Mining knowledge from natural language texts using fuzzy associated concept mapping
description
Transcript of Mining knowledge from natural language texts using fuzzy associated concept mapping
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Intelligent Database Systems Lab
Presenter : Kung, Chien-Hao
Authors : W.M. Wang, C.F. Cheung, W.B. Lee, S.K. Kwok
2008,IPM
Mining knowledge from natural language texts using fuzzy associated concept mapping
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Intelligent Database Systems Lab
OutlinesMotivationObjectivesMethodologyExperimentsConclusionsComments
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Intelligent Database Systems Lab
Motivation• Knowledge, for easy retrieval and
processing by computers, should be represented in a formal, structured.
• Unfortunately, knowledge presented in many documents has an informal, unstructured shape.
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Intelligent Database Systems Lab
Objectives• In order to provide advanced knowledge services,
efficient ways are needed to access and extract
knowledge from unstructured documents.
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Intelligent Database Systems Lab
Methodology-Framework
• Automatic process
• Interactive process
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Intelligent Database Systems Lab
Methodology• Automatic process
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Intelligent Database Systems Lab
Methodology• Automatic process
• Rule-based reasoning (RBR) • Case-based reasoning (CBR).
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Intelligent Database Systems Lab
Methodology• Automatic process
Variation type Example
Number “techniques” and “technique”
Semantic “classification” and “categorization”
Spelling “cluster-based” and “cluster based”
Syntactic “information retrieval” and “retrieval of information”
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Intelligent Database Systems Lab
Methodology• Interactive process
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Intelligent Database Systems Lab
Experiment
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Intelligent Database Systems Lab
Experiment
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Intelligent Database Systems Lab
Conclusions• The method provides users to convert scientific and
short texts into a structured format which can be easily processed by computer.
• Moreover, the method provides knowledge workers to view their knowledge from another angle.
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Intelligent Database Systems Lab
Comments• Advantages– This paper supplies the rich information.
• Applications– Concept mapping.