A dialogue-based NLIDB system in a schedule management domain

초록

To reduce the complexities of SQL query generation and increase the flexibilities of user interface, we propose a dialogue-based NLIDB system. The system classifies users' intentions into domain actions (pairs of a speech act and a concept sequence) using a maximum entropy model. Based on the classification results, the system fills up predefined SQL templates and generates proper SQL queries for natural language interface. In the experiment, the system showed the success rate of 83.4% for SQL generation.