Difference between revisions of "Extracting Domain-Relevant Term Using Wikipedia based on Random Walk Model"

From Wikipedia Quality
Jump to: navigation, search
(Infobox work)
(Embed for English Wikipedia, HTML)
 
Line 10: Line 10:
 
== Overview ==
 
== Overview ==
 
In this paper authors present a new approach for the automatic identification of domain-relevant concepts and entities of a given domain using the category and page structures of the [[Wikipedia]] in a language independent way. By applying Markov random walk algorithm on the weighted Wikipedia link graph, approach can identify large quantities of domain-relevant concepts and entities with very little human effort. Experimental results show that method achieves high accuracy and acceptable efficiency in domain-relevant term extraction.
 
In this paper authors present a new approach for the automatic identification of domain-relevant concepts and entities of a given domain using the category and page structures of the [[Wikipedia]] in a language independent way. By applying Markov random walk algorithm on the weighted Wikipedia link graph, approach can identify large quantities of domain-relevant concepts and entities with very little human effort. Experimental results show that method achieves high accuracy and acceptable efficiency in domain-relevant term extraction.
 +
 +
== Embed ==
 +
=== Wikipedia Quality ===
 +
<code>
 +
<nowiki>
 +
Wu, Wenjuan; Liu, Tao; Hu, He; Du, Xiaoyong. (2012). "[[Extracting Domain-Relevant Term Using Wikipedia based on Random Walk Model]]".DOI: 10.1109/ChinaGrid.2012.20.
 +
</nowiki>
 +
</code>
 +
 +
=== English Wikipedia ===
 +
<code>
 +
<nowiki>
 +
{{cite journal |last1=Wu |first1=Wenjuan |last2=Liu |first2=Tao |last3=Hu |first3=He |last4=Du |first4=Xiaoyong |title=Extracting Domain-Relevant Term Using Wikipedia based on Random Walk Model |date=2012 |doi=10.1109/ChinaGrid.2012.20 |url=https://wikipediaquality.com/wiki/Extracting_Domain-Relevant_Term_Using_Wikipedia_based_on_Random_Walk_Model}}
 +
</nowiki>
 +
</code>
 +
 +
=== HTML ===
 +
<code>
 +
<nowiki>
 +
Wu, Wenjuan; Liu, Tao; Hu, He; Du, Xiaoyong. (2012). &amp;quot;<a href="https://wikipediaquality.com/wiki/Extracting_Domain-Relevant_Term_Using_Wikipedia_based_on_Random_Walk_Model">Extracting Domain-Relevant Term Using Wikipedia based on Random Walk Model</a>&amp;quot;.DOI: 10.1109/ChinaGrid.2012.20.
 +
</nowiki>
 +
</code>

Latest revision as of 23:04, 12 August 2019


Extracting Domain-Relevant Term Using Wikipedia based on Random Walk Model
Authors
Wenjuan Wu
Tao Liu
He Hu
Xiaoyong Du
Publication date
2012
DOI
10.1109/ChinaGrid.2012.20
Links
Original

Extracting Domain-Relevant Term Using Wikipedia based on Random Walk Model - scientific work related to Wikipedia quality published in 2012, written by Wenjuan Wu, Tao Liu, He Hu and Xiaoyong Du.

Overview

In this paper authors present a new approach for the automatic identification of domain-relevant concepts and entities of a given domain using the category and page structures of the Wikipedia in a language independent way. By applying Markov random walk algorithm on the weighted Wikipedia link graph, approach can identify large quantities of domain-relevant concepts and entities with very little human effort. Experimental results show that method achieves high accuracy and acceptable efficiency in domain-relevant term extraction.

Embed

Wikipedia Quality

Wu, Wenjuan; Liu, Tao; Hu, He; Du, Xiaoyong. (2012). "[[Extracting Domain-Relevant Term Using Wikipedia based on Random Walk Model]]".DOI: 10.1109/ChinaGrid.2012.20.

English Wikipedia

{{cite journal |last1=Wu |first1=Wenjuan |last2=Liu |first2=Tao |last3=Hu |first3=He |last4=Du |first4=Xiaoyong |title=Extracting Domain-Relevant Term Using Wikipedia based on Random Walk Model |date=2012 |doi=10.1109/ChinaGrid.2012.20 |url=https://wikipediaquality.com/wiki/Extracting_Domain-Relevant_Term_Using_Wikipedia_based_on_Random_Walk_Model}}

HTML

Wu, Wenjuan; Liu, Tao; Hu, He; Du, Xiaoyong. (2012). &quot;<a href="https://wikipediaquality.com/wiki/Extracting_Domain-Relevant_Term_Using_Wikipedia_based_on_Random_Walk_Model">Extracting Domain-Relevant Term Using Wikipedia based on Random Walk Model</a>&quot;.DOI: 10.1109/ChinaGrid.2012.20.