Information Technology Reference
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component in the context of the bio-information system framework. The prototype is
implemented with Java language and is applied to a medical case example: colorectal
cancer. The evidence based reasoning theory proposed in this chapter will have significant
impact on computer reasoning and artificial intelligence research.
With the increase of raw power in computer hardware, the search for better intelligent
systems never ends. The research topics cover a wide range of areas. For example, some
studies focus on the emotional aspect of an intelligent system (Fujita & et al., 2010), while
others use statistical reasoning method in classifying news articles (Asy'arie, A. & Pribadi,
A., 2009). Compare to existing literatures and reasoning methods, our presentation on the
topic of computer reasoning (evidence based reasoning) is thorough. In addition, the
reasoning method we proposed is generic in nature, thus it can be used in any domain. One
key feature of our method is its simple calculation. Especially when number of evidence gets
large, this simplicity becomes more important. Of course, you do not get this for free. You
have to do the preparation by calculating degrees for evidences. But the saving you get is
well worth the effort.
3. Background for data, information, knowledge, and wisdom
We can view data, information, knowledge, and wisdom as hierarchical in the context of
knowledge management. With the data at the bottom and the wisdom at the top, we journey
through concrete to abstract, and through no relationship to strong relationship as we move
from left bottom to right top. This phenomenon is shown in Figure 1.
strong relationship
wisdom
knowledge
information
data
no relationship
abstraction
concrete
Fig. 1. Hierarchy of data to wisdom
Raw data are just meaningless points in data space. There are no references or relationships
among these points. Raw data are like a phrase out of context. By themselves, they mean
nothing. (referenced Bellinger, 2004)
