Olivier Corby

Knowledge Engineering and Knowledge Management Methods, Models, and Tools

Knowledge Modelling Languages and Tools.- OIL in a Nutshell.- The Knowledge Model of Protege-2000: Combining Interoperability and Flexibility.- A Case Study in Using Protege-2000 as a Tool for CommonKADS.- The MOKA Modelling Language.- Md??: A Modelling Language to Build a Formal Ontology in Either Description Logics or Conceptual Graphs.- Ontologies.- Ontologys Crossed Life Cycles.- A Roadmap to Ontology Specification Languages.- A Formal Ontology of Properties.- Construction and Deployment of a Plant Ontology.- The Role of Ontologies for an Effective and Unambiguous Dissemination of Clinical Guidelines.- Supporting Inheritance Mechanisms in Ontology Representation.- Conflict Resolution in the Collaborative Design of Terminological Knowledge Bases.- Knowledge Acquisition from Texts.- Revisiting Ontology Design: A Method Based on Corpus Analysis.- Mining Ontologies from Text.- SVETLAN Or How to Classify Words Using Their Context.- Machine Learning.- KIDS: An Iterative Algorithm to Organize Relational Knowledge.- Informed Selection of Training Examples for Knowledge Refinement.- Experiences with a Generic Refinement Toolkit.- Knowledge Management & E-Commerce.- Whats in an Electronic Business Model?.- Chinese Encyclopaedias and Balinese Cockfights - Lessons for Business Process Change and Knowledge Management.- Using Problem-Solving Models to Design Efficient Cooperative Knowledge-Management Systems Based on Formalization and Traceability of Argumentation.- Integrating Textual Knowledge and Formal Knowledge for Improving Traceability.- Knowledge Management by Reusing Experience.- Problem-Solving Methods.- Integrating Knowledge-Based Configuration Systems by Sharing Functional Architectures.- The Nature of Knowledge in an Abductive Event Calculus Planner.- Adapting Tableaux for Classification.- Knowledge Representation.- Conceptual Information Systems Discussed through an IT-Security Tool.- Translations of Ripple Down Rules into Logic Formalisms.- Generalising Ripple-Down Rules.- Validation, Evaluation and Certification.- Monitoring Knowledge Acquisition Instead of Evaluating Knowledge Bases.- Torture Tests: A Quantitative Analysis for the Robustness of Knowledge-Based Systems.- Certifying KBSs: Using CommonKADS to Provide Supporting Evidence for Fitness for Purpose of KBSs.- Methodologies.- Kinesys, a Participative Approach to the Design of Knowledge Systems.- An Organizational Semiotics Model for Multi-agent Systems Design.

Blackboard architectures in computer aided engineering

Blackboards (BB) are global memory-resident databases, accessible through a uniform protocol and tailored for expert source cooperation. They have been developed for continuous speech understanding (Hearsay-II~), and successfully used in signal processing (HASP-SIAPZ), civil engineering design (Destiny3), and general expert systems shells (BB14). In a way, any expert system working memory is a kind of blackboard: rules can be considered as small expert sources, and they all look at the working memory simultaneously. However, the intelligence and activity of the working memory is very small, and it does not fully qualify for the Blackboard label. For that reason, we claim that one should focus on blackboard architectures more than blackboards per se. What appears essential in a real blackboard architecture is that it is especially tailored to manage complex cooperation of actors. This in turn requires some distinctive features such as uniformity of representation of the data, powerful structuring possibilities and a rich agenda-based monitoring of problem solving. In this paper, we shall further investigate the characteristic features of blackboards, expose some of t he reasons why this architecture will be very useful for Computer Aided Engineering (CAE) expert systems, and report on some preliminary results we have already obtained in the domain. In particular, we show what can be gained by designing a reflexive blackboard architecture where the explanation component is a fullscale knowledge source.

SAMOVAR: Using Ontologies and Text-Mining for Building an Automobile Project Memory

This paper describes SAMOVAR (Systems Analysis of Modeling and Validation of Renault Automobiles), aiming at preserving the memory of the problems encountered during a project in automobile design so as to reuse them in new projects. SAMOVAR relies on (1) the semi-automatic building of ontologies by using a linguistic tool on a textual corpus, (2) the “semantic” annotations of the problem descriptions relatively to these ontologies, (3) the formalization of the ontologies and annotations in RDF(S), (4) the integration of the semantic search engine CORESE that enables an ontology-guided search in the base of problem descriptions.

Challenges in Bridging Social Semantics and Formal Semantics on the Web

This paper describes several results of Wimmics, a research lab which names stands for: web-instrumented man-machine interactions, communities, and semantics. The approaches introduced here rely on graph-oriented knowledge representation, reasoning and operationalization to model and support actors, actions and interactions in web-based epistemic communities. The research results are applied to support and foster interactions in online communities and manage their resources.