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Information tuning with KARAT: Capitalizing on existing documents

Long Papers
Part of the Lecture Notes in Computer Science book series (LNCS, 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.

Keywords

Knowledge Management Text Document Requirement Engineer Source Text Preparation Phase 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  1. 1.German Research Center for Artificial Intelligence (DFKI) GmbHKaiserslauternGermany

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