A Distributed System for Answering Range Queries on Sensor Network Data
PERCOMW '05 Proceedings of the Third IEEE International Conference on Pervasive Computing and Communications Workshops
Graphs over time: densification laws, shrinking diameters and possible explanations
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Proceedings of the 8th ACM international workshop on Data warehousing and OLAP
Structure and evolution of online social networks
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
MONIC: modeling and monitoring cluster transitions
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Evolutionary spectral clustering by incorporating temporal smoothness
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
GraphScope: parameter-free mining of large time-evolving graphs
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
A framework for community identification in dynamic social networks
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Facetnet: a framework for analyzing communities and their evolutions in dynamic networks
Proceedings of the 17th international conference on World Wide Web
Community evolution in dynamic multi-mode networks
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Efficient Fragmentation of Large XML Documents
DEXA '07 Proceedings of the 18th international conference on Database and Expert Systems Applications
Dirichlet Process Based Evolutionary Clustering
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
Evolutionary Clustering by Hierarchical Dirichlet Process with Hidden Markov State
ICDM '08 Proceedings of the 2008 Eighth IEEE International Conference on Data Mining
RankClus: integrating clustering with ranking for heterogeneous information network analysis
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
An event-based framework for characterizing the evolutionary behavior of interaction graphs
ACM Transactions on Knowledge Discovery from Data (TKDD)
A particle-and-density based evolutionary clustering method for dynamic networks
Proceedings of the VLDB Endowment
Event-based lossy compression for effective and efficient OLAP over data streams
Data & Knowledge Engineering
Finding spread blockers in dynamic networks
SNAKDD'08 Proceedings of the Second international conference on Advances in social network mining and analysis
Tracking the Evolution of Communities in Dynamic Social Networks
ASONAM '10 Proceedings of the 2010 International Conference on Advances in Social Networks Analysis and Mining
SSDBM'11 Proceedings of the 23rd international conference on Scientific and statistical database management
Co-author Relationship Prediction in Heterogeneous Bibliographic Networks
ASONAM '11 Proceedings of the 2011 International Conference on Advances in Social Networks Analysis and Mining
Analytics over large-scale multidimensional data: the big data revolution!
Proceedings of the ACM 14th international workshop on Data Warehousing and OLAP
DaWaK'06 Proceedings of the 8th international conference on Data Warehousing and Knowledge Discovery
Community evolution detection in time-evolving information networks
Proceedings of the Joint EDBT/ICDT 2013 Workshops
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DynamicNet, an effective and efficient algorithm for supporting community evolution detection in time-evolving information networks is presented and experimentally evaluated in this paper. DynamicNet introduces a graph-based model-theoretic approach to represent time-evolving information networks, and to capture how they change over time. A central feature of DynamicNet is represented by the ability of supporting matching-based community evolution detection, by identifying several classes of community transitions. Experimental results clearly demonstrate the reliability and the efficiency of our proposal.