Natural Language SQL Query Processing using Fuzzy Matching and Elimination Technique
Praveena Mydolalu Veerappa1, Ajeet Annarao Chikkamannur2
1Praveena Mydolalu Veerappa, Department of Computer Science and Engineering, Dr. Ambedkar Institute of Technology, Bangalore (Karnataka), India.
2Dr. Ajeet Annarao Chikkamannur, Department of Computer Science and Engineering, R L Jalappa Institute of Technology, Bangalore (Karnataka), India.
Manuscript received on 04 December 2019 | Revised Manuscript received on 12 December 2019 | Manuscript Published on 31 December 2019 | PP: 222-228 | Volume-9 Issue-2S December 2019 | Retrieval Number: B11321292S19/2019©BEIESP | DOI: 10.35940/ijitee.B1132.1292S19
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In Structured Query Language (SQL), complex queries are difficult to write or understand by a user, because every user is not familiar with SQL. A common user can able to retrieve the information from the query databases using natural language is considered as an important research area. To improve the communication between databases application and naive user, an enhanced application with intelligent interface are needed. A fuzzy system with matching and elimination technique is designed in this research study, where SQL queries are formed from the input given by the user through several steps like noise removal, lexicon normalization and query formation. Then, the system uses the Latent Dirichlet Allocation (LDA) to extract the keywords from the input query. Finally, matching and elimination techniques are used to find the data, which is related to the input query given by end-user. When compared with the existing SQL techniques, the proposed fuzzy method achieved 91% and 90.5% accuracy, 95% and 93% precision, and 0.10 and 0.12 error rate for both 28 and 50 queries.
Keywords: Elimination Technique, Fuzzy Matching Technique, Natural Language, Query Database, Structured Query Language.
Scope of the Article: Fuzzy Logics