Difference between revisions of "A Technique for Suggesting Related Wikipedia Articles Using Link Analysis"

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== Overview ==
 
== Overview ==
 
With more than 3.7 million articles, [[Wikipedia]] has become an important social medium for sharing knowledge. However, with this enormous repository of information, it can often be difficult to locate fundamental topics that support lower-level articles. By exploiting the information stored in the links between articles, authors propose that related companion articles can be automatically generated to help further the reader's understanding of a given topic. This approach to a recommendation system uses tested link analysis techniques to present users with a clear path to related high-level articles, furthering the understanding of low-level topics.
 
With more than 3.7 million articles, [[Wikipedia]] has become an important social medium for sharing knowledge. However, with this enormous repository of information, it can often be difficult to locate fundamental topics that support lower-level articles. By exploiting the information stored in the links between articles, authors propose that related companion articles can be automatically generated to help further the reader's understanding of a given topic. This approach to a recommendation system uses tested link analysis techniques to present users with a clear path to related high-level articles, furthering the understanding of low-level topics.
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== Embed ==
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=== Wikipedia Quality ===
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Markson, Christopher; Song, Min. (2012). "[[A Technique for Suggesting Related Wikipedia Articles Using Link Analysis]]".DOI: 10.1145/2232817.2232883.
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=== English Wikipedia ===
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{{cite journal |last1=Markson |first1=Christopher |last2=Song |first2=Min |title=A Technique for Suggesting Related Wikipedia Articles Using Link Analysis |date=2012 |doi=10.1145/2232817.2232883 |url=https://wikipediaquality.com/wiki/A_Technique_for_Suggesting_Related_Wikipedia_Articles_Using_Link_Analysis}}
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=== HTML ===
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Markson, Christopher; Song, Min. (2012). &amp;quot;<a href="https://wikipediaquality.com/wiki/A_Technique_for_Suggesting_Related_Wikipedia_Articles_Using_Link_Analysis">A Technique for Suggesting Related Wikipedia Articles Using Link Analysis</a>&amp;quot;.DOI: 10.1145/2232817.2232883.
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Revision as of 08:10, 4 October 2019


A Technique for Suggesting Related Wikipedia Articles Using Link Analysis
Authors
Christopher Markson
Min Song
Publication date
2012
DOI
10.1145/2232817.2232883
Links
Original

A Technique for Suggesting Related Wikipedia Articles Using Link Analysis - scientific work related to Wikipedia quality published in 2012, written by Christopher Markson and Min Song.

Overview

With more than 3.7 million articles, Wikipedia has become an important social medium for sharing knowledge. However, with this enormous repository of information, it can often be difficult to locate fundamental topics that support lower-level articles. By exploiting the information stored in the links between articles, authors propose that related companion articles can be automatically generated to help further the reader's understanding of a given topic. This approach to a recommendation system uses tested link analysis techniques to present users with a clear path to related high-level articles, furthering the understanding of low-level topics.

Embed

Wikipedia Quality

Markson, Christopher; Song, Min. (2012). "[[A Technique for Suggesting Related Wikipedia Articles Using Link Analysis]]".DOI: 10.1145/2232817.2232883.

English Wikipedia

{{cite journal |last1=Markson |first1=Christopher |last2=Song |first2=Min |title=A Technique for Suggesting Related Wikipedia Articles Using Link Analysis |date=2012 |doi=10.1145/2232817.2232883 |url=https://wikipediaquality.com/wiki/A_Technique_for_Suggesting_Related_Wikipedia_Articles_Using_Link_Analysis}}

HTML

Markson, Christopher; Song, Min. (2012). &quot;<a href="https://wikipediaquality.com/wiki/A_Technique_for_Suggesting_Related_Wikipedia_Articles_Using_Link_Analysis">A Technique for Suggesting Related Wikipedia Articles Using Link Analysis</a>&quot;.DOI: 10.1145/2232817.2232883.