Integration of linked open data in case-based reasoning systems

This paper discusses the opportunities of integrating Linked Open Data (LOD) resources into Case-Based Reasoning (CBR) systems. Upon the application domain travel medicine, we will exemplify how LOD can be used to fill three out of four knowledge containers a CBR system is based on. The paper also presents the applied techniques for the realization and demonstrates the performance gain of knowledge acquisition by the use of LOD

GenRule : Learning of Shortcut-Oriented Diagnostic Problem Solving in the MOLTKE 3 Workbench

GenRule is the offline processing component of the MOLTKE3 workbench’s learning mechanism. It learns from diagnostic cases, i.e. protocols of the diagnostic behavior of an experienced service technician. The result of a learning step are so called shortcut rules, which allow the derivation of symptom values from other already known values. Furthermore, these rules are used to direct the diagnostic strategy applied by the MOLTKE3 shell. The presented mechanism appears to be well suited for modeling the typical diagnostic behavior of a service technician

Knowledge modelling with the open source tool myCBR

Building knowledge intensive Case-Based Reasoning applications requires tools that support this on-going process between domain experts and knowledge engineers. In this paper we will introduce how the open source tool myCBR 3 allows for flexible knowledge elicitation and formalisation form CBR and non CBR experts. We detail on myCBR 3 's versatile approach to similarity modelling and will give an overview of the Knowledge Engineering workbench, providing the tools for the modelling process. We underline our presentation with three case studies of knowledge modelling for technical diagnosis and recommendation systems using myCBR 3

Deriving case base vocabulary from web community data

This paper presents and approach for knowledge extraction for Case-Based Reasoning systems. The recent development of the WWW, especially the Web 2.0, shows that many successful applications are web based. Moreover, the Web 2.0 offers many experiences and our approach uses those experiences to fill the knowledge containers. We are especially focusing on vocabulary knowledge and are using forum posts to create domain-dependent taxonomies that can be directly used in Case-Based Reasoning systems. This paper introduces the applied knowledge extraction process based on the KDD process and explains its application on a web forum for travelers

Multiple Knowledge Acquisition Strategies in MOLTKE

In this paper we will present a design model (in the sense of KADS) for the domain of technical diagnosis. Based on this we will describe the fully implemented expert system shell MOLTKE 3.0, which integrates common knowledge acquisition methods with techniques developed in the fields of Model-Based Diagnosis and Machine Learning, especially Case-Based Reasoning

Artificial intelligence and software engineering: Status and future trends

The disciplines of Artificial Intelligence and Software Engineering have many commonalities. Both deal with modeling real world objects from the real world like business processes, expert knowledge, or process models. This article gives a short overview about these disciplines and describes some current research topics against the background of common points of contact

Knowledge management in case-based reasoning

The Knowledge Engineering Review, 20(3): pp. 305-310.This commentary describes two core knowledge management approaches that applied case-based reasoning as a methodological foundation for organizational systems managing experience. These research projects illustrate the presence of knowledge management in case-based reasoning by focusing on the dualism between case-based reasoning and organizational approaches targeting knowledge management goals