DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Chung, Sae-Young | - |
dc.contributor.advisor | 정세영 | - |
dc.contributor.author | Ryu, Narae | - |
dc.date.accessioned | 2018-06-20T06:21:38Z | - |
dc.date.available | 2018-06-20T06:21:38Z | - |
dc.date.issued | 2017 | - |
dc.identifier.uri | http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=675397&flag=dissertation | en_US |
dc.identifier.uri | http://hdl.handle.net/10203/243272 | - |
dc.description | 학위논문(석사) - 한국과학기술원 : 전기및전자공학부, 2017.2,[i, 19 :] | - |
dc.description.abstract | In this paper, we prove a sharp limit on the community detection problem with colored edges. We assume two equal-sized communities and there are $m$ different types of edges. If two vertices are in the same community, the distribution of edges follows $p_i=\alpha_i\log{n}/n$ for $1\leq i \leq m$, otherwise the distribution of edges is $q_i=\beta_i\log{n}/n$ for $1\leq i \leq m$, where $\alpha_i$ and $\beta_i$ are positive constants and $n$ is the total number of vertices. Under these assumptions, a fundamental limit on community detection is characterized using the Hellinger distance between the two distributions. If $\sum_{i=1}^{m} {(\sqrt{\alpha_{i}}-\sqrt{\beta_{i}})}^{2}>2$, then the community detection via maximum likelihood (ML) estimator is possible with high probability. If $\sum_{i=1}^{m} {(\sqrt{\alpha_{i}}-\sqrt{\beta_{i}})}^{2}<2$, the probability that the ML estimator fails to detect the communities does not go to zero. | - |
dc.language | eng | - |
dc.publisher | 한국과학기술원 | - |
dc.subject | Community detection problem | - |
dc.subject | Hellinger distance | - |
dc.subject | 커뮤니티 검출 문제 | - |
dc.subject | 헬링거 거리 | - |
dc.title | Community Detection with Colored Edges | - |
dc.title.alternative | 여러 종류의 연결을 포함한 그래프에서의 커뮤니티 검출 | - |
dc.type | Thesis(Master) | - |
dc.identifier.CNRN | 325007 | - |
dc.description.department | 한국과학기술원 :전기및전자공학부, | - |
dc.contributor.alternativeauthor | 유나래 | - |
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