IJSRSET calls volunteers interested to contribute towards the scientific development in the field of Science, Engineering and Technology

Home > IJSRSET152276                                                     


Database Traversal to Support Search Enhance Technique using SQL

Authors(4):

Sivakumar K, Sriram U, Yasar Arafath S, Bhanu Priya
  • Abstract
  • Authors
  • Keywords
  • References
  • Details
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.

Sivakumar K, Sriram U, Yasar Arafath S, Bhanu Priya

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 Print ISSN Online ISSN
2015-04-25 2395-1990 2394-4099
Page(s) Manuscript Number   Publisher
200-204 IJSRSET152276   Technoscience Academy

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.php