Design of an ontological interface for chemical and biotechnological knowledge acquisition by means of an intelligent agent

  • Authors:

  • F. A. Batzias;C. G. Siontorou

  • Affiliations:

  • Department of Industrial Management and Technology, University of Piraeus, Piraeus, Greece;Department of Industrial Management and Technology, University of Piraeus, Piraeus, Greece

  • Venue:
  • AIKED'12 Proceedings of the 11th WSEAS international conference on Artificial Intelligence, Knowledge Engineering and Data Bases
  • Year:
  • 2012

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Abstract

This work advocates the use of an ontology-supported intelligent agent for knowledge acquisition in the chemical/biotechnological domain. A methodological framework is presented, under the form of an algorithmic procedure with 14 activity stages and 5 decision nodes, for introducing a taxonomy/partonomy function within an ad hoc established Knowledge Base (KB), set in the core of the IA, between a cognitive interface and the activity decision maker. This approach has been implemented in optimizing the reliability of a biosensor system. The interface built, based on ontology-supported biosensor modeling that enables the correct annotation of domain semantics for transdisciplinary searching, facilitates (i) model-supported ontology expansion based on both, user interests and domain specificity, and (ii) ontology-supported model retrieval, by which the power of ontology features can be leveraged as a fast index structure to locate most-needed information for the user. Thereby, the functionality of the scheme proposed has been proven suitable to support decision making in knowledge-intensive, multifaceted and dynamic environments.