dc.creator | Fan, Xiaoping | |
dc.creator | Chen, Zhijie | |
dc.creator | Cai, Fei | |
dc.creator | Wu, Jinsong | |
dc.creator | Liu, Shengzong | |
dc.creator | Liao, Zhining | |
dc.creator | Liao, Zhifang | |
dc.date.accessioned | 2019-10-11T17:30:13Z | |
dc.date.available | 2019-10-11T17:30:13Z | |
dc.date.created | 2019-10-11T17:30:13Z | |
dc.date.issued | 2019 | |
dc.identifier | Mobile Networks and Applications, Volumen 24, Issue 4, 2019, Pages 1373-1381 | |
dc.identifier | 15728153 | |
dc.identifier | 1383469X | |
dc.identifier | 10.1007/s11036-018-0994-2 | |
dc.identifier | https://repositorio.uchile.cl/handle/2250/171295 | |
dc.description.abstract | © 2018, Springer Science+Business Media, LLC, part of Springer Nature.The relationship of friends in social networks can be strong or weak. Some research works have shown that a close relationship between friends conducts good community structure. Based on this result, we propose an effective method in detecting community structure in social networks based on the closeness of relations among neighbors. This method calculates the gravity between each neighbor node to core nodes, then makes judgement if the node should be classified in the community or not, and finally form the process of community detection. The experimental results show that the proposed method can mine the social structure efficiently with a low computational complexity. | |
dc.language | en | |
dc.publisher | Springer New York LLC | |
dc.rights | http://creativecommons.org/licenses/by-nc-nd/3.0/cl/ | |
dc.rights | Attribution-NonCommercial-NoDerivs 3.0 Chile | |
dc.source | Mobile Networks and Applications | |
dc.subject | Community detection | |
dc.subject | Core members | |
dc.subject | Social network | |
dc.title | Local Core Members Aided Community Structure Detection | |
dc.type | Artículo de revista | |