Difference between revisions of "Extracting Domain-Relevant Term Using Wikipedia based on Random Walk Model"
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| + | | title = Extracting Domain-Relevant Term Using Wikipedia based on Random Walk Model | ||
| + | | date = 2012 | ||
| + | | authors = [[Wenjuan Wu]]<br />[[Tao Liu]]<br />[[He Hu]]<br />[[Xiaoyong Du]] | ||
| + | | doi = 10.1109/ChinaGrid.2012.20 | ||
| + | | link = http://doi.ieeecomputersociety.org/10.1109/ChinaGrid.2012.20 | ||
| + | }} | ||
'''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]]. | '''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 == | == 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. | ||
Revision as of 08:58, 25 July 2019
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.
