| Title | IQS-intelligent querying system using natural language processing |
| Publication Type | Conference Paper |
| Year of Publication | 2017 |
| Authors | Gupta, P., Goswami, A., Koul, S., Sartape, K. |
| Conference Name | 2017 International conference of Electronics, Communication and Aerospace Technology (ICECA) |
| Keywords | data mining, Data Warehousing, Databases, Generators, Human Behavior, MR Generator, natural language processing, NLIDB, pubcrawl, Query Generator, Resiliency, Scalability, Semantic Builder, Semantics, SQL, Structured Query Language |
| Abstract | Modern databases contain an enormous amount of information stored in a structured format. This information is processed to acquire knowledge. However, the process of information extraction from a Database System is cumbersome for non-expert users as it requires an extensive knowledge of DBMS languages. Therefore, an inevitable need arises to bridge the gap between user requirements and the provision of a simple information retrieval system whereby the role of a specialized Database Administrator is annulled. In this paper, we propose a methodology for building an Intelligent Querying System (IQS) by which a user can fire queries in his own (natural) language. The system first parses the input sentences and then generates SQL queries from the natural language expressions of the input. These queries are in turn mapped with the desired information to generate the required output. Hence, it makes the information retrieval process simple, effective and reliable. |
| DOI | 10.1109/ICECA.2017.8212846 |
| Citation Key | gupta_iqs-intelligent_2017 |
IQS-intelligent querying system using natural language processing