| Title | Natural Language Processing Technique for Generation of SQL Queries Dynamically |
| Publication Type | Conference Paper |
| Year of Publication | 2021 |
| Authors | Sanyal, Hrithik, Shukla, Sagar, Agrawal, Rajneesh |
| Conference Name | 2021 6th International Conference for Convergence in Technology (I2CT) |
| Keywords | Complexity theory, convergence, Databases, English Text, Human Behavior, Lexical Analysis, natural language processing, Optimization, parsing, pubcrawl, resilience, Resiliency, Scalability, Standards, Structured Query Language |
| Abstract | Natural Language Processing is being used in every field of human to machine interaction. Database queries although have a confined set of instructions, but still found to be complex and dedicated human resources are required to write, test, optimize and execute structured query language statements. This makes it difficult, time-consuming and many a time inaccurate too. Such difficulties can be overcome if the queries are formed dynamically with standard procedures. In this work, parsing, lexical analysis, synonym detection and formation processes of the natural language processing are being proposed to be used for dynamically generating SQL queries and optimization of them for fast processing with high accuracy. NLP parsing of the user inputted text for retrieving, creation and insertion of data are being proposed to be created dynamically from English text inputs. This will help users of the system to generate reports from the data as per the requirement without the complexities of SQL. The proposed system will not only generate queries dynamically but will also provide high accuracy and performance. |
| DOI | 10.1109/I2CT51068.2021.9418091 |
| Citation Key | sanyal_natural_2021 |
Natural Language Processing Technique for Generation of SQL Queries Dynamically