Difference between revisions of "Exploring Lexicographic Ontologies for Hierarchically Organizing the Greek Wikipedia Articles"
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| − | '''Exploring Lexicographic Ontologies for Hierarchically Organizing the Greek Wikipedia Articles''' - scientific work related to Wikipedia quality published in 2012, written by Maria Niarou and Sofia Stamou. | + | '''Exploring Lexicographic Ontologies for Hierarchically Organizing the Greek Wikipedia Articles''' - scientific work related to [[Wikipedia quality]] published in 2012, written by [[Maria Niarou]] and [[Sofia Stamou]]. |
== Overview == | == Overview == | ||
| − | To effectively manage the proliferating online content, it is imperative that authors come up with efficient data structuring and organization methods. Based on the findings of previous research (6) (7) that the most flexible and useful way to organize the online content is via the use of taxonomies and/or ontologies, authors carried out the present study, which aims at structuring the content of the Greek Wikipedia via the use of the Greek WordNet. In particular, study objective is to design a model that can automatically organize the Greek Wikipedia categories into a thematic taxonomy and based on the derived organization, to implicitly assign hierarchical structure to the encyclopedia articles that have been classified to the respective categories. To this end, authors relied on the data encoded in Greek WordNet out of which authors harvested the hierarchical relations that hold between the terms used to verbalize the Wikipedia categories. The effectiveness of model is verified by the findings of several experimental evaluations conducted, which demonstrate that semantic networks are powerful resources for hierarchically organizing large volumes of dynamic data. | + | To effectively manage the proliferating online content, it is imperative that authors come up with efficient data structuring and organization methods. Based on the findings of previous research (6) (7) that the most flexible and useful way to organize the online content is via the use of taxonomies and/or ontologies, authors carried out the present study, which aims at structuring the content of the Greek [[Wikipedia]] via the use of the Greek [[WordNet]]. In particular, study objective is to design a model that can automatically organize the Greek [[Wikipedia categories]] into a thematic taxonomy and based on the derived organization, to implicitly assign hierarchical structure to the encyclopedia articles that have been classified to the respective [[categories]]. To this end, authors relied on the data encoded in Greek WordNet out of which authors harvested the hierarchical relations that hold between the terms used to verbalize the Wikipedia categories. The effectiveness of model is verified by the findings of several experimental evaluations conducted, which demonstrate that semantic networks are powerful resources for hierarchically organizing large volumes of dynamic data. |
Revision as of 07:55, 16 July 2019
Exploring Lexicographic Ontologies for Hierarchically Organizing the Greek Wikipedia Articles - scientific work related to Wikipedia quality published in 2012, written by Maria Niarou and Sofia Stamou.
Overview
To effectively manage the proliferating online content, it is imperative that authors come up with efficient data structuring and organization methods. Based on the findings of previous research (6) (7) that the most flexible and useful way to organize the online content is via the use of taxonomies and/or ontologies, authors carried out the present study, which aims at structuring the content of the Greek Wikipedia via the use of the Greek WordNet. In particular, study objective is to design a model that can automatically organize the Greek Wikipedia categories into a thematic taxonomy and based on the derived organization, to implicitly assign hierarchical structure to the encyclopedia articles that have been classified to the respective categories. To this end, authors relied on the data encoded in Greek WordNet out of which authors harvested the hierarchical relations that hold between the terms used to verbalize the Wikipedia categories. The effectiveness of model is verified by the findings of several experimental evaluations conducted, which demonstrate that semantic networks are powerful resources for hierarchically organizing large volumes of dynamic data.
