| Presentation | 2019-06-07 Overlapping Communities in Correlation Matrices Koji Oishi, Naoki Masuda, |
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| PDF Download Page |  PDF download Page Link |
| Abstract(in Japanese) | (See Japanese page) |
| Abstract(in English) | Various algorithms have been designed to detect overlapping community structure in networks. The factor analysis, a classical multivariate data analysis method, operates on correlation (or covariance) matrix data and can be regarded as a method of overlapping community detection, where an estimated factor corresponds to a community and an estimated factor loading corresponds to the strength of affiliation of a node to a community. To date, a common pathway to analyze overlapping community structure in correlation matrices has probably been to first create an unweighted or weighted conventional network from a correlational data and then to apply an overlapping community detection algorithms for conventional networks. Here we compare the factor analysis and three popular methods of overlapping community detection on synthetic correlation matrices and those obtained from the brain of healthy human adults recorded with functional magnetic resonance imaging. We found that overlapping communities detected by the factor analysis and the other algorithms are largely different, whereas the different methods consistently detected communities that are close to two biologically determined communities. |
| Keyword(in Japanese) | (See Japanese page) |
| Keyword(in English) | NetworkCommunity detectionFactor analysis |
| Paper # | NLP2019-24,CCS2019-7 |
| Date of Issue | 2019-05-31 (NLP, CCS) |
| Conference Information | |
| Committee | CCS / NLP |
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| Conference Date | 2019/6/7(3days) |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | machinaka campus nagaoka |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Chair | Makoto Naruse(NICT) / Hiroaki Kurokawa(Tokyo Univ. of Tech.) |
| Vice Chair | Shigeki Shiokawa(Kanagawa Inst. of Tech.) / Tetsuya Asai(Hokkaido Univ.) / Kiyohisa Natsume(Kyushu Inst. of Tech.) |
| Secretary | Shigeki Shiokawa(Hiroshima City Univ.) / Tetsuya Asai(Kanagawa Inst. of Tech.) / Kiyohisa Natsume(Nippon Inst. of Tech.) |
| Assistant | Hidehiro Nakano(Tokyo City Univ.) / Kazuki Nakada(Tsukuba Univ. of Tech.) / Hiroyasu Ando(Tsukuba Univ.) / Takashi Matsubara(Kobe Univ.) / Yutaka Shimada(Saitama Univ.) / Toshikaza Samura(Yamaguchi Univ.) |
| Paper Information | |
| Registration To | Technical Committee on Complex Communication Sciences / Technical Committee on Nonlinear Problems |
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| Language | ENG |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Overlapping Communities in Correlation Matrices |
| Sub Title (in English) | Factor Analysis Compared with Existing Algorithms for Networks |
| Keyword(1) | NetworkCommunity detectionFactor analysis |
| 1st Author's Name | Koji Oishi |
| 1st Author's Affiliation | National Institute of Informatics(NII) |
| 2nd Author's Name | Naoki Masuda |
| 2nd Author's Affiliation | University of Bristol(Univ. of Bristol) |
| Date | 2019-06-07 |
| Paper # | NLP2019-24,CCS2019-7 |
| Volume (vol) | vol.119 |
| Number (no) | NLP-71,CCS-72 |
| Page | pp.pp.31-35(NLP), pp.31-35(CCS), |
| #Pages | 5 |
| Date of Issue | 2019-05-31 (NLP, CCS) |