Knowledge Management

Case-Based Reasoning

A Case-Based Reasoning(CBR) is a process of a solving problem or finding solution by taking

previously similar problem or old experiance while adapting a suitable approach to the new to solve

current and new problem.

To store the knowledge CBR is method for building intelligent computer system out of the human

reasoning and thinking. The case used in CBR must have feature that describing a real event problem

with and outcome or solution.. Type of cases can be a rich sources of text, symbols and even

multimedia. Most of all the case should be able to justify a decision.

Figure 1: CBR Techniques

Source : Pedro Gonzalez 2011

One way on how to make the Case-Base reasoning formalize is to describe in the four main

process(figure 1) for automated computer and mathematical logic to understand different aspect of

human reasoning and thinking. There are four main process of CBR techniques are retrieve, reuse,

revise and retain. Giving an example of a case of a new Android Television(TV) software problem.

The cycle starts from a new problem is identified, for example Youtube is not able to display picture.

When a problem found The project leaders retrieve similar experience about similar situation from

the memory the new targeted problem. They will search for any similar cases such as memory, records

or system existed. From the memory, the project leaders will try to remember any cases that they have

experienced before, they may also looked from previous records or system which is still relevant for

the same problem . For example when a project leader found a new Android TV software problem. He

or she will require to know on from the problem how to do recovering, what is the frequency of the

problem, how did previous engineers solve the problem and the project leader will put the solutions

together and justifies for decision from the retrieved solution.

The project leader then will reuse such similar cases to find the best solution which can be used. They

will then compare the problem to ensure it is not duplicated, it clear and consisely the same or relevant

problem to the new problem, learn the behavior of problem to diagnose, understand who is the right

person to refer to and how does the previous problem solved. All the retrieved solution needed to fit

the new problem situation. For example the expert has found similar problem which Duomi music

player made a could not be displayed which have been solve to find solution on where to do solution

mapping and debugging of the problem.

After reuse steps, revise will take the new solution which found from Youtube cannot display

problem then to be tested and simulate. This is to find out whether the solution works or it may result

to lead to other problem or undesired effect and whether there is need of revise. The result from the

undesired effect cause the package release of a new application to be delayed. It can also be revise to

the current or previous package release to be used.

After solution found and successfully implemented to solve the problem, the expert will retain which

stores the experience in his/her memory, or other type of memory such as system or documentation.

For example the solution of Youtube cannot be display the expert or project leader keep information

in the Product Helpdek system to retain the knowledge.

Case based reasoning system is made to assist users to identify previous solution and condition to

match with new problem and find the solution. It also assisting project leasers to make decision, to

find similar cases from previous problem, to find best solutions and make decision. It is the best tools

to assist users to take next action and to know whether the processess that have been done is

successful. Most of all, in the example of Android TV software problem from past problem the

programmer who do the debugging can easily identify specifically which programming lines to be

debug and do trouble shoot. With the assistance from Case Based reasoning it has help users not only

for Helpdesk domain but also others domain case base system such as diagnosis such as medical

diagnostic system, assesment such s finance, decision suport such s decision making system and

design system to support designers on design that they have created.

In conclusion, Case Base reasoning not only suitable for the domains above it can also helps to

capture, store and recorded past leaders experience and domain experts. The Case based reasoning

system should be develop incrementally or it can be setup according to the technology and suitability

or wheter the knowledge is relevant. It also helps experts and other users benefiting by incremental

learning. They learn by having to face the difficulty and built up experience by seing different kind of

problem and relating it to the previous problem. It helps the users to build stronger problem solving

skills and understand complexity of problem. By having system, the expert save time on the

explanation by recorded problem and solutions. The most important benefit from Case Base

Reasoning is can stores and easily retrieve to assist other users besides that the expert to share

knowledge for future references.

REFERENCE:

1. Artificaial Intelligence Review. Kolodner, J.L. 1992.

http://alumni.media.mit.edu/~jorkin/generals/papers/Kolodner_case_based_reasoning.pdf

2. Case-Based Reasoning. Ram, A. 2014. https://www.cs.auckland.ac.nz/~ian/CBR/

3. Case-Based Reasoning. Aamodt, A., & Plaza, E.. 1994.

http://cbrwiki.fdi.ucm.es/mediawiki/index.php/Main_Page

4. Case-Based Reasoning. Watson, I., 2001. https://www.cs.auckland.ac.nz/~ian/CBR/cbr-

intro.pdf

5. Introduction to Machine Learning & Case-Based Reasoning. Pantic, M., 2015.

http://ibug.doc.ic.ac.uk/media/uploads/documents/courses/syllabus-CBR.pdf