Evaluation of natural language software interfaces to databases

Abstract

Relational databases are still important in modern times due to their many advantages, such as ease of interaction, simplicity and data integrity. In this regard, structured query language (SQL) and technical knowledge about database schemas are the basic building blocks for retrieving information from relational databases. Generally, non-expert users cannot skillfully write technical queries on the target database. To this end, many database natural language interfaces (NLIDB) have been developed to greatly facilitate users. However, each system provides a different interface for new users, so beginners can use different interactive modes to enter keyword-based queries. For users, migrating from one NLIDB to another is a difficult problem. To solve this problem, NLIDB needs to be standardized so that novice users can easily enter queries in their native language. This paper proposes a standardized interface for NLIDB, which considers the three quality parameters of interface, query comparison and performance. Based on these parameters, we developed a standardized interface called the keyword-based frequent search engine (FKBSE). The DBLP data set has been evaluated experimentally. The results show the effectiveness of FKBSE compared with parallel systems in terms of quality parameters.