Meaningful change detection in structured data
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
A framework for measuring changes in data characteristics
PODS '99 Proceedings of the eighteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Hancock: a language for processing very large-scale data
Proceedings of the 2nd conference on Domain-specific languages
Evolution and change in data management — issues and directions
ACM SIGMOD Record
Hancock: a language for extracting signatures from data streams
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining high-speed data streams
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Mining data streams under block evolution
ACM SIGKDD Explorations Newsletter
Maintenance of Discovered Association Rules in Large Databases: An Incremental Updating Technique
ICDE '96 Proceedings of the Twelfth International Conference on Data Engineering
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Efficient Snapshot Differential Algorithms for Data Warehousing
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
Research Issues in Spatio-temporal Database Systems
SSD '99 Proceedings of the 6th International Symposium on Advances in Spatial Databases
A bibliography of temporal, spatial and spatio-temporal data mining research
ACM SIGKDD Explorations Newsletter
Dynamic Histograms: Capturing Evolving Data Sets
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
Online Data Mining for Co-Evolving Time Sequences
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
Systematic data selection to mine concept-drifting data streams
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
On demand classification of data streams
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Framework and algorithms for trend analysis in massive temporal data sets
Proceedings of the thirteenth ACM international conference on Information and knowledge management
On Change Diagnosis in Evolving Data Streams
IEEE Transactions on Knowledge and Data Engineering
LIPED: HMM-based life profiles for adaptive event detection
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Streaming pattern discovery in multiple time-series
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Temporal analysis of clusters of supermarket customers: conventional versus interval set approach
Information Sciences—Informatics and Computer Science: An International Journal
A martingale framework for concept change detection in time-varying data streams
ICML '05 Proceedings of the 22nd international conference on Machine learning
A Framework for On-Demand Classification of Evolving Data Streams
IEEE Transactions on Knowledge and Data Engineering
Evaluating the intrinsic dimension of evolving data streams
Proceedings of the 2006 ACM symposium on Applied computing
Adaptive non-linear clustering in data streams
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
The Journal of Machine Learning Research
Detecting and tracking regional outliers in meteorological data
Information Sciences: an International Journal
Effective variation management for pseudo periodical streams
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Statistical change detection for multi-dimensional data
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
A framework for clustering evolving data streams
VLDB '03 Proceedings of the 29th international conference on Very large data bases - Volume 29
A framework for projected clustering of high dimensional data streams
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Approximate mining of maximal frequent itemsets in data streams with different window models
Expert Systems with Applications: An International Journal
A Problem Oriented Approach to Data Mining in Distributed Spatio-temporal Database
ICCS '07 Proceedings of the 7th international conference on Computational Science, Part III: ICCS 2007
An Incremental Fuzzy Decision Tree Classification Method for Mining Data Streams
MLDM '07 Proceedings of the 5th international conference on Machine Learning and Data Mining in Pattern Recognition
Clustering Massive Text Data Streams by Semantic Smoothing Model
ADMA '07 Proceedings of the 3rd international conference on Advanced Data Mining and Applications
Maintaining the Maximum Normalized Mean and Applications in Data Stream Mining
ADMA '08 Proceedings of the 4th international conference on Advanced Data Mining and Applications
StreamKrimp: Detecting Change in Data Streams
ECML PKDD '08 Proceedings of the 2008 European Conference on Machine Learning and Knowledge Discovery in Databases - Part I
A framework for estimating complex probability density structures in data streams
Proceedings of the 17th ACM conference on Information and knowledge management
An adaptive threshold framework for event detection using HMM-based life profiles
ACM Transactions on Information Systems (TOIS)
PGG: an online pattern based approach for stream variation management
Journal of Computer Science and Technology
Measuring evolving data streams' behavior through their intrinsic dimension
New Generation Computing
On classification and segmentation of massive audio data streams
Knowledge and Information Systems
Change (Detection) You Can Believe in: Finding Distributional Shifts in Data Streams
IDA '09 Proceedings of the 8th International Symposium on Intelligent Data Analysis: Advances in Intelligent Data Analysis VIII
History Guided Low-Cost Change Detection in Streams
DaWaK '09 Proceedings of the 11th International Conference on Data Warehousing and Knowledge Discovery
Mining data streams with periodically changing distributions
Proceedings of the 18th ACM conference on Information and knowledge management
Efficient incremental mining of contrast patterns in changing data
Information Processing Letters
Temporal analysis of clusters of supermarket customers: conventional versus interval set approach
Information Sciences: an International Journal
Efficient decision tree construction for mining time-varying data streams
CASCON '09 Proceedings of the 2009 Conference of the Center for Advanced Studies on Collaborative Research
Visualising the cluster structure of data streams
IDA'07 Proceedings of the 7th international conference on Intelligent data analysis
FAW'07 Proceedings of the 1st annual international conference on Frontiers in algorithmics
PAKDD'07 Proceedings of the 2007 international conference on Emerging technologies in knowledge discovery and data mining
Data Mining and Knowledge Discovery
MEC --Monitoring Clusters' Transitions
Proceedings of the 2010 conference on STAIRS 2010: Proceedings of the Fifth Starting AI Researchers' Symposium
Self-adaptive change detection in streaming data with non-stationary distribution
ADMA'10 Proceedings of the 6th international conference on Advanced data mining and applications: Part I
Efficient decision tree re-alignment for clustering time-changing data streams
From active data management to event-based systems and more
On complex event processing for real-time situational awareness
RuleML'2011 Proceedings of the 5th international conference on Rule-based reasoning, programming, and applications
SCENT: Scalable compressed monitoring of evolving multirelational social networks
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP) - Special section on ACM multimedia 2010 best paper candidates, and issue on social media
Anomaly detection in information streams without prior domain knowledge
IBM Journal of Research and Development
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
Robustness of change detection algorithms
IDA'11 Proceedings of the 10th international conference on Advances in intelligent data analysis X
A random method for quantifying changing distributions in data streams
PKDD'05 Proceedings of the 9th European conference on Principles and Practice of Knowledge Discovery in Databases
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
On futuristic query processing in data streams
EDBT'06 Proceedings of the 10th international conference on Advances in Database Technology
Granularity adaptive density estimation and on demand clustering of concept-drifting data streams
DaWaK'06 Proceedings of the 8th international conference on Data Warehousing and Knowledge Discovery
Bipartite graphs for monitoring clusters transitions
IDA'10 Proceedings of the 9th international conference on Advances in Intelligent Data Analysis
On clustering techniques for change diagnosis in data streams
WebKDD'05 Proceedings of the 7th international conference on Knowledge Discovery on the Web: advances in Web Mining and Web Usage Analysis
Clustering similarity comparison using density profiles
AI'06 Proceedings of the 19th Australian joint conference on Artificial Intelligence: advances in Artificial Intelligence
Situation-Aware adaptive visualization for sensory data stream mining
Sensor-KDD'08 Proceedings of the Second international conference on Knowledge Discovery from Sensor Data
Towards a variable size sliding window model for frequent itemset mining over data streams
Computers and Industrial Engineering
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
Data stream clustering: A survey
ACM Computing Surveys (CSUR)
A framework to monitor clusters evolution applied to economy and finance problems
Intelligent Data Analysis
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In recent years, the progress in hardware technology has made it possible for organizations to store and record large streams of transactional data. This results in databases which grow without limit at a rapid rate. This data can often show important changes in trends over time. In such cases, it is useful to understand, visualize and diagnose the evolution of these trends. When the data streams are fast and continuous, it becomes important to analyze and predict the trends quickly in online fashion. In this paper, we discuss the concept of velocity density estimation, a technique used to understand, visualize and determine trends in the evolution of fast data streams. We show how to use velocity density estimation in order to create both temporal velocity profiles and spatial velocity profiles at periodic instants in time. These profiles are then used in order to predict three kinds of data evolution: dissolution, coagulation and shift. Methods are proposed to visualize the changing data trends in a single online scan of the data stream, and a computational requirement which is linear in the number of data points. In addition, batch processing techniques are proposed in order to identify combinations of dimensions which show the greatest amount of global evolution. The techniques discussed in this paper can be easily extended to spatio-temporal data, changes in data snapshots at fixed instances in time, or any other data which has a temporal component during its evolution.