Abstract:
Encephalon is a trainable natural language interface for databases based on template matching to convert the human language into an appropriate SQL query for relational database system. The reason for building natural language interfaces for systems as opposed to formal language systems e.g SQL is to make interaction for naive users easier by having just a little knowledge about the system. Such front ends relieve the users of the need to know the structure of the database and offer a much more convenient and flexible interaction. This interface will act as an abstract middleware between user and database systems. Previously many interfaces like these have been developed but analysis shows that people are unwilling to trade reliable and predictable interfaces with intelligent and unreliable ones so while designing the system, four critical factors from clients perspective extensibility, portability, domain independence, and enhanced sense modality were kept under consideration and to increase the percentage of accuracy a new idea of rules and templates is introduced.
