NatalieDB: Natural Language Interface for Databases
At a glance
Due to the success of relational databases, new trends in big
data technologies and Open Data, the query languages SQL and SPARQL
are the most-widely used techniques to access databases. Even
though SQL and SPARQL are very powerful, significant technical
knowledge and training is required. Today, business users and
scientists are restricted in their ability to query databases by
using preconceived query patterns. As a result, a wide range of
users are basically not capable of accessing vast amounts of data
The goal of this project is to develop a natural language interface for databases, which allows non-technical users to query all the data sets a company or a research institution has collected and curated in a data warehouse or knowledge base. The key idea is to automatically translate a natural language query to the query languages SQL and SPARQL depending on the underlying database. Our system will enable users without prior training to perform powerful queries, thus truly leveraging the data – a crucial differentiator in our data-driven age.
Affolter, Katrin; Stockinger, Kurt; Bernstein, Abraham,
The VLDB journal.
Available from: https://doi.org/10.21256/zhaw-18074