Data Extraction from Structured Databases using Keyword-based Queries

Relational databases are used to store a large quantity of data scattered around the world. However, users face difficulties in accessing such data for lack of a more natural way of specifying queries. Techniques that use natural language words to search different information sources on the Web are now very common, but they cannot be employed to search relational databases. This work proposes a method that allows user to submit keyword-based queries, which are then semantically analysed and enriched before being mapped for the database language. By analysing keyword-based queries, the method considers different factors, e.g. the proximity between keywords, query segmentation, and the use of aggregate functions.