Algorithms for clustering data
Algorithms for clustering data
Discovering shared interests using graph analysis
Communications of the ACM - Special issue on internetworking
Inferring Web communities from link topology
Proceedings of the ninth ACM conference on Hypertext and hypermedia : links, objects, time and space---structure in hypermedia systems: links, objects, time and space---structure in hypermedia systems
Trawling the Web for emerging cyber-communities
WWW '99 Proceedings of the eighth international conference on World Wide Web
Theoretical Improvements in Algorithmic Efficiency for Network Flow Problems
Journal of the ACM (JACM)
Efficient identification of Web communities
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining newsgroups using networks arising from social behavior
WWW '03 Proceedings of the 12th international conference on World Wide Web
The link prediction problem for social networks
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
Relescope: an experiment in accelerating relationships
CHI '05 Extended Abstracts on Human Factors in Computing Systems
Link prediction approach to collaborative filtering
Proceedings of the 5th ACM/IEEE-CS joint conference on Digital libraries
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Graphs over time: densification laws, shrinking diameters and possible explanations
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Community Mining Tool Using Bibliography Data
IV '05 Proceedings of the Ninth International Conference on Information Visualisation
Proceedings of the 2006 international workshop on Mining software repositories
An event-based framework for characterizing the evolutionary behavior of interaction graphs
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Virtual knowledge service market-For effective knowledge flow within knowledge grid
Journal of Systems and Software
Journal of Systems and Software
Development of a team measure for tacit knowledge in software development teams
Journal of Systems and Software
Social and Economic Networks
Mining and analyzing organizational social networks for collaborative design
CSCWD '09 Proceedings of the 2009 13th International Conference on Computer Supported Cooperative Work in Design
Mining and Analyzing Multirelational Social Networks
CSE '09 Proceedings of the 2009 International Conference on Computational Science and Engineering - Volume 04
Role of weak ties in link prediction of complex networks
Proceedings of the 1st ACM international workshop on Complex networks meet information & knowledge management
Link Prediction on Evolving Data Using Matrix and Tensor Factorizations
ICDMW '09 Proceedings of the 2009 IEEE International Conference on Data Mining Workshops
BSN: An automatic generation algorithm of social network data
Journal of Systems and Software
Community mining from multi-relational networks
PKDD'05 Proceedings of the 9th European conference on Principles and Practice of Knowledge Discovery in Databases
GCC: a knowledge management environment for research centers and universities
APWeb'06 Proceedings of the 8th Asia-Pacific Web conference on Frontiers of WWW Research and Development
Defining and Evaluating Network Communities Based on Ground-Truth
ICDM '12 Proceedings of the 2012 IEEE 12th International Conference on Data Mining
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Analyzing social networks enables us to detect several inter and intra connections between people in and outside their organizations. We model a multi-relational scientific social network where researchers may have four different types of relationships with each other. We adopt some criteria to enable the modeling of a scientific social network as close as possible to reality. Using clustering techniques with maximum flow measure, we identify the social structure and research communities in a way that allows us to evaluate the knowledge flow in the Brazilian scientific community. Finally, we evaluate the temporal evolution of scientific social networks to suggest/predict new relationships.