5th GENERATION DBMS-ADBMS (ARTIFICIAL DBMS)
DBMS is nothing but collection of inter-related data and set of software to arrange and manage that data. DBMS replaces earlier MIS (management information systems). In MIS only limited operations is possible, but in DBMS a wide range of operations and high-level programming constructs can be implemented easily. DBMS provides high user-interface, security and integrity when compared to MIS.
One of the missing features in DBMS is proper decision making. Although we use queries to some extent, in complicated and in vast data maintenance decision making is a serious problem.
One of the best approaches to solve this problem is by introducing an expert system to solve this problem. A database cannot think by itself. By using knowledge based concept we make DBMS to think on its own.
Expert systems use the properties of artificial intelligence, knowledge engineering and fuzzy logic. One of the implementation strategy used in artificial intelligence is fuzzy logic. Fuzzy logic is nothing by approximation of values. Range of the fuzzy logic is between o and 1.
TRADITIONAL DBMS | ARTIFICIAL DBMS |
IF(data=x1, x2, x3, x4) then...true(1) ELSE false(0) | IF (data=x1, x2, x3, x4) then true(1) ELSE IF (data=x1, x2,x3 || x3, x4, x1 || x2, x3, x4) then true(0.75)=true(1) ELSE IF (data=x1, x2 || x2, x3 || x4, x1 || x2, x4 || x1, x3) then false(0.25)=false(0) ELSE IF (data=x1 || x2 || x3 || x4) then false(0) |
IMPLEMENTATION:
This fuzzy logic will be implemented by using an expert system.so one must create an expert system, based on user's rules and need. This expert system is then placed above DBMS and hence it will acts as a decision-maker. The DBMS will return output based on input query, without any knowledge, but the expert system which lies above DBMS will take proper decision and provide processed and knowledge data called ARTIFICIALLY PROCESSED DATA.
Since the direct retrieval of data may come directly from management systems. The data which needs decisions will enter into expert system and hence provides the knowledge output.
By this way the decision making problem is rectified. Hence it uses knowledge based concept (DBMS WITH BRAIN) and so it is called ARTIFICIAL DBMS OR ADBMS.
ADVANTAGES:
* Proper decision making will be achieved for real life applications.
* The protocols given in the expert system will be changed easily.
DISADVANTAGES:
* Interfacing DBMS and EXPERT SYSTEM will be a difficult problem.
* Special Embedded SQL's are needed.
KNOWLEDGED OUTPUT
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INPUT QUERY
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KNOWLEDGE-LESS
OUTPUT
