The R*-tree: an efficient and robust access method for points and rectangles
SIGMOD '90 Proceedings of the 1990 ACM SIGMOD international conference on Management of data
Fast subsequence matching in time-series databases
SIGMOD '94 Proceedings of the 1994 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
Dimensionality reduction for similarity searching in dynamic databases
SIGMOD '98 Proceedings of the 1998 ACM SIGMOD international conference on Management of data
Fast time-series searching with scaling and shifting
PODS '99 Proceedings of the eighteenth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Efficient Similarity Search In Sequence Databases
FODO '93 Proceedings of the 4th International Conference on Foundations of Data Organization and Algorithms
Variable Length Queries for Time Series Data
Proceedings of the 17th International Conference on Data Engineering
The Haar Wavelet Transform in the Time Series Similarity Paradigm
PKDD '99 Proceedings of the Third European Conference on Principles of Data Mining and Knowledge Discovery
Fast Time Sequence Indexing for Arbitrary Lp Norms
VLDB '00 Proceedings of the 26th International Conference on Very Large Data Bases
Hilbert R-tree: An Improved R-tree using Fractals
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
A Signature Technique for Similarity-Based Queries
SEQUENCES '97 Proceedings of the Compression and Complexity of Sequences 1997
On Similarity-Based Queries for Time Series Data
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Efficient Time Series Matching by Wavelets
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
An Improvement of PAA for Dimensionality Reduction in Large Time Series Databases
PRICAI '08 Proceedings of the 10th Pacific Rim International Conference on Artificial Intelligence: Trends in Artificial Intelligence
Feature extraction from time series data
Journal of Computational Methods in Sciences and Engineering
Decision tree induction for identifying trends in line graphs
ISMIS'08 Proceedings of the 17th international conference on Foundations of intelligent systems
Recognizing the intended message of line graphs
Diagrams'10 Proceedings of the 6th international conference on Diagrammatic representation and inference
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Similarity search in time series data is an active area of research in data mining. In this paper we introduce a new approach for performing similarity search over time series data using second moments denoted by us as time weighted moments. This technique is based on the observation that similar time sequences will have their centroids close to each other. The proposed technique is capable of handling variable length queries. It works irrespective of global scaling and shrinking of time series data and can also handle different baselines.