Difference between revisions of "Constructing Large-Scale Person Ontology from Wikipedia"
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+ | {{Infobox work | ||
+ | | title = Constructing Large-Scale Person Ontology from Wikipedia | ||
+ | | date = 2010 | ||
+ | | authors = [[Yumi Shibaki]]<br />[[Masaaki Nagata]]<br />[[Kazuhide Yamamoto]] | ||
+ | | link = http://www.aclweb.org/anthology/W10-3501 | ||
+ | }} | ||
'''Constructing Large-Scale Person Ontology from Wikipedia''' - scientific work related to [[Wikipedia quality]] published in 2010, written by [[Yumi Shibaki]], [[Masaaki Nagata]] and [[Kazuhide Yamamoto]]. | '''Constructing Large-Scale Person Ontology from Wikipedia''' - scientific work related to [[Wikipedia quality]] published in 2010, written by [[Yumi Shibaki]], [[Masaaki Nagata]] and [[Kazuhide Yamamoto]]. | ||
== Overview == | == Overview == | ||
This paper presents a method for constructing a large-scale Person Ontology with category hierarchy from [[Wikipedia]]. Authors first extract Wikipedia category labels which represent person (hereafter, Wikipedia Person Category, WPC) by using a machine learning classifier. Authors then construct a WPC hierarchy by detecting is-a relations in the Wikipedia category network. Authors then extract the titles of Wikipedia articles which represent person (hereafter, Wikipedia person instance, WPI). Experiments show that the accuracy of WPC extraction is 99.3% precision and 98.4% recall, while that of WPI extraction is 98.2% and 98.6%, respectively. The accuracies are significantly higher than the previous methods. | This paper presents a method for constructing a large-scale Person Ontology with category hierarchy from [[Wikipedia]]. Authors first extract Wikipedia category labels which represent person (hereafter, Wikipedia Person Category, WPC) by using a machine learning classifier. Authors then construct a WPC hierarchy by detecting is-a relations in the Wikipedia category network. Authors then extract the titles of Wikipedia articles which represent person (hereafter, Wikipedia person instance, WPI). Experiments show that the accuracy of WPC extraction is 99.3% precision and 98.4% recall, while that of WPI extraction is 98.2% and 98.6%, respectively. The accuracies are significantly higher than the previous methods. |
Revision as of 09:45, 12 July 2019
Authors | Yumi Shibaki Masaaki Nagata Kazuhide Yamamoto |
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Publication date | 2010 |
Links | Original |
Constructing Large-Scale Person Ontology from Wikipedia - scientific work related to Wikipedia quality published in 2010, written by Yumi Shibaki, Masaaki Nagata and Kazuhide Yamamoto.
Overview
This paper presents a method for constructing a large-scale Person Ontology with category hierarchy from Wikipedia. Authors first extract Wikipedia category labels which represent person (hereafter, Wikipedia Person Category, WPC) by using a machine learning classifier. Authors then construct a WPC hierarchy by detecting is-a relations in the Wikipedia category network. Authors then extract the titles of Wikipedia articles which represent person (hereafter, Wikipedia person instance, WPI). Experiments show that the accuracy of WPC extraction is 99.3% precision and 98.4% recall, while that of WPI extraction is 98.2% and 98.6%, respectively. The accuracies are significantly higher than the previous methods.