Abstract
Accessing up-to-date information in a fast and easy way implies the necessity of information management tools to explore and analyse the huge number of available electronic resources. The Web offers a large amount of valuable information, but its human-oriented representation and its size makes extremely difficult any kind of computer-based processing. In this paper, a combination of distributed AI and information extraction techniques is proposed to tackle this problem. In particular, we have designed a multiagent system that composes ontologies from taxonomies of terms. Moreover, the obtained ontology is used to represent, in a structured way, the currently available web resources. The paper analyses the application of this approach in some examples in the medical domain.
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Sánchez, D., Isern, D., Moreno, A. (2005). An Agent-Based Knowledge Acquisition Platform. In: Eymann, T., Klügl, F., Lamersdorf, W., Klusch, M., Huhns, M.N. (eds) Multiagent System Technologies. MATES 2005. Lecture Notes in Computer Science(), vol 3550. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11550648_11
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DOI: https://doi.org/10.1007/11550648_11
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