We apologize for a recent technical issue with our email system, which temporarily affected account activations. Accounts have now been activated. Authors may proceed with paper submissions. PhDFocusTM
CFP last date
20 December 2024
Reseach Article

Survey on Comparative Analysis of Queries over Historical Time Series

by Suganya Devi R, D Manjula
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 106 - Number 6
Year of Publication: 2014
Authors: Suganya Devi R, D Manjula
10.5120/18527-9722

Suganya Devi R, D Manjula . Survey on Comparative Analysis of Queries over Historical Time Series. International Journal of Computer Applications. 106, 6 ( November 2014), 34-37. DOI=10.5120/18527-9722

@article{ 10.5120/18527-9722,
author = { Suganya Devi R, D Manjula },
title = { Survey on Comparative Analysis of Queries over Historical Time Series },
journal = { International Journal of Computer Applications },
issue_date = { November 2014 },
volume = { 106 },
number = { 6 },
month = { November },
year = { 2014 },
issn = { 0975-8887 },
pages = { 34-37 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume106/number6/18527-9722/ },
doi = { 10.5120/18527-9722 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:38:43.429221+05:30
%A Suganya Devi R
%A D Manjula
%T Survey on Comparative Analysis of Queries over Historical Time Series
%J International Journal of Computer Applications
%@ 0975-8887
%V 106
%N 6
%P 34-37
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Most search engine queries are time dependent in retrieving the results. Time series analysis plays an important role in predicting the status of the query, at every time stamp to retrieve efficiently. Studies have shown that different approaches are used for different queries over time series. Generally they are broadly classified into two types of queries; exact match queries and pattern existence queries. Some applications need the existence of any one of the queries and while others may need both. Numerous methods have been employed to answer both the queries. Analyzing all these methods, the paper tries to survey some improved methods and have experimentally tested their effectiveness. Besides, it also studies some future directions on historical time series queries.

References
  1. Hao Wang, Yilun Cai, Yin Yang, Shiming Zhang, and Nikos Mamoulis, "Durable Queries over Historical Time Series," IEEE Computer Society 2014
  2. V. Athitsos, P. Papapetrou, M. Potamias, G. Kollios, and D. Gunopulos, "Approximate Embedding-Based Subsequence Matching of Time Series," Proc. ACM SIGMOD Int'l Conf. Management of Data, 2008.
  3. Q. Chen, L. Chen, X. Lian, Y. Liu, and J. X. Yu, "Indexable PLA for Efficient Similarity Search," Proc. 33rd Int'l Conf. Very Large Data Bases (VLDB), 2007.
  4. C. Faloutsos, M. Ranganathan, and Y. Manolopoulos, "Fast Subsequence Matching in Time-Series Databases," Proc. ACM SIGMOD Int'l Conf. Management of Data, 1994.
  5. R. H. Guting, T. Behr, and J. Xu, "Efficient K-Nearest Neighbor Search on Moving Object Trajectories," VLDB J. , vol. 19, pp. 687- 714, 2010.
  6. A. Guttman, "R-Trees: A Dynamic Index Structure for Spatial Searching," Proc. ACM SIGMOD Int'l Conf. Management of Data, 1984.
  7. I. F. Ilyas, G. Beskales, and M. A. Soliman, "A Survey of Top-K Query Processing Techniques in Relational Database Systems," ACM Computing Surveys, vol. 40, no. 4, pp. 11:1-11:58, 2008.
  8. J. Jestes, J. M. Phillips, F. Li, and M. Tang, "Ranking Large Temporal Data," Proc. VLDB Endowment, vol. 5, pp. 1412-1423, 2012.
  9. B. Jiang and J. Pei, "Online Interval Skyline Queries on Time Series," Proc. IEEE Int'l Conf. Data Eng. (ICDE), 2009.
  10. E. Keogh, "Exact Indexing of Dynamic Time Warping," Proc. 28th Int'l Conf. Very Large Data Bases (VLDB), 2002.
  11. M. L. Lee, W. Hsu, L. Li, and W. H. Tok, "Consistent Top-K Queries over Time," Proc. 14th Int'l Conf. Database Systems for Advanced Applications (DASFAA), 2009.
  12. F. Li, K. Yi, and W. Le, "Top-k Queries on Temporal Data," VLDB J. , vol. 19, pp. 715-733, 2010.
  13. L. H. U, N. Mamoulis, K. Berberich, and S. Bedathur, "Durable Top-K Search in Document Archives," Proc. ACM SIGMOD Int'l Conf. Management of Data, 2010.
  14. X. Yu, K. Q. Pu, and N. Koudas, "Monitoring K-Nearest Neighbor Queries over Moving Objects," Proc. Int'l Conf. Data Eng. (ICDE), 2005.
Index Terms

Computer Science
Information Sciences

Keywords

Search engine queries survey comparative analysis and historical time series.