The progressive knowledge reconstruction and its value chain management

Description

In this paper, we have proposed and explained how to realize the progressive knowledge reconstruction. As a new concept, we have defined the four different knowledge levels from level 0 to level 3. In level 0, raw knowledge is arranged. Knowledge is either explicit or implicit. There is no relation between knowledge. The width and depth of knowledge is different from each other. Level 1 is a domain-oriented knowledge which is generally shown at present. The knowledge is classified and arranged with tree structure. There is normally a boundary decided in advance. The process of converting knowledge from the knowledge level 0 to knowledge level 1 is considered as the structuring knowledge. With this converting process, knowledge is represented with well-defined and well-formed structure. This deductive point of view has been effective ways for the knowledge management. Knowledge level 2 is a domain-free semantic network where knowledge is related with each other by using the concept of association paths. There are multiple association paths from the starting knowledge to the arriving knowledge on the semantic network. This network is regarded as an infrastructure for the knowledge management. In level 3, knowledge is related with an enterprise activity or specified target to achieve. There is a requirement to utilize the knowledge infrastructure in order to give the regarding knowledge to the business model in level 3. Then, some association paths on level 2 are activated. The decision making process in level 3 acts as a catalyst for the activation of association paths. By the progressive knowledge reconstruction process, it is expected to support the creation of new technology and innovation in industry. In order to support the value chain management throughout the progressive knowledge reconstruction process, we have proposed to utilize the knowledge activists in the knowledge community. The knowledge community on the Web is very important to continuously create value from knowledge reconstruction.

Journal

Details 詳細情報について

Report a problem

Back to top