Sampling from a moving window over streaming data
SODA '02 Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms
Maintaining stream statistics over sliding windows: (extended abstract)
SODA '02 Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms
The cougar approach to in-network query processing in sensor networks
ACM SIGMOD Record
Continuous queries over data streams
ACM SIGMOD Record
An Online Algorithm for Segmenting Time Series
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Maintaining variance and k-medians over data stream windows
Proceedings of the twenty-second ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Finding surprising patterns in a time series database in linear time and space
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
One-Pass Wavelet Decompositions of Data Streams
IEEE Transactions on Knowledge and Data Engineering
Processing set expressions over continuous update streams
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
A framework for diagnosing changes in evolving data streams
Proceedings of the 2003 ACM SIGMOD international conference on Management of data
Aurora: a new model and architecture for data stream management
The VLDB Journal — The International Journal on Very Large Data Bases
Mining concept-drifting data streams using ensemble classifiers
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Efficient elastic burst detection in data streams
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Online novelty detection on temporal sequences
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Online event-driven subsequence matching over financial data streams
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
MAIDS: mining alarming incidents from data streams
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Adaptive, unsupervised stream mining
The VLDB Journal — The International Journal on Very Large Data Bases
Subsequence matching on structured time series data
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Streaming pattern discovery in multiple time-series
VLDB '05 Proceedings of the 31st international conference on Very large data bases
Continuous Similarity-Based Queries on Streaming Time Series
IEEE Transactions on Knowledge and Data Engineering
HOT SAX: Efficiently Finding the Most Unusual Time Series Subsequence
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
Optimal multi-scale patterns in time series streams
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
Comparing data streams using Hamming norms (how to zero in)
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
A regression-based temporal pattern mining scheme for 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
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
Pseudo Period Detection on Time Series Stream with Scale Smoothing
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
Online constrained pattern detection over streams
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 5
Finding semantics in time series
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
An adaptive algorithm for online time series segmentation with error bound guarantee
Proceedings of the 15th International Conference on Extending Database Technology
Trustworthiness analysis of sensor data in cyber-physical systems
Journal of Computer and System Sciences
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Many database applications require the analysis and processing of data streams. In such systems, huge amounts of data arrive rapidly and their values change over time. The variations on streams typically imply some fundamental changes of the underlying objects and possess significant domain meanings. In some data streams, successive events seem to recur in a certain time interval, but the data indeed evolves with tiny differences as time elapses. This feature is called pseudo periodicity, which poses a non-trivial challenge to variation management in data streams. This paper presents our research effort in online variation management over such streams, and the idea can be applied to the problem domain of medical applications, such as patient vital signal monitoring. We propose a new method named Pattern Growth Graph (PGG) to detect and manage variations over pseudo periodical streams. PGG adopts the wave-pattern to capture the major information of data evolution and represent them compactly. With the help of wave-pattern matching algorithm, PGG detects the stream variations in a single pass over the stream data. PGG only stores the different segments of the pattern for incoming stream, and hence it can substantially compress the data without losing important information. The statistical information of PGG helps to distinguish meaningful data changes from noise and to reconstruct the stream with acceptable accuracy. Extensive experiments on real datasets containing millions of data items demonstrate the feasibility and effectiveness of the proposed scheme.