Information Technology Reference
In-Depth Information
2
Knowledge Management in
Bio-Information Systems
Kuodi Jian
Metropolitan State University, Saint Paul, MN
USA
1. Introduction
Knowledge management is a broad topic. For different people, it may mean different things.
For business people, this phrase means the accumulated procedures/processes and
experiences (organizational assets), and the way to facilitate the use, and to retain these
assets within an organization. The Wikipedia website has the following definition for the
knowledge management:
“Knowledge Management (KM)
comprises a range of strategies and practices used in an
organization to identify, create, represent, distribute, and enable adoption of insights and
experiences. Such insights and experiences comprise knowledge, either embodied in
individuals or embedded in organizational processes or practice.” (Internet resource:
http://en.wikipedia.org/wiki/Knowledge_management. Retrieved on 5/30/2011)
For computer science people, especially for those expert system developers, the term
“knowledge management” has different meaning. We, computer science scientists, are
concerned with the knowledge representation, data mining, and the knowledge structure
that facilitates knowledge storage and retrieval with computers in mind. Thus, we will
define the knowledge management as follows:
Knowledge Management (KM)
comprises a wide range of methods/activities that extract
information/knowledge from a body of unstructured raw data; organize the extracted
information into structured form called knowledge; and design knowledge databases that
are able to store and retrieve knowledge in an efficient way using computers.
In the above definition, we mentioned several terms such as raw data, information, and
knowledge. What are the differences and the relationships among them? And the more
fundamental question: how do we reason when faced with these entities? In the following
sections, we will address these questions. First, we will outline the contributions of this
document in the next section.
2. Contributions
In this chapter, we will introduce a computer reasoning method called “evidence theory”
that is based on Bayes' theorem. We will describe relationships among raw data, knowledge,
and information; we will implement a prototype of the evidence based reasoning software
