**5. Case-based reasoning**

#### **5.1 Principle**

Case-based reasoning (CBR) is the process of solving new problems based on the solutions of similar past problems [17], [18]. A new problem is solved by finding a similar past case, and reusing it in the new problem situation. The knowledge and reasoning process used by an expert to solve the problem is not recorded, but is implicit in the solution.

To solve a current problem: the problem is matched against the cases in the case base, and similar cases are retrieved. The retrieved cases are used to suggest a solution which is reused and tested for success. If necessary, the solution is then revised. Finally the current problem and the final solution are retained as part of a new case.

All case-based reasoning methods have in common the following process:


Retrieving a case starts with a (possibly partial) problem description and ends when a best matching case has been found. The subtasks comprise:


The finance law is a law of the land and provides for and authorizes all State revenue and expenditure for the upcoming fiscal year. It is founded on a budgetary ontology presented

Input ontology

Union of terminological ontologies

Case-based reasoning (CBR) is the process of solving new problems based on the solutions of similar past problems [17], [18]. A new problem is solved by finding a similar past case, and reusing it in the new problem situation. The knowledge and reasoning process used by

Output ontology

To solve a current problem: the problem is matched against the cases in the case base, and similar cases are retrieved. The retrieved cases are used to suggest a solution which is reused and tested for success. If necessary, the solution is then revised. Finally the current

retrieve the most similar case (or cases) comparing the case to the library of past cases;

Retrieving a case starts with a (possibly partial) problem description and ends when a best

matching the case and returning a set of sufficiently similar cases (given a similarity

an expert to solve the problem is not recorded, but is implicit in the solution.

All case-based reasoning methods have in common the following process:

problem and the final solution are retained as part of a new case.

 reuse the retrieved case to try to solve the current problem; revise and adapt the proposed solution if necessary; retain the final solution as part of a new case.

matching case has been found. The subtasks comprise: identifying a set of relevant problem descriptors;

selecting the best case from the set of cases returned.

threshold of some kind); and

**Budgetary ontology** 

Fig. 4. Budgetary ontology

**5.1 Principle** 

**5. Case-based reasoning** 

in figure….

Some systems retrieve cases based largely on superficial syntactic similarities among problem descriptors, while advanced systems use semantic similarities.

Reusing the retrieved case solution in the context of the new case focuses on: identifying the differences between the retrieved and the current case; and identifying the part of a retrieved case which can be transferred to the new case. Generally the solution of the retrieved case is transferred to the new case directly as its solution case.

Revising the case solution generated by the reuse process is necessary when the solution proves incorrect. This provides an opportunity to learn from failure.

Retaining the case is the process of incorporating whatever is useful from the new case into the case library. This involves deciding what information to retain and in what form to retain it; how to index the case for future retrieval; and integrating the new case into the case library.

### **5.2 Learning in Case-Based Reasoning**

A very important feature of case-based reasoning is its coupling to learning. CBR is an approach to incremental, sustained learning, since a new experience is retained each time a problem has been solved, making it immediately available for future problems. Learning in CBR occurs as a natural by-product of problem solving. When a problem is successfully solved, the experience is retained in order to solve similar problems in the future. When an attempt to solve a problem fails, the reason for the failure is identified and remembered in order to avoid the same mistake in the future.

Case-based reasoning allows learning from experience, since it is usually easier to learn by retaining a concrete problem solving experience than to generalize from it.
