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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
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Index Terms

Computer Science
Information Sciences

Keywords

Search engine queries survey comparative analysis and historical time series.