TY - GEN
T1 - Approximate search on massive spatiotemporal datasets
AU - Brugere, Ivan
AU - Steinhaeuser, Karsten
AU - Boriah, Shyam
AU - Kumar, Vipin
PY - 2012
Y1 - 2012
N2 - Efficient time series similarity search is a fundamental operation for data exploration and analysis. While previous work has focused on indexing progressively larger datasets and has proposed data structures with efficient exact search algorithms, we motivate the need for approximate query methods that can be used in interactive exploration and as fast data analysis subroutines on large spatiotemporal datasets. We formulate a simple approximate range query problem for time series data, and propose a method that aims to quickly access a small number of high quality results of the exact search resultset.We propose an evaluation strategy on the query framework when the false dismissal class is very large relative to the query resultset, and investigate the performance of indexing novel classes of time series subsequences.
AB - Efficient time series similarity search is a fundamental operation for data exploration and analysis. While previous work has focused on indexing progressively larger datasets and has proposed data structures with efficient exact search algorithms, we motivate the need for approximate query methods that can be used in interactive exploration and as fast data analysis subroutines on large spatiotemporal datasets. We formulate a simple approximate range query problem for time series data, and propose a method that aims to quickly access a small number of high quality results of the exact search resultset.We propose an evaluation strategy on the query framework when the false dismissal class is very large relative to the query resultset, and investigate the performance of indexing novel classes of time series subsequences.
UR - http://www.scopus.com/inward/record.url?scp=84873205314&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84873205314&partnerID=8YFLogxK
U2 - 10.1109/ICDMW.2012.27
DO - 10.1109/ICDMW.2012.27
M3 - Conference contribution
AN - SCOPUS:84873205314
SN - 9780769549255
T3 - Proceedings - 12th IEEE International Conference on Data Mining Workshops, ICDMW 2012
SP - 773
EP - 780
BT - Proceedings - 12th IEEE International Conference on Data Mining Workshops, ICDMW 2012
T2 - 12th IEEE International Conference on Data Mining Workshops, ICDMW 2012
Y2 - 10 December 2012 through 10 December 2012
ER -