intelligent database systems lab presenter: chang, shih-jie authors: kevin meijer, flavius...
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Intelligent Database Systems Lab
Presenter: CHANG, SHIH-JIE
Authors: Kevin Meijer, Flavius Frasincar, Frederik Hogenboom
2014.DSS.
A semantic approach for extracting domain taxonomies from text
Intelligent Database Systems Lab
Outlines
MotivationObjectivesMethodologyExperimentsConclusionsComments
Intelligent Database Systems Lab
Motivation
• Manually creating a taxonomy is difficult and time
consuming process and may not be high quality.
Intelligent Database Systems Lab
Objectives
• This paper presents a framework using a semantic
approach for the automatic building of a domain taxonomy,
called Automatic Taxonomy Construction from Text (ATCT).
Intelligent Database Systems Lab
Methodology
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Methodology – term filtering
lexical cohesion
domain pertinence
domain consensus
domain score of term tin domain corpus Di
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WSD on text corpora
WSD on existing taxonomies
Intelligent Database Systems Lab
Methodology – Concept hierarchy creation
score(pricing | ‘pricing behavior’) = 0.6 + ½*0.4 +1/3*0.3= 0.9 score(trading | ‘pricing behavior’) = 0.7 + ½*0.3 = 0.85
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Implementation WSD result
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Implementation hierarchy creation result
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Experiments
semantic precision
semantic recall
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Experiments – core taxonomy V.S. reference taxonomy
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Experiments – two measurestaxonomic precision
taxonomic recall
global taxonomic precision
global taxonomic recall
taxonomic F-measure
Intelligent Database Systems Lab
Experiments
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Experiments
Intelligent Database Systems Lab
Conclusions– ATCT framework can be successfully applied to other domains than economics and management.– Our approach works well in capturing the broader–narrower relation between concepts .
Intelligent Database Systems Lab
Comments• Advantages
– Define concepts well.• Applications
– Built taxonomies 、 Term extraction and filtering.