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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Xiyang Liu Qiong Pan Yingying An Guimin Qin |
| Copyright Year | 2015 |
| Description | Author affiliation: Sch. of Telecommun. of Eng., Xidian Univ., Xi'an, China (Qiong Pan) || Sch. of Comput. Sci. & Technol., Xidian Univ., Xi'an, China (Xiyang Liu; Yingying An; Guimin Qin) |
| Abstract | Many complex networks in the real world demonstrate similar patterns, including the scale-free property and strong community structure. In this paper, we present a novel parameter-free community detection algorithm based on the scale-free property of networks, named ScaleFreeCDA. The basic idea behind it is two mechanisms, i.e., node growth and preferential attachment. Community centers are firstly determined by node degree and similarity, and then community structures are obtained accordingly. The experiments indicate that our algorithm can find high-quality communities, and can determine appropriate number of communities on most artificial and real networks. |
| Starting Page | 2270 |
| Ending Page | 2275 |
| File Size | 584948 |
| Page Count | 6 |
| File Format | |
| e-ISBN | 9781509001545 |
| DOI | 10.1109/CIT/IUCC/DASC/PICOM.2015.335 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2015-10-26 |
| Publisher Place | UK |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Blogs Clustering algorithms Complex networks Community detection Linear programming Partitioning algorithms complex networks Detection algorithms scale-free property Dolphins algorithm |
| Content Type | Text |
| Resource Type | Article |
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