Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
The link prediction problem for social networks
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
A survey of kernel and spectral methods for clustering
Pattern Recognition
A tutorial on spectral clustering
Statistics and Computing
Survey of Text Mining II: Clustering, Classification, and Retrieval
Survey of Text Mining II: Clustering, Classification, and Retrieval
Connections between the lines: augmenting social networks with text
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Learning systems of concepts with an infinite relational model
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Bipartite graphs as models of complex networks
CAAN'04 Proceedings of the First international conference on Combinatorial and Algorithmic Aspects of Networking
Computer Science Review
Bridging the gap: complex networks meet information and knowledge management
Proceedings of the 18th ACM conference on Information and knowledge management
Discovery of Interesting Users in Twitter by Overlapping Propagation Paths of Retweets
WI-IAT '12 Proceedings of the The 2012 IEEE/WIC/ACM International Joint Conferences on Web Intelligence and Intelligent Agent Technology - Volume 03
Text clustering using one-mode projection of document-word bipartite graphs
Proceedings of the 28th Annual ACM Symposium on Applied Computing
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Complex network analysis is a growing research area in a wide variety of domains and has recently become closely associated with data, text and web mining. One of the most active areas in the study of complex networks is the detection of community structure, which can be related to the clustering problem in data mining. This paper employs a community structure detection algorithm for document clustering in order to discover potential relationships in a social network. The proposed approach is explored in a case study of potential collaboration discovery among the research staff in the Graduate Civil Engineering Department of the Federal University of Rio de Janeiro, Brazil. The results show that the combined use of both techniques provides useful insights on the relationships, both existent and potential, among individuals in the social network.