FANDA: A Novel Approach to Perform Follow-up Query Analysis

Understand

Recent work on Natural Language Interfaces to Databases (NLIDB) has attracted considerable attention.

• NLIDB allow users to search databases using natural language instead of SQL-like query languages.
• While saving the users from having to learn query languages, multi-turn interaction with NLIDB usually involves multiple queries where contextual information is vital to understand the users' query intents.
• In this paper, we address a typical contextual understanding problem, termed as follow-up query analysis.