Human like Query Tool: Non-Stationary Fuzzy Set Approach Adel A. Sabour 1,** , Ahmed M. Gadallah 2, * and Hesham Hefny 3, * * Computer Science Department, Institute of Statistical Studies and Research, Cairo University, Egypt. ** Information Systems Department, Institute of Statistical Studies and Research, Cairo Uni- versity, Egypt. 1 adelsabour@gmail.com, 2 ahmgad10@yahoo.com and 3 hehefny@ieee.com Abstract Abstract. Generally, users often have vague or imprecise ideas when searching databases and thus may not know how to use traditional structured query lan- guage to precisely formulate queries that lead to satisfactory answers. Also, the user searching criteria may depend on the current state of the data stored in the searched database. This paper presents a more flexible fuzzy set-based approach for human-like querying of relational databases. Such approach supports queries that can use both of stationary fuzzy sets with fixed definition and non-stationary fuzzy sets or data-sensitive fuzzy sets with dynamic definitions. Based on fuzzy set theory and data-sensitive fuzzy sets, this paper proposes a fuzzy query ap- proach supporting data-sensitive fuzzy queries in which the definition of a fuzzy set can be dynamic and depend on some data in the current database state. Also, the proposed approach allows fuzzy joining of database relations. Such fuzzy join makes a query statement much closed to human querying behaviors. On the other hand, many other query structures like nested, complex and correlated fuzzy que- ries are supported by the proposed approach. Keywords: Fuzzy Joins, Non-Stationary Fuzzy Set, Data-Sensitive Fuzzy Set, Information Retrieval, Fuzzy Logic, Fuzzy Sets, Fuzzy SQL. 1 Introduction Structured Query Language (SQL) is a very essential tool for querying relational data- bases. It manipulates and retrieves data which is crisp and precise by nature. In contrary, it is unable to respond to human-like queries which are uncertain, imprecise and vague in nature. The Fuzzy Queries based on stored procedures to provides many different methods of combining data sets. While care must be taken to avoid inefficient pro- cessing, this process allows you to combine data sets in ways that would be difficult or even impossible using other methods. The following SQL query illustrates difference between the structured query languages (SQL) and Fuzzy queries: Query(1) SELECT student_name, height, weight FROM student WHERE height> X and weight< Y;