A study of retrospective and on-line event detection
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Concept decompositions for large sparse text data using clustering
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Knowledge Acquisition Via Incremental Conceptual Clustering
Machine Learning
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Tracking the best linear predictor
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Pattern Classification (2nd Edition)
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Identifying similarities, periodicities and bursts for online search queries
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Semantic similarity between search engine queries using temporal correlation
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Evolutionary spectral clustering by incorporating temporal smoothness
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Structural and temporal analysis of the blogosphere through community factorization
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An event-based framework for characterizing the evolutionary behavior of interaction graphs
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Topic taxonomy adaptation for group profiling
ACM Transactions on Knowledge Discovery from Data (TKDD)
Facetnet: a framework for analyzing communities and their evolutions in dynamic networks
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A bayesian mixture model with linear regression mixing proportions
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Community evolution in dynamic multi-mode networks
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A visual-analytic toolkit for dynamic interaction graphs
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Description and simulation of dynamic mobility networks
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A Dynamic Clustering Algorithm for Mobile Objects
PKDD 2007 Proceedings of the 11th European conference on Principles and Practice of Knowledge Discovery in Databases
Analyzing communities and their evolutions in dynamic social networks
ACM Transactions on Knowledge Discovery from Data (TKDD)
MetaFac: community discovery via relational hypergraph factorization
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Incremental spectral clustering by efficiently updating the eigen-system
Pattern Recognition
COWES: Web user clustering based on evolutionary web sessions
Data & Knowledge Engineering
An event-based framework for characterizing the evolutionary behavior of interaction graphs
ACM Transactions on Knowledge Discovery from Data (TKDD)
On evolutionary spectral clustering
ACM Transactions on Knowledge Discovery from Data (TKDD)
Semi-supervised classification on evolutionary data
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
On-line evolutionary exponential family mixture
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Detecting dynamic communities in opportunistic networks
ICUFN'09 Proceedings of the first international conference on Ubiquitous and future networks
A particle-and-density based evolutionary clustering method for dynamic networks
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CHRONICLE: A Two-Stage Density-Based Clustering Algorithm for Dynamic Networks
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Mining Query Logs: Turning Search Usage Data into Knowledge
Foundations and Trends in Information Retrieval
Multiobjective evolutionary community detection for dynamic networks
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Evolutionary clustering using frequent itemsets
Proceedings of the First International Workshop on Novel Data Stream Pattern Mining Techniques
Towards mobility-based clustering
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Evolutionary hierarchical dirichlet processes for multiple correlated time-varying corpora
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
A framework for clustering categorical time-evolving data
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Using cohesive subgroups for analyzing the evolution of the friend view mobile social network
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Topic-constrained hierarchical clustering for document datasets
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Tracking group evolution in social networks
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On clustering heterogeneous social media objects with outlier links
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Modularity-driven clustering of dynamic graphs
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Incremental visual objects clustering with the growing vocabulary tree
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Dense subgraph maintenance under streaming edge weight updates for real-time story identification
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Intrinsically dynamic network communities
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Correspondence clustering: an approach to cluster multiple related spatial datasets
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Modeling the flow and change of information on the web
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Community detection in Social Media
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Mining temporal patterns in popularity of web items
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A sparsity-inducing formulation for evolutionary co-clustering
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Detecting changes of clustering structures using normalized maximum likelihood coding
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Understanding online groups through social media
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Maximum margin clustering on evolutionary data
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Online video segmentation by bayesian split-merge clustering
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Online community detection in social sensing
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Identification of Group Changes in Blogosphere
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Mining evolutionary multi-branch trees from text streams
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Maximizing influence of viral marketing via evolutionary user selection
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Understanding evolving group structures in time-varying networks
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Incremental local community identification in dynamic social networks
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
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Real time event detection in twitter
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Dynamic joint sentiment-topic model
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Adaptive evolutionary clustering
Data Mining and Knowledge Discovery
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We consider the problem of clustering data over time. An evolutionary clustering should simultaneously optimize two potentially conflicting criteria: first, the clustering at any point in time should remain faithful to the current data as much as possible; and second, the clustering should not shift dramatically from one timestep to the next. We present a generic framework for this problem, and discuss evolutionary versions of two widely-used clustering algorithms within this framework: k-means and agglomerative hierarchical clustering. We extensively evaluate these algorithms on real data sets and show that our algorithms can simultaneously attain both high accuracy in capturing today's data, and high fidelity in reflecting yesterday's clustering.