Difference between revisions of "Graph-Based Domain-Specific Semantic Relatedness from Wikipedia"

From Wikipedia Quality
Jump to: navigation, search
(Wikilinks)
(Infobox work)
Line 1: Line 1:
 +
{{Infobox work
 +
| title = Graph-Based Domain-Specific Semantic Relatedness from Wikipedia
 +
| date = 2014
 +
| authors = [[Armin Sajadi]]
 +
| doi = 10.1007/978-3-319-06483-3_42
 +
| link = https://link.springer.com/content/pdf/10.1007%2F978-3-319-06483-3_42.pdf
 +
}}
 
'''Graph-Based Domain-Specific Semantic Relatedness from Wikipedia''' - scientific work related to [[Wikipedia quality]] published in 2014, written by [[Armin Sajadi]].
 
'''Graph-Based Domain-Specific Semantic Relatedness from Wikipedia''' - scientific work related to [[Wikipedia quality]] published in 2014, written by [[Armin Sajadi]].
  
 
== Overview ==
 
== Overview ==
 
Human made ontologies and lexicons are promising resources for many text mining tasks in domain specific applications, but they do not exist for most domains. Authors study the suitability of [[Wikipedia]] as an alternative resource for ontologies regarding the Semantic Relatedness problem.
 
Human made ontologies and lexicons are promising resources for many text mining tasks in domain specific applications, but they do not exist for most domains. Authors study the suitability of [[Wikipedia]] as an alternative resource for ontologies regarding the Semantic Relatedness problem.

Revision as of 11:59, 14 June 2020


Graph-Based Domain-Specific Semantic Relatedness from Wikipedia
Authors
Armin Sajadi
Publication date
2014
DOI
10.1007/978-3-319-06483-3_42
Links
Original

Graph-Based Domain-Specific Semantic Relatedness from Wikipedia - scientific work related to Wikipedia quality published in 2014, written by Armin Sajadi.

Overview

Human made ontologies and lexicons are promising resources for many text mining tasks in domain specific applications, but they do not exist for most domains. Authors study the suitability of Wikipedia as an alternative resource for ontologies regarding the Semantic Relatedness problem.