Integrating flexibility and fuzziness into a question driven query model

The wide usage of relational databases motivated researchers to develop more user friendly interfaces which would allow a larger population of users to access databases. Such interfaces range from visual to natural language based. This paper contributes a question driven query model which falls under the natural language based category. The proposed model supports fuzziness where every user is given the freedom to define his/her own understanding of fuzzy terms. The developed system captures the fuzzy understanding of each user to utilize it while deciding on the result to be communicated back as answer to a raised question. Data mining techniques are employed to guide users in defining their fuzzy understanding. The developed model is intended to help users to retrieve data from a relational database without expecting them to know SQL. The system handles different types of questions, including (1) simple questions, (2) complex questions with inner joins and where conditions, (3) questions that involve usage of aggregate functions (e.g., min, max, etc.), and (4) questions with fuzzy terms. The reported test results demonstrate the effectiveness and applicability of the developed system in handling various types of questions raised by a heterogeneous set of users ranging from professional to naive.