Knowledge Management Technologies and Systems

WE NOW HAVE MOVED FROM KM SYSTEMS THEORY AND PRACTICE TO THE FOUNDATIONAL SUPPORT OF KM TECHNOLOGIES. KM SYSTEMS AND TECHNOLOGIES ARE THE MAJOR CHAPTERS WE WILL FOCUS ON IN THIS SUMMER SESSION . READ CHAPTER 7 AND THE LECTURE NOTES IN “COURSE MATERIALS”

ANSWER QUESTIONS ON PAGE 127, 1 – 7

please see the attached file.

Sample sections of the paper

Knowledge Management Technologies and Systems

1. Types of Knowledge Typically Found In Intelligent Systems

The two form of knowledge found in intelligent systems are the knowledge base and inference engine. Knowledge base can be identified as a descriptive, declarative, or propositional knowledge, which is a summation of the existing knowledge through tools such as the ontologies. The model stores complex data, which may be structured and unstructured and which relies on standardization of data elements in representation of facts. On the other hand, Inference engine, which may be viewed as the procedural or non-proposition, defines the facts that have been identified by the knowledge base. The features applied by inference engine are what may be viewed to as the intelligent aspects since they infer from all the obtained information in the knowledge base. The two are easily distinguishable based on their roles. Inference engine often tends to interpret and evaluate the facts possessed in the knowledge base while knowledge base can be said to be an organized collection of facts and information in the domain of the system. Together, the two work in unison.

2. Why Knowledge Based Systems Are More Capable Of Solving Real World Problems Than Search- Based AI Methods

Knowledge based system would be considered to be a better tool in resolving issues in the real world in comparison to search based intelligent system all based on the roles the two perform and the abilities that the two possess. Knowledge based systems are unique in that they can combine more than one factor that may not directly relate to the issues being resolved. The real world issues are a combination of specific case scenarios that have issues that directly or indirectly relate to the issues being reviewed yet they are important issues that contribute to the problem (Fernandez & Sabherwal, 2004). Each of these issues can be defined and well stored in the system of the knowledge based systems for future references. Search based Artificial method cannot be able to apply this aspect in resolving issues, as they have to consider only a specific query. Additionally, connecting queries to offer solutions might require a high level of expertise, which cannot be very applicable in the search, based methods, but can easily be adopted by the knowledge-based systems since they have the expert feature in them.

3. Advantages Of Knowledge Based Systems

Knowledge based systems are an important aspect due to their roles in resolving issues as requested. One most important advantage that accrues to these systems is in their ability to handle issues even in the absence of experts who would have otherwise solved such issues. Their response is also near to perfection and they are always on service at all times. These systems do not experience issues such as fatigue, which

4. disadvantages of knowledge based systems
5. What is heuristic?
6. What is a heuristic Function?
7. What is a heuristic search?

References

Fernandez, I., lez, A. & Sabherwal, R. (2004). Knowledge management : challenges, solutions, and technologies. Upper Saddle River, N.J: Pearson/Prentice Hall.

Maier, R. (2002). Knowledge Management Systems Information and Communication Technologies for Knowledge Management. Berlin, Heidelberg: Springer Berlin Heidelberg.