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Database Traversal to Support Search Enhance Technique using SQL

Authors(4) :-Sivakumar K, Sriram U, Yasar Arafath S, Bhanu Priya

A search-as-you-type system computes answers on-the-fly as a user sorts during a keyword question character by character. We have a tendency to support search-as-you-type on information residing during relative software. We have a tendency to target the way to support this kind of search mistreatment the native information language, SQL. A main challenge is the way to leverage existing information functionalities to satisfy the high performance demand to realize associate interactive speed. We have a tendency to use auxiliary indexes hold on as tables to extend search performance. We have a tendency to gift solutions for each single-keyword queries and multi keyword queries, and develop novel techniques for fuzzy search mistreatment SQL by permitting mismatches between question keywords and answers. We gift techniques to answer first-N queries and discuss the way to support updates expeditiously. Experiments on massive, real information sets show that our techniques modify software systems on a trade goods pc to support search-as-you-type on tables with a lot of records.

Authors and Affiliations

Sivakumar K
Computer Science and Engineering, Dhanalakshmi College of Engineering, Chennai, Tamilnadu, India
Sriram U
Computer Science and Engineering, Dhanalakshmi College of Engineering, Chennai, Tamilnadu, India
Yasar Arafath S
Computer Science and Engineering, Dhanalakshmi College of Engineering, Chennai, Tamilnadu, India
Bhanu Priya
Computer Science and Engineering, Dhanalakshmi College of Engineering, Chennai, Tamilnadu, India

Search-as-you-type, databases, SQL, fuzzy search

[1] S. Agrawal, K. Chakrabarti, S. Chaudhuri, and V. Ganti, “Scalable Ad-Hoc Entity Extraction from Text Collections,” Proc. VLDB Endowment, vol. 1, no. 1, pp. 945-957, 2008.

[2] S. Agrawal, S. Chaudhuri, and G. Das, “DBXplorer: A System for Keywordth-Based Search over Relational Data Bases,” Proc. 18 Int’l Conf. Data Eng. (ICDE ’02), pp. 5-16, 2002.

[3] A. Arasu, V. Ganti, and R. Kaushik, “Efficient Exact Set-Similarity Joins,” Proc. 32nd Int’l Conf. Very Large Data Bases (VLDB ’06 pp. 918-929, 2006.

[4] H. Bast, A. Chitea, F.M. Suchanek, and I. Weber, “ESTER: Efficient Search on Text, Entities, and Relations,” Proc. 30th Ann. Int’l ACM SIGIR Conf. Research and Development in Information Retrieval ( SIGIR ’07), pp. 671-678, 2007.

[5] H. Bast and I. Weber, “Type Less, Find More: Fast Autocompletion Search with a Succinct Index,” Proc. 29th Ann. Int’l ACM SIGIR Conf. Research and Development in Information Retrieval(SIGIR ’06), pp. 364-371, 2006.

[6] H. Bast and I. Weber, “The Complete Search Engine: Interactive, Efficient, and Towards IR & DB Integration,” Proc. Conf. Innovative Data Systems Research (CIDR), pp. 88 -95, 2007.

[7] R.J. Bayardo, Y. Ma, and R. Srikant, “Scaling up all Pairs Similarity Search,” Proc. 16th Int’l Conf. World Wide Web (WWW ’07), pp. 131 -140, 2007.

[8] G. Bhalotia, A. Hulgeri, C. Nakhe, S. Chakrabarti, and S.Sudarshan, “Keyword Searching and Browsing in DataBases Using Banks,” Proc. 18th Int’l Conf. Data Eng. (ICDE ’02), p p. 431-440, 2002.

[9] K. Chakrabarti, S. Chaudhuri, V. Ganti, and D. Xin, “An Efficient Filter for Approximate Membership Checking,” Proc. ACM SIGMOD Int’l Conf. Management of Data (SIGMOD ’08), pp. 805-818, 2008 .

[10] S. Chaudhuri, K. Ganjam, V. Ganti, R. Kapoor, V. Narasayya, and T. Vassilakis, “Data Cleaning in Microsoft SQL Server 2005,” Proc.ACM SIGMOD Int’l Conf. Management of Data (SIGMOD ’05),pp. 918-920, 2005.

[11] S. Chaudhuri, K. Ganjam, V. Ganti, and R. Motwani, “Robust and Efficient Fuzzy Match for Online Data Cleaning,” Proc. ACM SIGMOD Int’l Conf. Management of Data (SIGMOD ’03), pp. 313- 324, 2003.

[12] S. Chaudhuri, V. Ganti, and R. Kaushik, “A Primitive Operator for Similarity Joins in Data Cleaning,” Proc. 22nd Int’l Conf. Data Eng. (ICDE ’06), pp. 5-16, 2006.

[13] S. Chaudhuri, V. Ganti, and R. Motwani, “Robust Identification of Fuzzy Duplicates,” Proc. 21st Int’l Conf. Data Eng. (ICDE), pp. 865- 876, 2005.

[14] S. Chaudhuri and R. Kaushik, “Extending Autocompletion to Tolerate Errors,” Proc. 35th ACM SIGMOD Int’l Conf. Management of Data (SIGMOD ’09), pp. 433-439, 2009.

[15] B. B. Dalvi, M. Kshirsagar, and S. Sudarshan, “Keyword Search on External Memory Data Graphs,” Proc. VLDB Endowment, vol. 1, no. 1, pp. 1189-1204, 2008.

[16] B. Ding, J.X. Yu, S. Wang, L. Qin, X. Zhang, and X. Lin, “Finding Top-K Min-Cost Connected Trees in Data Bases,” Proc. IEEE 23rd Int’l Conf. Data Eng. (ICDE ’07), pp. 836-845, 2007.

[17] L. Gravano, P.G. Ipeirotis, H.V. Jagadish, N. Koudas, S. Muthukrishnan, and D. Srivastava, “Approximate String Joins in a Data Base (Almost) for Free,” Proc. 27th Int’l Conf. Very Large Data Bases (VLDB ’01), pp. 491-500, 2001.

[18] M. Hadjieleftheriou, A. Chandel, N. Koudas, and D. Srivastava, “Fast Indexes and Algorithms for Set Similarity Selection Queries,” Proc. IEEE 24th Int’l Conf. Data Eng. (ICDE ’08), pp. 267-276, 2008.

[19] M. Hadjieleftheriou, N. Koudas, and D. Srivastava, “Incremental Maintenance of Length Normalized Indexes for Approximate String Matching,” Proc. 35th ACM SIGMOD Int’l Conf. Management of Data (SIGMOD ’09), pp. 429-440, 2009.

[20] M. Hadjieleftheriou, X. Yu, N. Koudas, and D. Srivastava, “Hashed Samples: Selectivity Estimators for Set Similarity Selection Queries,” Proc. VLDB Endowment, vol. 1, no. 1, pp. 201-212, 2008.

Publication Details

Published in : Volume 1 | Issue 2 | March-April 2015
Date of Publication : 2015-04-25
License: This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 200-204
Manuscript Number : IJSRSET152276
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

Sivakumar K, Sriram U, Yasar Arafath S, Bhanu Priya, " Database Traversal to Support Search Enhance Technique using SQL , International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 1, Issue 2, pp.200-204, March-April.2015
URL : http://ijsrset.com/IJSRSET152276

Manuscript Number : IJSRSET152276

Database Traversal to Support Search Enhance Technique using SQL