Incremental clustering and dynamic information retrieval
STOC '97 Proceedings of the twenty-ninth annual ACM symposium on Theory of computing
Normalized Cuts and Image Segmentation
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Multilinear Singular Value Decomposition
SIAM Journal on Matrix Analysis and Applications
Constrained K-means Clustering with Background Knowledge
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
FOCS '00 Proceedings of the 41st Annual Symposium on Foundations of Computer Science
Segmentation Using Eigenvectors: A Unifying View
ICCV '99 Proceedings of the International Conference on Computer Vision-Volume 2 - Volume 2
Kernel k-means: spectral clustering and normalized cuts
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
K-means clustering via principal component analysis
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Document clustering with prior knowledge
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Learning Spectral Clustering, With Application To Speech Separation
The Journal of Machine Learning Research
A framework for clustering evolving data streams
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
Facetnet: a framework for analyzing communities and their evolutions in dynamic networks
Proceedings of the 17th international conference on World Wide Web
A bayesian mixture model with linear regression mixing proportions
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Community evolution in dynamic multi-mode networks
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Colibri: fast mining of large static and dynamic graphs
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Fast mining of complex time-stamped events
Proceedings of the 17th ACM conference on Information and knowledge management
Analyzing communities and their evolutions in dynamic social networks
ACM Transactions on Knowledge Discovery from Data (TKDD)
Incremental spectral clustering by efficiently updating the eigen-system
Pattern Recognition
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
A particle-and-density based evolutionary clustering method for dynamic networks
Proceedings of the VLDB Endowment
CHRONICLE: A Two-Stage Density-Based Clustering Algorithm for Dynamic Networks
DS '09 Proceedings of the 12th International Conference on Discovery Science
Fast computation of SimRank for static and dynamic information networks
Proceedings of the 13th International Conference on Extending Database Technology
Community evolution detection in dynamic heterogeneous information networks
Proceedings of the Eighth Workshop on Mining and Learning with Graphs
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
Metric forensics: a multi-level approach for mining volatile graphs
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
Parallel SimRank computation on large graphs with iterative aggregation
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
Online evolutionary collaborative filtering
Proceedings of the fourth ACM conference on Recommender systems
Adapting neighborhood and matrix factorization models for context aware recommendation
Proceedings of the Workshop on Context-Aware Movie Recommendation
A framework for clustering categorical time-evolving data
IEEE Transactions on Fuzzy Systems
Tracking communities in dynamic social networks
SBP'11 Proceedings of the 4th international conference on Social computing, behavioral-cultural modeling and prediction
Neurocomputing
Community Discovery via Metagraph Factorization
ACM Transactions on Knowledge Discovery from Data (TKDD)
Spatio-temporal data evolutionary clustering based on MOEA/D
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Eigenvector sensitive feature selection for spectral clustering
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part II
On clustering heterogeneous social media objects with outlier links
Proceedings of the fifth ACM international conference on Web search and data mining
Relation strength-aware clustering of heterogeneous information networks with incomplete attributes
Proceedings of the VLDB Endowment
International Journal of Computer Vision
Discovering global and local bursts in a stream of news
Proceedings of the 27th Annual ACM Symposium on Applied Computing
Mining temporal patterns in popularity of web items
Information Sciences: an International Journal
Generative Models for Evolutionary Clustering
ACM Transactions on Knowledge Discovery from Data (TKDD)
Non-negative residual matrix factorization: problem definition, fast solutions, and applications
Statistical Analysis and Data Mining
SeqiBloc: mining multi-time spanning blockmodels in dynamic graphs
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining
ciForager: Incrementally discovering regions of correlated change in evolving graphs
ACM Transactions on Knowledge Discovery from Data (TKDD)
Maximum margin clustering on evolutionary data
Proceedings of the 21st ACM international conference on Information and knowledge management
Tracing clusters in evolving graphs with node attributes
Proceedings of the 21st ACM international conference on Information and knowledge management
Online video segmentation by bayesian split-merge clustering
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part IV
Online community detection in social sensing
Proceedings of the sixth ACM international conference on Web search and data mining
Optimizing temporal topic segmentation for intelligent text visualization
Proceedings of the 2013 international conference on Intelligent user interfaces
Exploiting online social data in ontology learning for event tracking and emergency response
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Analyzing future communities in growing citation networks
Proceedings of the 2013 international workshop on Mining unstructured big data using natural language processing
Proceedings of the 17th International Database Engineering & Applications Symposium
Summarizing dynamic Social Tagging Systems
Expert Systems with Applications: An International Journal
Dynamic joint sentiment-topic model
ACM Transactions on Intelligent Systems and Technology (TIST) - Special Section on Intelligent Mobile Knowledge Discovery and Management Systems and Special Issue on Social Web Mining
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Evolutionary clustering is an emerging research area essential to important applications such as clustering dynamic Web and blog contents and clustering data streams. In evolutionary clustering, a good clustering result should fit the current data well, while simultaneously not deviate too dramatically from the recent history. To fulfill this dual purpose, a measure of temporal smoothness is integrated in the overall measure of clustering quality. In this paper, we propose two frameworks that incorporate temporal smoothness in evolutionary spectral clustering. For both frameworks, we start with intuitions gained from the well-known k-means clustering problem, and then propose and solve corresponding cost functions for the evolutionary spectral clustering problems. Our solutions to the evolutionary spectral clustering problems provide more stable and consistent clustering results that are less sensitive to short-term noises while at the same time are adaptive to long-term cluster drifts. Furthermore, we demonstrate that our methods provide the optimal solutions to the relaxed versions of the corresponding evolutionary k-means clustering problems. Performance experiments over a number of real and synthetic data sets illustrate our evolutionary spectral clustering methods provide more robust clustering results that are not sensitive to noise and can adapt to data drifts.