A Peer Review on Natural Language Interface: Various Challenges and Scope

Abstract

A natural language interface to query databases (NLIDB) permits users to access data stored in databases by typing queries stated in some natural language. It is typical for the elements in a SQL statement to refer to specific information in the database table rather than being expressly mentioned in the natural language query. As a result, it is vital to gauge the similarity of two texts from the standpoint of semantics rather than strings because it can be challenging to deduce the proper element values purely based on the original query in this circumstance. It can be challenging for a text-to-SQL model to decide which column to utilize if the query includes numerous columns with identical semantics. First, the column representations are improved using table contents, and then, the query representation is improved using the revised column representations. As a result of the efficiency of the column contents being less than ideal, a small-scale introduction is planned. A generic module for use in nlidb systems that enables such systems to conduct queries using aggregations is presented in great detail in this survey. These methods include query-based, pattern-based, general, keyword-based, and grammar-based systems.