Computer-based information technologies have been extensively used to help many organizations, private companies, and academic and education institutions manage their processes and information systems hereby become their nervous centre. The explosion of massive data sets created by businesses, science and governments necessitates intelligent and more powerful computing paradigms so that users can benefit from this data. Therefore most new-generation database applications demand intelligent information management to enhance efficient interactions between database and the users. Database systems support only a Boolean query model. A selection query on SQL database returns all those tuples that satisfy the conditions in the query.
But lately, there is an overwhelming need for non-expert users to query relational databases in their natural language using linguistic variables and terms instead of working with the values of the attributes. As a result, intelligent databases have emerged, which provides expanded and more flexible options for manipulating queries. In this paper, we propose an intelligent layer for database which is responsible for manipulating flexible queries. Initially, the flexible queries from users in their natural language are submitted to intelligent layer and this layer converts the amorphous query into a structured SQL query. The shaped query is executed and the results are presented to the user. Afterwards, on the basis of results, feedback and the acceptance or rejection of the results are requested from the user. It enables the design of a knowledge based self learning system based the values obtained from user, which will aid the selection of appropriate SQL query, when a same flexible query is issued in the future. The experimental results demonstrate the effectiveness of the proposed intelligent database system.
