Intelligent Database Systems Lab
Presenter : JHOU, YU-LIANG
Authors :Shady Shehata , Fakhri Karray, Mohamed S. Kamel, Fellow
2012, IEEE
An Efficient Concept-Based Mining Model for Enhancing Text Clustering
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OutlinesMotivationObjectivesMethodology EvaluationConclusionsComments
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Motivation• In text mining ,the term frequency is
computed to explore the importance of the term in document.
• However, two terms can have the same frequency in documents, but one term contributes more to the meaning of its sentences than the other term.
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ObjectivesUsing Concept-Based Mining Model for Text Clustering , improve the clustering quality.
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Methodology Concept-Based Mining Model
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Methodology CONCEPT-BASED MINING MODEL
Ex: a concept c which appears twice in document d in the first and the second sentences The concept c appears five times in the verb argument structures of the first sentence s 1 , and three times in the verb argument structuresof the second sentence s 2 . ans : ctf value = (5+3)/2=4
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MethodologyCorpus-Based Concept Analysis Algorithm
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Methodology Example of Conceptual Term Frequency
. [ARG0 Texas and Australia researchers] have [TARGET created] [ARG1 industry-ready sheets of materials made from nanotubes that could lead tothe development of artificial muscles].
[ARG1 materials] [TARGET made ] [ARG2 from nanotubes that could leadto the development of artificial muscles].
[ARG1 nanotubes] [R-ARG1 that] [ARGM-MOD could] [TARGET lead] [ARG2 to the development of artificial muscles].
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Methodology Example of Conceptual Term Frequency
1. First verb argument structure for the verb created:. [ARG0 Texas and Australia researchers]. [TARGET created]. [ARG1 industry-ready sheets of materials madefrom nanotubes that could lead to the development of artificial muscles].
2. Second verb argument structure for the verb made:. [ARG1 materials]. [TARGET made]. [ARG2 from nanotubes that could lead to the development of artificial muscles].
3. Third verb argument structure for the verb lead:. [ARG1 nanotubes]. [R-ARG1 that]. [ARGM-MOD could]. [TARGET lead]. [ARG2 to the development of artificial muscles].
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MethodologyExample of Conceptual Term Frequency
1. Concepts in the first verb argument structure of the verb created:. Texas Australia researchers. created. industry-ready sheets materials nanotubes lead development artificial muscles
2. Concepts in the second verb argument structure of the verb made:. materials. nanotubes lead development artificial muscles
3. Concepts in the third verb argument structure of the verb lead:. nanotubes. lead. development artificial muscles.
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Methodology Example of Conceptual Term Frequency
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Methodology Concept-Based Similarity Measure
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Experimental Result
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Experimental Result
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Experimental Result
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Experimental Result
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Conclusions The new approach enhance text clustering quality.
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CommentsAdvantages Improve the text clustering quality.Applications -Concept-based mining model -Conceptual term frequency
