intelligent database systems lab presenter: chang, shih-jie authors: kevin meijer, flavius...

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.

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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).

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Methodology

Intelligent Database Systems Lab

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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

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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

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Experiments

Intelligent Database Systems Lab

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.