CFP last date
20 May 2024
Reseach Article

Efficient Proximity Search with Query Logs

by Sushilkumar N. Holambe, Bhagyashri G. Patil
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 129 - Number 5
Year of Publication: 2015
Authors: Sushilkumar N. Holambe, Bhagyashri G. Patil
10.5120/ijca2015906892

Sushilkumar N. Holambe, Bhagyashri G. Patil . Efficient Proximity Search with Query Logs. International Journal of Computer Applications. 129, 5 ( November 2015), 9-11. DOI=10.5120/ijca2015906892

@article{ 10.5120/ijca2015906892,
author = { Sushilkumar N. Holambe, Bhagyashri G. Patil },
title = { Efficient Proximity Search with Query Logs },
journal = { International Journal of Computer Applications },
issue_date = { November 2015 },
volume = { 129 },
number = { 5 },
month = { November },
year = { 2015 },
issn = { 0975-8887 },
pages = { 9-11 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume129/number5/23067-2015906892/ },
doi = { 10.5120/ijca2015906892 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:22:35.650664+05:30
%A Sushilkumar N. Holambe
%A Bhagyashri G. Patil
%T Efficient Proximity Search with Query Logs
%J International Journal of Computer Applications
%@ 0975-8887
%V 129
%N 5
%P 9-11
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In information retrieval technology there are various techniques for fetching data from resources. And that technique also contains various issues. Information retrieval techniques require advanced manipulating schemes which improves keyword search. There are many techniques have been proposed but results get down when large amount data interrupted. In this paper, have tendency to achieve efficient time and space complexities by integrating proximity information. This system improves the performance by using previous searching results. All the previous system consist basic solutions for extracting results and ranking them. Query logs consists the last searching results and use that results for next search. Fuzzy keyword search truly enhance the system usability. Existing system in databases requires to write complete keyword for searching but by using auto-complete scheme it is easy to type less and find more. In this system proper demand paging algorithm is used for finding previous results.

References
  1. Inci Cetindil, Iamshid Esmaelnezhad, Taewoo Kim, and Chen Li, “Efficient instant fuzzy search with proximity raking,” in ICDE, 2014.
  2. Centennial, J. Esmaelnezhad, C. Li, and D. Newman, “Analysis of instant search query logs,” In WebDB, 2012,pp.7-12.
  3. R. B. Miller, “Response time in man-computer conversational transactions,” in Proceedings of the December 9-11, 1968, fall joint computer conference, part I, ser. AFIPS ’68 (fall, part I). New York, NY, USA: ACM, 1968, pp. 267–277.
  4. K. Grabski and T. Scheffer, “Sentence completion,” in SIGIR, 2004, pp.433-439.
  5. A. Nandi and H.V. Jagadish, “Effective phrase prediction,” in VLDB, 2007, pp.219-230.
  6. R. Schenkel, A. Broschart, S. won Wang, M. Theo bald, and G. Welkom, “Efficient text proximity search,” in SPIRE, 2007, pp. 287-299.
  7. H. Yan, S. Shi, F. Zhang, T. Suel, and R. Wen, “Efficient term proximity search with term pair indexes,” in CIKM, 2010,pp. 1229-1238.
  8. M. Zhu, S. Shi, F. Zhang, T. Suel, and R. Wen, ”Can phrase indexing helps to non-phrase queries?, ”in CIKM, 2010, pp. 1229-1238.
  9. R. Fagin, A. Lotem, and M. Naor, “Optimal aggregation algorithm for middleware,” in PODS, 2001.
  10. F. Zhang, H. Yan, S. Shi, and R. Wen, “revisiting globally sorted indexes for efficient document retrieval,” in WSDM, 2010, pp. 371-380.
  11. M. Persin, J. Zobel, R. Sacks-Davis, “Filtered document retrieval with frequency-sorted indexes,” JASIS, val. 47, no. 10, pp. 749-764, 1996.
  12. S. Ji, G. Li, C. Li, and J. Feng, “efficient interactive fuzzy keyword search,” in WWW, 2009, pp.371-380.
Index Terms

Computer Science
Information Sciences

Keywords

Auto complete Algorithm demand paging Top-k Segmentation Term pair edit distance.