Indexing values of time sequences
CIKM '96 Proceedings of the fifth international conference on Information and knowledge management
Using a sequential index in terrain-aided navigation
CIKM '97 Proceedings of the sixth international conference on Information and knowledge management
MALM: a framework for mining sequence database at multiple abstraction levels
Proceedings of the seventh international conference on Information and knowledge management
Fast time-series searching with scaling and shifting
PODS '99 Proceedings of the eighteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Mining hybrid sequential patterns and sequential rules
Information Systems
Data Mining: An Overview from a Database Perspective
IEEE Transactions on Knowledge and Data Engineering
Querying Time Series Data Based on Similarity
IEEE Transactions on Knowledge and Data Engineering
Querying Continuous Time Sequences
VLDB '98 Proceedings of the 24rd International Conference on Very Large Data Bases
Fast Time Sequence Indexing for Arbitrary Lp Norms
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Efficient Pattern Matching of Time Series Data
IEA/AIE '02 Proceedings of the 15th international conference on Industrial and engineering applications of artificial intelligence and expert systems: developments in applied artificial intelligence
Efficient Similarity Search for Time Series Data Based on the Minimum Distance
CAiSE '02 Proceedings of the 14th International Conference on Advanced Information Systems Engineering
A template model for multidimensional inter-transactional association rules
The VLDB Journal — The International Journal on Very Large Data Bases
Haar Wavelets for Efficient Similarity Search of Time-Series: With and Without Time Warping
IEEE Transactions on Knowledge and Data Engineering
Connectionist and evolutionary models for learning, discovering and forecasting software effort
Managing data mining technologies in organizations
Minimum distance queries for time series data
Journal of Systems and Software
Fast window correlations over uncooperative time series
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Information Sciences—Informatics and Computer Science: An International Journal
A non-linear dimensionality-reduction technique for fast similarity search in large databases
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
A geometrical solution to time series searching invariant to shifting and scaling
Knowledge and Information Systems
Statistical damage identification for bridges using ambient vibration data
Computers and Structures
Mining Nonambiguous Temporal Patterns for Interval-Based Events
IEEE Transactions on Knowledge and Data Engineering
Generalized regression model for sequence matching and clustering
Knowledge and Information Systems
StatStream: statistical monitoring of thousands of data streams in real time
VLDB '02 Proceedings of the 28th international conference on Very Large Data Bases
Indexing time series using signatures
Intelligent Data Analysis
On mining multi-time-interval sequential patterns
Data & Knowledge Engineering
Information Sciences: an International Journal
Fast approximate correlation for massive time-series data
Proceedings of the 2010 ACM SIGMOD International Conference on Management of data
Knowledge gathering of fuzzy multi-time-interval sequential patterns
Information Sciences: an International Journal
Discovering multi-label temporal patterns in sequence databases
Information Sciences: an International Journal
A review on time series data mining
Engineering Applications of Artificial Intelligence
Parsimonious temporal aggregation
The VLDB Journal — The International Journal on Very Large Data Bases
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We present a hierarchical algorithm, HierarchyScan, that efficiently locates one-dimensional subsequences within a collection of sequences of arbitrary length. The subsequences identified by HierarchyScan match a given template pattern in a scale- and phase-independent fashion. The idea is to perform correlation between the stored sequences and the template in the transformed domain hierarchically. Only those subsequences whose maximum correlation value is higher than a predefined threshold will be selected. The performance of this approach is compared to the sequential scanning and an order-of-magnitude speedup is observed.