BIRCH: an efficient data clustering method for very large databases
SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
CURE: an efficient clustering algorithm for large databases
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Mining frequent patterns without candidate generation
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Efficient computation of Iceberg cubes with complex measures
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Machine Learning
Models and issues in data stream systems
Proceedings of the twenty-first ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Multi-dimensional regression analysis of time-series data streams
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
A framework for clustering evolving data streams
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
ACM SIGMOD Record
Research issues in data stream association rule mining
ACM SIGMOD Record
Hierarchical Visualization of Network Intrusion Detection Data
IEEE Computer Graphics and Applications
Classification spanning correlated data streams
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Effective variation management for pseudo periodical streams
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Event-Based Compression and Mining of Data Streams
KES '08 Proceedings of the 12th international conference on Knowledge-Based Intelligent Information and Engineering Systems, Part II
Incremental clustering of dynamic data streams using connectivity based representative points
Data & Knowledge Engineering
Palantir: a framework for collaborative incident response and investigation
Proceedings of the 8th Symposium on Identity and Trust on the Internet
Intervention Events Detection and Prediction in Data Streams
APWeb/WAIM '09 Proceedings of the Joint International Conferences on Advances in Data and Web Management
PGG: an online pattern based approach for stream variation management
Journal of Computer Science and Technology
Composing Miners to Develop an Intrusion Detection Solution
Privacy, Security, and Trust in KDD
CAMS: OLAPing Multidimensional Data Streams Efficiently
DaWaK '09 Proceedings of the 11th International Conference on Data Warehousing and Knowledge Discovery
DS-Cuber: an integrated OLAP environment for data streams
Proceedings of the 18th ACM conference on Information and knowledge management
Location-dependent query processing: Where we are and where we are heading
ACM Computing Surveys (CSUR)
Event-based lossy compression for effective and efficient OLAP over data streams
Data & Knowledge Engineering
i-SEE: integrated stream execution environment over on-line data streams
CIKM '10 Proceedings of the 19th ACM international conference on Information and knowledge management
An efficient approach for mining segment-wise intervention rules in time-series streams
WAIM'10 Proceedings of the 11th international conference on Web-age information management
SSDBM'11 Proceedings of the 23rd international conference on Scientific and statistical database management
DSEC: a data stream engine based clinical information system
APWeb'06 Proceedings of the 8th Asia-Pacific Web conference on Frontiers of WWW Research and Development
Monitoring abnormal patterns with complex semantics over ICU data streams
IWICPAS'06 Proceedings of the 2006 Advances in Machine Vision, Image Processing, and Pattern Analysis international conference on Intelligent Computing in Pattern Analysis/Synthesis
Non-linear data stream compression: foundations and theoretical results
HAIS'12 Proceedings of the 7th international conference on Hybrid Artificial Intelligent Systems - Volume Part I
Sequential pattern mining -- approaches and algorithms
ACM Computing Surveys (CSUR)
FGIT'12 Proceedings of the 4th international conference on Future Generation Information Technology
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