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
FreeSpan: frequent pattern-projected sequential pattern mining
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Content-Based Image Retrieval at the End of the Early Years
IEEE Transactions on Pattern Analysis and Machine Intelligence
A guided tour to approximate string matching
ACM Computing Surveys (CSUR)
Locally adaptive dimensionality reduction for indexing large time series databases
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Data mining: concepts and techniques by Jiawei Han and Micheline Kamber
ACM SIGMOD Record
Wireless sensor networks for habitat monitoring
WSNA '02 Proceedings of the 1st ACM international workshop on Wireless sensor networks and applications
Wireless sensor networks: a survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
An Online Algorithm for Segmenting Time Series
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
VLDB '86 Proceedings of the 12th International Conference on Very Large Data Bases
Fast Similarity Search in the Presence of Noise, Scaling, and Translation in Time-Series Databases
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
PADKK '00 Proceedings of the 4th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Current Issues and New Applications
Issues in data stream management
ACM SIGMOD Record
Fast Retrieval of Similar Subsequences in Long Sequence Databases
KDEX '99 Proceedings of the 1999 Workshop on Knowledge and Data Engineering Exchange
Online Data Mining for Co-Evolving Time Sequences
ICDE '00 Proceedings of the 16th International Conference on Data Engineering
A symbolic representation of time series, with implications for streaming algorithms
DMKD '03 Proceedings of the 8th ACM SIGMOD workshop on Research issues in data mining and knowledge discovery
Indexing spatio-temporal trajectories with Chebyshev polynomials
SIGMOD '04 Proceedings of the 2004 ACM SIGMOD international conference on Management of data
Exact indexing of dynamic time warping
Knowledge and Information Systems
Subsequence matching on structured time series data
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Managing Requirements in a Co-evolution Context
RE '05 Proceedings of the 13th IEEE International Conference on Requirements Engineering
MauveDB: supporting model-based user views in database systems
Proceedings of the 2006 ACM SIGMOD international conference on Management of data
A note on efficient aggregate queries in sensor networks
Theoretical Computer Science
Experiencing SAX: a novel symbolic representation of time series
Data Mining and Knowledge Discovery
Data mining with Temporal Abstractions: learning rules from time series
Data Mining and Knowledge Discovery
Model-driven data acquisition in sensor networks
VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
Forecasting Solar Activity Using Co-evolution of Models and Tests
ISDA '07 Proceedings of the Seventh International Conference on Intelligent Systems Design and Applications
Space-Time Summarization of Multisensor Time Series. Case of Missing Data
ICDMW '07 Proceedings of the Seventh IEEE International Conference on Data Mining Workshops
Diagnosing Similarity of Oscillation Trends in Time Series
ICDMW '07 Proceedings of the Seventh IEEE International Conference on Data Mining Workshops
Proceedings of the VLDB Endowment
APCAS: an approximate approach to adaptively segment time series stream
APWeb/WAIM'07 Proceedings of the joint 9th Asia-Pacific web and 8th international conference on web-age information management conference on Advances in data and web management
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Sensor networks have increased the amount and variety of temporal data available, requiring the definition of new techniques for data mining. Related research typically addresses the problems of indexing, clustering, classification, summarization, and anomaly detection. There is a wide range of techniques to describe and compare time series, but they focus on series' values. This paper concentrates on a new aspect--that of describing oscillation patterns. It presents a technique for time series similarity search, and multiple temporal scales, defining a descriptor that uses the angular coefficients from a linear segmentation of the curve that represents the evolution of the analyzed series. This technique is generalized to handle co-evolution, in which several phenomena vary at the same time. Preliminary experiments with real datasets showed that our approach correctly characterizes the oscillation of single time series, for multiple time scales, and is able to compute the similarity among sets of co-evolving series.