DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Oh, Alice | - |
dc.contributor.advisor | 오혜연 | - |
dc.contributor.author | Seonwoo, Yeon | - |
dc.date.accessioned | 2019-09-04T02:47:08Z | - |
dc.date.available | 2019-09-04T02:47:08Z | - |
dc.date.issued | 2017 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=867039&flag=dissertation | en_US |
dc.identifier.uri | http://hdl.handle.net/10203/267065 | - |
dc.description | 학위논문(석사) - 한국과학기술원 : 전산학부, 2017.8,[iv, 23 p. :] | - |
dc.description.abstract | To predict future events, previous research models diffusion patterns of events. Limitation of these research is that they could only model fixed number of event types. For this reason, existing models could not predict new types of events. To solve this problem, we introduce Vectorized Hawkes Process, which extends Hawkes process in continuous vector space. We conduct experiment on synthetic data and two real world datasets. Our model’s predictive power and estimate power of relations between events are demonstrated by the experimental results. | - |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.subject | Hawkes process▼aNode2Vec▼ainformation diffusion▼asocial network | - |
dc.subject | 호크스 프로세스▼a노드벡터▼a정보확산▼a소셜네트워크▼a문서 스트림 | - |
dc.title | Event prediction using vector representation in hawkes processes | - |
dc.title.alternative | 연속된 벡터공간상의 호크스 프로세스를 통한 이벤트 예측 | - |
dc.type | Thesis(Master) | - |
dc.identifier.CNRN | 325007 | - |
dc.description.department | 한국과학기술원 :전산학부, | - |
dc.contributor.alternativeauthor | 선우연 | - |
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