The exploitation process describes the method of exploiting and visualizing capitalized knowledge. It is based on the EQUA2TE (Explore, Query, Analyze and Annotate) method and case based reasoning matching technique. It is of two modes, namely, exploration and querying modes.

Function δ in (2) is executed by this algorithm in a way that facilitates visualization of KR by actors through query formulation. The other option is through direct exploration of clusters of related KR. Visualization of KR is classified into three options. They are - validated KR, its evolution before the validation and the complete sequence from initiation through to validation. The next section describes the implementation of the algorithm.

E. KM System Testing and Application to Case Study The Recursively Dynamic Algorithm for Capitalization of Knowledge was implemented in the form of a web-based prototype called EIKC (Economic Intelligence Knowledge Capitalization) system. The sample case study was Sunseed Oil Nigeria Plc. (Private Limited Company). The survey of the case study was carried out as a Professional Master Degree project. The board of directors of the company constitutes the decision makers while the product researchers serve as watchers. They normally use the general managerial approach for handling DP. However, the application of EI process was proposed to them. A typical DP on how to improve the productivity of the company and to guarantee customer satisfaction was considered in the light of total automation of production and sales processes.

EIKC system is simulated with a number of scenarios of DP projects including that of total automation specified for our case study. Knowledge is capitalized from actors according to the EI process in the course of resolving the DP. The snapshots in figures 5 and 6 describe the knowledge capitalization of DP resolution on "total automation of production and sales processes".

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In figure 7, the system was accessed by the decision maker to present DP and its contexts in form of internal and external environments. This DP document was automatically stored with the timestamp. Subsequently, the watcher defines the stake of the DP as illustrated in figure 8. Decision maker used annotation interface for the validation of the specified stake while the timestamp is also stored. The watcher reacts to decision maker"s annotation and update DP stake accordingly. 

This process is repeated until concession is reached. The knowledge of the subsequent tasks of the resolution process was capitalized with respective links on the EIKC system interface.

Actors exploit the KM system by visualizing both validated and pre-validated or evolving knowledge of specific tasks of resolving DP according to EI process. Figure 7illustrates knowledge of actors on the DP as it evolved. It also makes visible the actors who originated such knowledge and the respective timestamps.

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