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Intelligent Database Systems Lab Presenter: CHANG, SHIH-JIE Authors: Kevin Meijer, Flavius Frasincar, Frederik Hogenboom 2014.DSS. A semantic approach.

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Presentation on theme: "Intelligent Database Systems Lab Presenter: CHANG, SHIH-JIE Authors: Kevin Meijer, Flavius Frasincar, Frederik Hogenboom 2014.DSS. A semantic approach."— Presentation transcript:

1 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

2 Intelligent Database Systems Lab Outlines Motivation Objectives Methodology Experiments Conclusions Comments

3 Intelligent Database Systems Lab Motivation Manually creating a taxonomy is difficult and time consuming process and may not be high quality.

4 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).

5 Intelligent Database Systems Lab Methodology   

6 Intelligent Database Systems Lab    

7 Methodology – term filtering lexical cohesion domain pertinence domain consensus domain score of term t in domain corpus Di

8 Intelligent Database Systems Lab WSD on text corpora WSD on existing taxonomies

9 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

10 Intelligent Database Systems Lab Implementation WSD result

11 Intelligent Database Systems Lab Implementation hierarchy creation result

12 Intelligent Database Systems Lab Experiments semantic precision semantic recall

13 Intelligent Database Systems Lab Experiments – core taxonomy V.S. reference taxonomy

14 Intelligent Database Systems Lab Experiments – two measures taxonomic precision taxonomic recall global taxonomic precision global taxonomic recall taxonomic F-measure

15 Intelligent Database Systems Lab Experiments

16 Intelligent Database Systems Lab Experiments

17 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.

18 Intelligent Database Systems Lab Comments Advantages –Define concepts well. Applications –Built taxonomies 、 Term extraction and filtering.


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