Call for Paper - August 2022 Edition
IJCA solicits original research papers for the August 2022 Edition. Last date of manuscript submission is July 20, 2022. Read More

Structured Query Language (SQL) Answering Model for User Queries based on Intuitionistic Fuzzy Logic

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2015
Ashit Kumar Dutta

Ashit Kumar Dutta. Article: Structured Query Language (SQL) Answering Model for User Queries based on Intuitionistic Fuzzy Logic. International Journal of Computer Applications 129(1):32-36, November 2015. Published by Foundation of Computer Science (FCS), NY, USA. BibTeX

	author = {Ashit Kumar Dutta},
	title = {Article: Structured Query Language (SQL) Answering Model for User Queries based on Intuitionistic Fuzzy Logic},
	journal = {International Journal of Computer Applications},
	year = {2015},
	volume = {129},
	number = {1},
	pages = {32-36},
	month = {November},
	note = {Published by Foundation of Computer Science (FCS), NY, USA}


Instuitionistic fuzzy logic is widely accepted method to analyse the imprecise and vague data. There are number of database management systems (DBMS) are available to facilitate the users to store and organize the data for the future purpose. DBMS lacks to understand the user queries in distributed environment. Sql is a popular querying language to fetch data depend upon the user queries. The structure of the sql query is designed for precise queries from the user but it will return error for vague queries. As the business extends from one part of the world to the other language should be a barrier for the non - English speakers. The research is to find the solution for the problems exist in the sql to translate the user queries. The proposed model will answer all kind of user queries and tries solve the vagueness problem using fuzzy logic.


  1. Marlene Goncalves and Leonid Tineo, “ SQLf3: An extension of SQLF with SQL3 features”, IEEE International fuzzy systems conference, PP. 477 – 480.
  2. Yanhui Lv, Z.M.Ma and Fu zhang, “ A fuzzy ontology generation framework from relational schema”, Fifth international conference on fuzzy systems and knowledge discovery, PP. 435 – 439.
  3. Shyi- Ming and Woei – Tzy Jong,” Fuzzy query translation for relational database systems”, IEEE transactions on systems, man and cybernetics – part B: Cybernetics, Vol. 27, No.4, August 1997.
  4. Ke Xiao – Hua, “An automatic translation evaluation system based on semantic similairities and fuzzy neartude”, 2009 International conference on environmental science and information application technology, pp. 583 – 586.
  5. Zheng Qin and Qing – Chen Shang, “ Eliminate people’s expressive preference in the mood of fuzzy linguistics”, Krakow, Poland, May 25 – 27, 2008. pp.1021 – 1026.
  6. Amit Garg and Rahul Rishi, “ Querying capability enhancement in database using fuzzy logic”, Global journal of computer science and technology, Vol.12,Iss.6, 2012.
  7. Ulli waltinger, Dan Tecuci, Mihaela Olteanu, Vlad Mocanu and Sean Sullivan, “ USI Answers: Natural Language Question Answering over (Semi-) Structured Industry Data”, Proceedings of the Twenty – Fifth applications of artificial intelligence conference, pp.1471 – 1478.
  8. Abhijeet R.Raipurkar and G.R. Bamnote,” Fuzzy logic based query optimization in distributed database”, International journal of innovative research in computer and communication engineering”, Vol.1, Iss.2, April 2013. pp. 422 – 426.
  9. C.T.Yu, K.C.Guh, W.Zhang, M. Templeton, D.Brill and A.L.P. Chen, “ An integrated algorithm for distributed query processing”, IFIP Conference, Amsterdam, 1987.
  10. J.K.T. Huang, “ Query optimization in Distributed databases”, Conference of information and decision systems, MIT.1982.
  11. M.S.Chen and P.S.Yu, “ A graph theoretical approach to determine a join reducer sequences in Distributed query processing”, Vol.5:3, pp.534 – 542, 1993.
  12. Jyothsna Cherapanamjeri, Lavanya Lingareddy, Himabindu. K, “ Keyword based question answering system in natural language interface to database”, IJARCET, Vol.3, Iss.12, December 2014.
  13. N. Ramireddy, Sivaji Bandyopadhya, “ Dialog based question answering system in Telugu,” EACL workshopon Multilingual Question Answering., 2006.
  14. Dhanshri patil, Abhijeet chopade, Pankaj bhambare, sanket deshmukh and aniket tetame,” A proposed automatic answering system for natural language questions”, IJEC, Vol.4,Iss.4, April 2015. Pp. 11310- 11312.
  15. S.R.Balasundaram and B.Ramadoss, “ SMS for question – answering in the m-learning scenario, journal of computer science 3(2), pp. 119 – 121, 2007


Answering system, Fuzzifier, Translator