Agile Development Of Diagnostic Knowledge Systems
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Agile Development of Diagnostic Knowledge Systems
The success of diagnostic knowledge systems has been proved over the last decades. Nowadays, intelligent systems are embedded in machines within various domains or are used in interaction with a user for solving problems. However, the development of a knowledge system is still a critical issue. Similarly to projects dealing with customized software at a highly innovative level a precise specification often cannot be given in advance. Moreover, necessary requirements of the knowledge system can be defined not until the project has been started or are changing during the development phase. This thesis motivates that classical, document-centered approaches cannot be applied in such a setting. We introduce an agile process model for developing diagnostic knowledge systems, mainly inspired by the ideas of the eXtreme Programming methodology known in software engineering. The engineering process is supported at a primary level by the introduction of knowledge containers, that define an organized view of knowledge contained in the system. The actual knowledge is acquired and formalized right from start, and the integration to runnable knowledge systems is done continuously in order to allow for an early and concrete feedback. The validity and maintainability of the collected knowledge is ensured by appropriate test methods and restructuring techniques, respectively. Additionally, we propose learning methods to support the knowledge acquisition process sufficiently. The process model and its activities are evaluated in two real life applications: in a medical and in an environmental project the benefits of the agile development are clearly demonstrated.
Engineering Knowledge in the Age of the Semantic Web
The central themes of the 14th International Conference on Knowledge Engineering and Knowledge Management (EKAW 2004) were ontological engineering and the Semantic Web. These provide the key foundational and delivery mechanisms for building open, Web-based knowledge services. However, consistent with the tradition of EKAW conferences, EKAW 2004 was concerned with all aspects of eliciting, acquiring, modelling and managing knowledge, and its role in the construction of knowledge-intensive systems. Indeed a key aspect of the Knowledge Acquisition Workshops (KAWs) held in the US, Europe and Asia over the past 20 years has been the emphasis on ‘holistic’ knowledge engineering, addressing problem solving, usability, socio-technological factors and knowledge modelling, rather than simply analyzing and designing symbol-level inferential mechanisms. The papers included in this volume are thus drawn from a variety of research areas both at the cutting edge of research in ontologies and the Semantic Web and in the more traditionally grounded areas of knowledge engineering. A Semantic Web service can be seen as the addition of semantic technologies to Web services to produce Web-accessible services that can be described using appropriate ontologies, reasoned about and combined automatically. Since Web services can be seen as Web-accessible computational objects, much of the work in this area is also concerned with problem-solving methods (PSMs).
KI 2006
This book constitutes the thoroughly refereed post-proceedings of the 29th Annual German Conference on Artificial Intelligence, KI 2006, held in Bremen, Germany, in June 2006. This was co-located with RoboCup 2006, the innovative robot soccer world championship, and with ACTUATOR 2006, the 10th International Conference on New Actuators. The 29 revised full papers presented together with two invited contributions were carefully reviewed and selected from 112 submissions.