A framework for measuring changes in data characteristics
PODS '99 Proceedings of the eighteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Tracking dynamics of topic trends using a finite mixture model
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
A unified and flexible framework for comparing simple and complex patterns
PKDD '04 Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases
On Change Diagnosis in Evolving Data Streams
IEEE Transactions on Knowledge and Data Engineering
Discovering evolutionary theme patterns from text: an exploration of temporal text mining
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
A generalized framework for mining spatio-temporal patterns in scientific data
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
On discovering moving clusters in spatio-temporal data
SSTD'05 Proceedings of the 9th international conference on Advances in Spatial and Temporal Databases
Discovering emerging topics in unlabelled text collections
ADBIS'06 Proceedings of the 10th East European conference on Advances in Databases and Information Systems
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
Facetnet: a framework for analyzing communities and their evolutions in dynamic networks
Proceedings of the 17th international conference on World Wide Web
Pattern-Miner: integrated management and mining over data mining models
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
ACM SIGKDD Explorations Newsletter
Users in Volatile Communities: Studying Active Participation and Community Evolution
UM '07 Proceedings of the 11th international conference on User Modeling
Monitoring Patterns through an Integrated Management and Mining Tool
ECML PKDD '08 Proceedings of the European conference on Machine Learning and Knowledge Discovery in Databases - Part II
The SKM Algorithm: A K-Means Algorithm for Clustering Sequential Data
IBERAMIA '08 Proceedings of the 11th Ibero-American conference on AI: Advances in Artificial Intelligence
Discovery of convoys in trajectory databases
Proceedings of the VLDB Endowment
A Query Language and Its Processing for Time-Series Document Clusters
ICADL 08 Proceedings of the 11th International Conference on Asian Digital Libraries: Universal and Ubiquitous Access to Information
Analyzing communities and their evolutions in dynamic social networks
ACM Transactions on Knowledge Discovery from Data (TKDD)
Change analysis in spatial datasets by interestingness comparison
SIGSPATIAL Special
Change Analysis in Spatial Data by Combining Contouring Algorithms with Supervised Density Functions
PAKDD '09 Proceedings of the 13th Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining
On exploiting the power of time in data mining
ACM SIGKDD Explorations Newsletter
SSTD '09 Proceedings of the 11th International Symposium on Advances in Spatial and Temporal Databases
On evolutionary spectral clustering
ACM Transactions on Knowledge Discovery from Data (TKDD)
Detecting topic evolution in scientific literature: how can citations help?
Proceedings of the 18th ACM conference on Information and knowledge management
On-line discovery of flock patterns in spatio-temporal data
Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Automatic Detection of Terminology Evolution
OTM '09 Proceedings of the Confederated International Workshops and Posters on On the Move to Meaningful Internet Systems: ADI, CAMS, EI2N, ISDE, IWSSA, MONET, OnToContent, ODIS, ORM, OTM Academy, SWWS, SEMELS, Beyond SAWSDL, and COMBEK 2009
Quantitative evaluation of clusterings for marketing applications: a web portal case study
EPIA'07 Proceedings of the aritficial intelligence 13th Portuguese conference on Progress in artificial intelligence
Towards characterization of actor evolution and interactions in news corpora
ECIR'08 Proceedings of the IR research, 30th European conference on Advances in information retrieval
Analyzing change in spatial data by utilizing polygon models
Proceedings of the 1st International Conference and Exhibition on Computing for Geospatial Research & Application
SSDBM'10 Proceedings of the 22nd international conference on Scientific and statistical database management
MEC --Monitoring Clusters' Transitions
Proceedings of the 2010 conference on STAIRS 2010: Proceedings of the Fifth Starting AI Researchers' Symposium
The web of topics: discovering the topology of topic evolution in a corpus
Proceedings of the 20th international conference on World wide web
Community Discovery via Metagraph Factorization
ACM Transactions on Knowledge Discovery from Data (TKDD)
Tracing evolving clusters by subspace and value similarity
PAKDD'11 Proceedings of the 15th Pacific-Asia conference on Advances in knowledge discovery and data mining - Volume Part II
Summarizing cluster evolution in dynamic environments
ICCSA'11 Proceedings of the 2011 international conference on Computational science and its applications - Volume Part II
Density based subspace clustering over dynamic data
SSDBM'11 Proceedings of the 23rd international conference on Scientific and statistical database management
CLUES: a unified framework supporting interactive exploration of density-based clusters in streams
Proceedings of the 20th ACM international conference on Information and knowledge management
Tracing Evolving Subspace Clusters in Temporal Climate Data
Data Mining and Knowledge Discovery
Bipartite graphs for monitoring clusters transitions
IDA'10 Proceedings of the 9th international conference on Advances in Intelligent Data Analysis
Discovering emerging topics in unlabelled text collections
ADBIS'06 Proceedings of the 10th East European conference on Advances in Databases and Information Systems
Intrinsically dynamic network communities
Computer Networks: The International Journal of Computer and Telecommunications Networking
Community cores in evolving networks
Proceedings of the 21st international conference companion on World Wide Web
Discovering global and local bursts in a stream of news
Proceedings of the 27th Annual ACM Symposium on Applied Computing
CAMEUD: clustering approach for mining evolving usage data
Proceedings of the Ninth International Workshop on Information Integration on the Web
Expert Systems with Applications: An International Journal
Stream-dashboard: a framework for mining, tracking and validating clusters in a data stream
Proceedings of the 1st International Workshop on Big Data, Streams and Heterogeneous Source Mining: Algorithms, Systems, Programming Models and Applications
T-Scroll: visualizing trends in a time-series of documents for interactive user exploration
ECDL'07 Proceedings of the 11th European conference on Research and Advanced Technology for Digital Libraries
Online semantic mapping of urban environments
SC'12 Proceedings of the 2012 international conference on Spatial Cognition VIII
Where are we going? predicting the evolution of individuals
IDA'12 Proceedings of the 11th international conference on Advances in Intelligent Data Analysis
FINGERPRINT: Summarizing Cluster Evolution in Dynamic Environments
International Journal of Data Warehousing and Mining
Real Time Distributed Community Structure Detection in Dynamic Networks
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
Monitoring User Evolution in Twitter
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
Investigating Organized Crime Groups: A Social Network Analysis Perspective
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
Community evolution detection in time-evolving information networks
Proceedings of the Joint EDBT/ICDT 2013 Workshops
Nesting the earth mover's distance for effective cluster tracing
Proceedings of the 25th International Conference on Scientific and Statistical Database Management
Computer science fields as ground-truth communities: their impact, rise and fall
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Social life networks: a multimedia problem?
Proceedings of the 21st ACM international conference on Multimedia
Proceedings of the 17th International Database Engineering & Applications Symposium
Data stream clustering: A survey
ACM Computing Surveys (CSUR)
A framework to monitor clusters evolution applied to economy and finance problems
Intelligent Data Analysis
Mining trajectories of moving dynamic spatio-temporal regions in sensor datasets
Data Mining and Knowledge Discovery
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There is much recent work on detecting and tracking change in clusters, often based on the study of the spatiotemporal properties of a cluster. For the many applications where cluster change is relevant, among them customer relationship management, fraud detection and marketing, it is also necessary to provide insights about the nature of cluster change: Is a cluster corresponding to a group of customers simply disappearing or are its members migrating to other clusters? Is a new emerging cluster reflecting a new target group of customers or does it rather consist of existing customers whose preferences shift? To answer such questions, we propose the framework MONIC for modeling and tracking of cluster transitions. Our cluster transition model encompasses changes that involve more than one cluster, thus allowing for insights on cluster change in the whole clustering. Our transition tracking mechanism is not based on the topological properties of clusters, which are only available for some types of clustering, but on the contents of the underlying data stream. We present our first results on monitoring cluster transitions over the ACM digital library.