회귀 | - |
dc.title | Discovering daily POI exploitation using LTE cell tower access traces | - |
dc.title.alternative | LTE 셀 타워 접속 추적 데이터를 이용한 일상 POI이용 발견 | - |
dc.type | Thesis(Master) | - |
dc.identifier.CNRN | 325007 | - |
dc.description.department | 한국과학기술원 :전산학부, | - |
dc.contributor.alternativeauthor | 박기남 | - |
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