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Implementation av ett kunskapsbas system för rough set theory med kvantitativa mätningar
Linköping University, Department of Computer and Information Science.
2004 (Swedish)Independent thesis Basic level (professional degree)Student thesisAlternative title
Implementation of a Rough Knowledge Base System Supporting Quantitative Measures (English)
Abstract [en]

This thesis presents the implementation of a knowledge base system for rough sets [Paw92]within the logic programming framework. The combination of rough set theory with logic programming is a novel approach. The presented implementation serves as a prototype system for the ideas presented in [VDM03a, VDM03b]. The system is available at "".

The presented language for describing knowledge in the rough knowledge base caters for implicit definition of rough sets by combining different regions (e.g. upper approximation, lower approximation, boundary) of other defined rough sets. The rough knowledge base system also provides methods for querying the knowledge base and methods for computing quantitative measures.

We test the implemented system on a medium sized application example to illustrate the usefulness of the system and the incorporated language. We also provide performance measurements of the system.

Place, publisher, year, edition, pages
Institutionen för datavetenskap , 2004. , 91 p.
Keyword [en]
Datalogi, Rough set theory, rough sets, logic programming, knowledge bases, artificial intelligence, uncertain reasoning, incomplete reasoning, quantitative measures.
Keyword [sv]
National Category
Computer Science
URN: urn:nbn:se:liu:diva-1756ISRN: LITH-IDA-EX--04/056--SEOAI: diva2:19082
Available from: 2004-08-24 Created: 2004-08-24

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Department of Computer and Information Science
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