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

A Novel Document Retrieval Scheme using Relational Keyword Search System

by Neelam S. Pokale, Jyoti R. Yemul
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 122 - Number 19
Year of Publication: 2015
Authors: Neelam S. Pokale, Jyoti R. Yemul
10.5120/21808-5127

Neelam S. Pokale, Jyoti R. Yemul . A Novel Document Retrieval Scheme using Relational Keyword Search System. International Journal of Computer Applications. 122, 19 ( July 2015), 17-20. DOI=10.5120/21808-5127

@article{ 10.5120/21808-5127,
author = { Neelam S. Pokale, Jyoti R. Yemul },
title = { A Novel Document Retrieval Scheme using Relational Keyword Search System },
journal = { International Journal of Computer Applications },
issue_date = { July 2015 },
volume = { 122 },
number = { 19 },
month = { July },
year = { 2015 },
issn = { 0975-8887 },
pages = { 17-20 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume122/number19/21808-5127/ },
doi = { 10.5120/21808-5127 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:10:57.941535+05:30
%A Neelam S. Pokale
%A Jyoti R. Yemul
%T A Novel Document Retrieval Scheme using Relational Keyword Search System
%J International Journal of Computer Applications
%@ 0975-8887
%V 122
%N 19
%P 17-20
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Keyword search pattern to relational data is the most important and the highlighted area within a search and information retrieval community. For the system evaluations, there are many approaches followed but there is a lack of standardization. The result of lack of standardization affects performance of the system. The number of queries completed successfully in a query workload is performance wise not showing good results for relational keyword search system. The solution to above problem is to develop a novel technique for efficient document retrieval using relational keyword search system. The new system is developed to manage uploading and downloading of data from disk to improve performance and reuse dataset and query workload to provide greater consistency of results. A scalable document retrieval improves the search performance in terms of execution time, cost efficiency and apply ranking to the document depends on query weight. The new system gives 30% to 40% reduction in the search execution time compared to the existing system.

References
  1. J. Coffman and A. C. Weaver ,"An Empirical Performance Evaluation of Relational Keyword Search Systems", IEEE Transactions on Knowledge and Data Engineering,Vol. 26 , 2014.
  2. R. Vernica and C. Li, "Efficient Top-k Algorithms for Fuzzy Search in String Collections" , ACM, KEYS'09, June 28, 2009.
  3. J. Coffman and A. C. Weaver, "A Framework for Evaluating Database Keyword Search Strategies," in Proceedings of the 19th ACM International Conference on Information and Knowledge Management,ser. CIKM '10, 2010, pp. 729–738. [Online]. Available: http://doi. acm. org/10. 1145/1871437. 1871531.
  4. A. Baid, I. Rae, J. Li, A. Doan, and J. Naughton, "Toward Scalable Keyword Search over Relational Data," Proceedings of the VLDB Endowment, vol. 3, 2010 ,pp. 140–149.
  5. G. Bhalotia, A. Hulgeri, C. Nakhe, S. Chakrabarti, and S. Sudarshan,"Keyword Searching and Browsing in Databases using BANKS," in Proceedings of the 18th International Conference on Data Engineering,ser. ICDE '02, 2002, pp. 431–440.
  6. Y. Chen, W. Wang, Z. Liu, and X. Lin, "Keyword Search on Structured and Semi-Structured Data," in Proceedings of the 35th SIGMOD International Conference on Management of Data, ser. SIGMOD '09, 2009, pp. 1005–1010.
  7. B. Ding, J. X. Yu, S. Wang, L. Qin, X. Zhang, and X. Lin, "Finding Topk Min-Cost Connected Trees in Databases," in ICDE '07: Proceedings of the 23rd International Conference on Data Engineering, 2007,pp. 836–845.
  8. K. Golenberg, B. Kimelfeld, and Y. Sagiv, "Keyword Proximity Search in Complex Data Graphs," in Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, ser. SIGMOD '08, 2008, pp. 927–940.
  9. D. Chenthati , H. Mohanty, A. Damodaram, "A Scalable Relational Database Approach for WebService Matchmaking", DOI 10. 5013/IJSSST, 2003.
  10. L. J. Chen, Y. Papakonstantinou, "Supporting Top-K Keyword Search in XML Databases", research was supported by NSF IIS award 0713672.
  11. S. Bergamaschi, E. Domnori, R. Emilia, F. Guerra, R. T. Lado, and Y Velegrakis, "Keyword Search over Relational Databases: A Metadata Approach", SIGMOD'11, 2011.
Index Terms

Computer Science
Information Sciences

Keywords

Relational Keyword Search System Schema Based Systems Relational Database