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Information tuning with KARAT: Capitalizing on existing documents

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Knowledge Acquisition, Modeling and Management (EKAW 1997)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 1319))

Abstract

Organizations store their information in electronic or paper documents. This information is severely underutilized in the daily work of most organizations. Because there are no effective means to access the documents, employees do not find relevant information, or are not even aware of its existence. We describe Information Tuning - a first step towards knowledge management in enterprises. Information Tuning capitalizes on existing documents and enables better exploitation of the contained knowledge by adding the background, context, and meta information which is necessary for making possible beneficial utilization, sharing, and reuse. We present an Information Tuning method which evolved from model-based knowledge acquisition from texts, and illustrate the method with application examples. Information Tuning is supported by the KARAT tool which applies techniques from text analysis and hypertext technology.

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Authors and Affiliations

  1. German Research Center for Artificial Intelligence (DFKI) GmbH, P.O. Box 2080, D-67608, Kaiserslautern, Germany

    Bidjan Tschaitschian, Andreas Abecker & Franz Schmalhofer

Authors
  1. Bidjan Tschaitschian
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  2. Andreas Abecker
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  3. Franz Schmalhofer
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Enric Plaza Richard Benjamins

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© 1997 Springer-Verlag Berlin Heidelberg

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Tschaitschian, B., Abecker, A., Schmalhofer, F. (1997). Information tuning with KARAT: Capitalizing on existing documents. In: Plaza, E., Benjamins, R. (eds) Knowledge Acquisition, Modeling and Management. EKAW 1997. Lecture Notes in Computer Science, vol 1319. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0026791

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  • DOI: https://doi.org/10.1007/BFb0026791

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-63592-5

  • Online ISBN: 978-3-540-69606-3

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