Partitioning sparse matrices with eigenvectors of graphs
SIAM Journal on Matrix Analysis and Applications
Small worlds: the dynamics of networks between order and randomness
Small worlds: the dynamics of networks between order and randomness
Algorithm 457: finding all cliques of an undirected graph
Communications of the ACM
Massive Quasi-Clique Detection
LATIN '02 Proceedings of the 5th Latin American Symposium on Theoretical Informatics
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
On mining cross-graph quasi-cliques
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Coherent closed quasi-clique discovery from large dense graph databases
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Force-based incremental algorithm for mining community structure in dynamic network
Journal of Computer Science and Technology - Special section on China AVS standard
A Parallel Algorithm for Enumerating All Maximal Cliques in Complex Network
ICDMW '06 Proceedings of the Sixth IEEE International Conference on Data Mining - Workshops
A parallel algorithm for enumerating all the maximal k-plexes
PAKDD'07 Proceedings of the 2007 international conference on Emerging technologies in knowledge discovery and data mining
Computing communities in large networks using random walks
ISCIS'05 Proceedings of the 20th international conference on Computer and Information Sciences
Social Influence and Role Analysis Based on Community Structure in Social Network
ADMA '09 Proceedings of the 5th International Conference on Advanced Data Mining and Applications
Analyzing the impact of events in an online music community
Proceedings of the 4th Workshop on Social Network Systems
Discovery of Web user communities and their role in personalization
User Modeling and User-Adapted Interaction
A posteriori approach for community detection
Journal of Computer Science and Technology - Special issue on Community Analysis and Information Recommendation
| Hi-index | 0.00 |
The task of clustering is to identify classes of similar objects among a set of objects. The definition of similarity varies from one clustering model to another. However, in most of these models the concept of similarity is often based on such metrics ...