Fast subsequence matching in time-series databases
SIGMOD '94 Proceedings of the 1994 ACM SIGMOD international conference on Management of data
Similarity-based queries for time series data
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Efficiently supporting ad hoc queries in large datasets of time sequences
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Segment-based approach for subsequence searches in sequence databases
Proceedings of the 2001 ACM symposium on Applied computing
On computing correlated aggregates over continual data streams
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Locally adaptive dimensionality reduction for indexing large time series databases
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Maintaining stream statistics over sliding windows: (extended abstract)
SODA '02 Proceedings of the thirteenth annual ACM-SIAM symposium on Discrete algorithms
Continually evaluating similarity-based pattern queries on a streaming time series
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
General match: a subsequence matching method in time-series databases based on generalized windows
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
Evaluating continuous nearest neighbor queries for streaming time series via pre-fetching
Proceedings of the eleventh international conference on Information and knowledge management
Continuous queries over data streams
ACM SIGMOD Record
Efficient Similarity Search In Sequence Databases
FODO '93 Proceedings of the 4th International Conference on Foundations of Data Organization and Algorithms
Efficient Retrieval of Similar Time Sequences Under Time Warping
ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
PKDD '97 Proceedings of the First European Symposium on Principles of Data Mining and Knowledge Discovery
Surfing Wavelets on Streams: One-Pass Summaries for Approximate Aggregate Queries
Proceedings of the 27th International Conference on Very Large Data Bases
Issues in data stream management
ACM SIGMOD Record
Online event-driven subsequence matching over financial data streams
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
StatStream: statistical monitoring of thousands of data streams in real time
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Effective variation management for pseudo periodical streams
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
Using multiple indexes for efficient subsequence matching in time-series databases
Information Sciences: an International Journal
Mining approximate top-k subspace anomalies in multi-dimensional time-series data
VLDB '07 Proceedings of the 33rd international conference on Very large data bases
Approximate embedding-based subsequence matching of time series
Proceedings of the 2008 ACM SIGMOD international conference on Management of data
Temporal pattern matching for the prediction of stock prices
AIDM '07 Proceedings of the 2nd international workshop on Integrating artificial intelligence and data mining - Volume 84
SNIF TOOL: sniffing for patterns in continuous streams
Proceedings of the 17th ACM conference on Information and knowledge management
PGG: an online pattern based approach for stream variation management
Journal of Computer Science and Technology
Towards faster activity search using embedding-based subsequence matching
Proceedings of the 2nd International Conference on PErvasive Technologies Related to Assistive Environments
Online constrained pattern detection over streams
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 5
A contextual data mining approach toward assisting the treatment of anxiety disorders
IEEE Transactions on Information Technology in Biomedicine - Special section on new and emerging technologies in bioinformatics and bioengineering
Benchmarking dynamic time warping for music retrieval
Proceedings of the 3rd International Conference on PErvasive Technologies Related to Assistive Environments
A review on time series data mining
Engineering Applications of Artificial Intelligence
TIDES--a new descriptor for time series oscillation behavior
Geoinformatica
Embedding-based subsequence matching in time-series databases
ACM Transactions on Database Systems (TODS)
Time series subsequence searching in specialized binary tree
FSKD'06 Proceedings of the Third international conference on Fuzzy Systems and Knowledge Discovery
Online windowed subsequence matching over probabilistic sequences
SIGMOD '12 Proceedings of the 2012 ACM SIGMOD International Conference on Management of Data
Short communication: Selective Subsequence Time Series clustering
Knowledge-Based Systems
Mining effective multi-segment sliding window for pathogen incidence rate prediction
Data & Knowledge Engineering
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Subsequence matching in time series databases is a useful technique, with applications in pattern matching, prediction, and rule discovery. Internal structure within the time series data can be used to improve these tasks, and provide important insight into the problem domain. This paper introduces our research effort in using the internal structure of a time series directly in the matching process. This idea is applied to the problem domain of respiratory motion data in cancer radiation treatment. We propose a comprehensive solution for analysis, clustering, and online prediction of respiratory motion using subsequence similarity matching. In this system, a motion signal is captured in real time as a data stream, and is analyzed immediately for treatment and also saved in a database for future study. A piecewise linear representation of the signal is generated from a finite state model, and is used as a query for subsequence matching. To ensure that the query subsequence is representative, we introduce the concept of subsequence stability, which can be used to dynamically adjust the query subsequence length. To satisfy the special needs of similarity matching over breathing patterns, a new subsequence similarity measure is introduced. This new measure uses a weighted L1 distance function to capture the relative importance of each source stream, amplitude, frequency, and proximity in time. From the subsequence similarity measure, stream and patient similarity can be defined, which are then used for offline and online applications. The matching results are analyzed and applied for motion prediction and correlation discovery. While our system has been customized for use in radiation therapy, our approach to time series modeling is general enough for application domains with structured time series data.