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Acquisition of Knowledge

Cel

The aim of ACKNOWLEDGE is to improve the efficiency with which knowledge is acquired at all phases of knowledge-based system (KBS) development.
The aim of the project is to improve the efficiencywith which knowledge is acquired at all phases of knowledge based system (KBS) development.
The objective is to construct a knowledge engineering workbench (KEW) that will provide an integrated environment for knowledge elicitation and acquisition. Acquisition techniques will be integrated involving exisiting automated and nonautomated techniques. The key constituents of this workbench are machine learning, knowledge elicitation and dialogue techniques. Learning mechanisms will support automatic deduction and organization of new knowledge after new information has been provided or a particular event oberved. Elicitation methods will be implemented that will define the protocols of interaction with the system. Mixed initiative dialogue techniques, based on the recognition of intentions and the visualization of knowledge bases, will provide the foundations for integrating learning mechanisms and elicitation methods in the same environment. The project will also develop a comprehensive framework for guidance at all stages in KBS development.

A first experimental prototype, integrating knowledge acquisition tools for diagnosis and classification applications, has been built and demonstrated, and following evaluation and experiments, a fully integrated version of the workbench has been designed and implemented. Feedback from evaluation, experiments and application developments has been incorporated in the final version of KEW. The workbench includes various knowledge acquisition tools, knowledge storage facilities, knowledge transformation tools, advice and guidance for application developers and user interface libraries.
The objective is to construct a Knowledge Engineering Workbench (KEW) that will provide an integrated environment for knowledge elicitation and acquisition. Methods for integrating several knowledge acquisition techniques will be developed, and an environment that integrates a number of existing automated and non-automated techniques constructed.

The key constituents of this workbench are machine learning, knowledge elicitation and dialogue techniques. Learning mechanisms will support automatic deduction and organisation of new knowledge after new information has been provided or a particular event observed. This capability is necessary to guide the decisions and reactions of the environment. Elicitation methods will be implemented in the environment and will thus define the protocols of interaction with the system. Mixed-initiative dialogue techniques, based on the recognition of intentions and the visualisation of knowledge bases, will provide the foundations for integrating learning mechanisms and elicitation methods in the same environment. The project will also develop a comprehensive framework for guidance at all stages in KBS development.

Temat(-y)

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Zaproszenie do składania wniosków

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System finansowania

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Koordynator

CAP Gemini Innovation
Wkład UE
Brak danych
Adres
7 chemin du Vieux Chêne
38240 Meylan
Francja

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Uczestnicy (7)