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

Intelligent Database Systems Lab

OutlinesMotivationObjectivesMethodologyExperimentsConclusionsComments

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.

Intelligent Database Systems Lab

Objectives• In order to provide advanced knowledge services,

efficient ways are needed to access and extract

knowledge from unstructured documents.

Intelligent Database Systems Lab

Methodology-Framework

• Automatic process

• Interactive process

Intelligent Database Systems Lab

Methodology• Automatic process

Intelligent Database Systems Lab

Methodology• Automatic process

• Rule-based reasoning (RBR) • Case-based reasoning (CBR).

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”

Intelligent Database Systems Lab

Methodology• Interactive process

Intelligent Database Systems Lab

Experiment

Intelligent Database Systems Lab

Experiment

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.

Intelligent Database Systems Lab

Comments• Advantages– This paper supplies the rich information.

• Applications– Concept mapping.