Grid Representation for Efficient Similarity Search in Time Series Databases

Widespread interest in time-series similarity search has made more in need of efficient technique, which can reduce dimensionality of the data and then to index it easily using a multidimensional structure. In this paper, we introduce a new technique, which we called grid representation, based on a grid approximation of the data. We propose a lower bounding distance measure that enables a bitmap approach for fast computation and searching. We also show how grid representation can be indexed with a multidimensional index structure, and demonstrate its superiority.

[1]  Eamonn Keogh.  Exact Indexing of Dynamic Time Warping , 2002, VLDB.

[2]  Christos Faloutsos,et al.  Fast Time Sequence Indexing for Arbitrary Lp Norms , 2000, VLDB.

[3]  Christos Faloutsos,et al.  Efficiently supporting ad hoc queries in large datasets of time sequences , 1997, SIGMOD '97.

[4]  Eamonn J. Keogh,et al.  Mining motifs in massive time series databases , 2002, 2002 IEEE International Conference on Data Mining, 2002. Proceedings..

[5]  Jessica Lin,et al.  Finding Motifs in Time Series , 2002, KDD 2002.

[6]  Eamonn J. Keogh,et al.  HOT SAX: efficiently finding the most unusual time series subsequence , 2005, Fifth IEEE International Conference on Data Mining (ICDM'05).

[7]  Christos H. Papadimitriou,et al.  On the analysis of indexing schemes , 1997, PODS '97.

[8]  Christos H. Papadimitriou,et al.  Towards an analysis of indexing schemes , 1997, PODS 1997.

[9]  Ada Wai-Chee Fu,et al.  Efficient time series matching by wavelets , 1999, Proceedings 15th International Conference on Data Engineering (Cat. No.99CB36337).

[10]  Nitin Kumar,et al.  Time-series Bitmaps: a Practical Visualization Tool for Working with Large Time Series Databases , 2005, SDM.

[11]  Padhraic Smyth,et al.  Deformable Markov model templates for time-series pattern matching , 2000, KDD '00.

[12]  KeoghEamonn,et al.  On the Need for Time Series Data Mining Benchmarks , 2003 .

[13]  Sharad Mehrotra,et al.  The hybrid tree: an index structure for high dimensional feature spaces , 1999, Proceedings 15th International Conference on Data Engineering (Cat. No.99CB36337).

[14]  Antonin Guttman,et al.  R-trees: a dynamic index structure for spatial searching , 1984, SIGMOD '84.

[15]  Eamonn J. Keogh,et al.  Dimensionality Reduction for Fast Similarity Search in Large Time Series Databases , 2001, Knowledge and Information Systems.

[16]  Divyakant Agrawal,et al.  A comparison of DFT and DWT based similarity search in time-series databases , 2000, CIKM '00.

[17]  Eamonn J. Keogh,et al.  On the Need for Time Series Data Mining Benchmarks: A Survey and Empirical Demonstration , 2002, Data Mining and Knowledge Discovery.

[18]  Ambuj K. Singh,et al.  Variable length queries for time series data , 2001, Proceedings 17th International Conference on Data Engineering.

[19]  Christos Faloutsos,et al.  Searching Multimedia Databases by Content , 1996, Advances in Database Systems.

[20]  Haixun Wang,et al.  Landmarks: a new model for similarity-based pattern querying in time series databases , 2000, Proceedings of 16th International Conference on Data Engineering (Cat. No.00CB37073).

[21]  George M. Church,et al.  Aligning gene expression time series with time warping algorithms , 2001, Bioinform..

[22]  Eamonn J. Keogh,et al.  Probabilistic discovery of time series motifs , 2003, KDD '03.

[23]  Donald J. Berndt,et al.  Using Dynamic Time Warping to Find Patterns in Time Series , 1994, KDD Workshop.

[24]  Quanzhong Li,et al.  Skyline index for time series data , 2004, IEEE Transactions on Knowledge and Data Engineering.

[25]  Ambuj K. Singh,et al.  Dimensionality reduction for similarity searching in dynamic databases , 1998, SIGMOD '98.

[26]  Christos Faloutsos,et al.  Efficient Similarity Search In Sequence Databases , 1993, FODO.