Knowledge Acquisition for Case-Based Reasoning Systems
Published on 23. December 2013
Book
Paperback/Softback
223 pages
978-3-8439-1357-7 (ISBN)
Description
In this thesis a novel approach for developing distributed knowledge-based systems is presented: The SEASALT (Sharing Experience using an Agent-based System Architecture LayouT) architecture as a modularized, domain-independent architecture that features the extraction of experiences from Web 2.0 sources in order to formalize and apply them in Case-Based Reasoning (CBR) systems. The target CBR systems cover an individual topic (like experts their expertise) and are called to collaborate in order to solve complex, but modularizable problems.
This thesis introduces the overall SEASALT architecture along with the required knowledge modularization, knowledge engineering and knowledge composition components. A special focus within this work is the Knowledge Acquisition for CBR systems and we will present Knowledge Acquisition approaches for all of the above mentioned tasks.
In the course of developing these SEASALT components, the Open Source Tool myCBR is used and further developed in order to fit the SEASALT requirements. The components introduced and methodologies developed are explained within an instantiation of SEASALT for the real-world application domain of travel medicine.
This thesis introduces the overall SEASALT architecture along with the required knowledge modularization, knowledge engineering and knowledge composition components. A special focus within this work is the Knowledge Acquisition for CBR systems and we will present Knowledge Acquisition approaches for all of the above mentioned tasks.
In the course of developing these SEASALT components, the Open Source Tool myCBR is used and further developed in order to fit the SEASALT requirements. The components introduced and methodologies developed are explained within an instantiation of SEASALT for the real-world application domain of travel medicine.