Towards a theory of natural language interfaces to databases
Proceedings of the 8th international conference on Intelligent user interfaces
Building Usable Menu-Based Natural Language Interfaces To Databases
VLDB '83 Proceedings of the 9th International Conference on Very Large Data Bases
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
The Journal of Machine Learning Research
Automated creation of a forms-based database query interface
Proceedings of the VLDB Endowment
Hi-index | 0.00 |
Retrieving information from relational databases using a natural language query is a challenging task. Usually, the natural language query is transformed into its approximate SQL or formal languages. However, this requires knowledge about database structures, semantic relationships, natural language constructs and also handling ambiguities due to overlapping column names and column values. We present a machine learning based natural language search system to query databases without any knowledge of Structure Query Language (SQL) for underlying database. The proposed system - Cascaded Conditional Random Field is an extension to Conditional Random Fields, an undirected graph model. Unlike traditional Conditional Random Field models, we offer efficient labelling schemes to realize enhanced quality of search results. The system uses text indexing techniques as well as database constraint relationships to identify hidden semantic relationships present in the data. The presented system is implemented and evaluated on two real-life datasets.