Difference between revisions of "Fact Discovery in Wikipedia"

From Wikipedia Quality
Jump to: navigation, search
(Infobox)
(+ embed code)
Line 10: Line 10:
 
== Overview ==
 
== Overview ==
 
Authors address the task of extracting focused salient information items, relevant and important for a given topic, from a large encyclopedic resource. Specifically, for a given topic (a [[Wikipedia]] article) authors identify snippets from other articles in Wikipedia that contain important information for the topic of the original article, without duplicates. Authors compare several methods for addressing the task, and find that a mixture of content-based, link-based, and layout-based [[features]] outperforms other methods, especially in combination with the use of so-called reference corpora that capture the key properties of entities of a common type.
 
Authors address the task of extracting focused salient information items, relevant and important for a given topic, from a large encyclopedic resource. Specifically, for a given topic (a [[Wikipedia]] article) authors identify snippets from other articles in Wikipedia that contain important information for the topic of the original article, without duplicates. Authors compare several methods for addressing the task, and find that a mixture of content-based, link-based, and layout-based [[features]] outperforms other methods, especially in combination with the use of so-called reference corpora that capture the key properties of entities of a common type.
 +
 +
== Embed ==
 +
=== Wikipedia Quality ===
 +
<code>
 +
<nowiki>
 +
Adafre, Sisay Fissaha; Jijkoun, Valentin; Rijke, M. de. (2007). "[[Fact Discovery in Wikipedia]]". IEEE Computer Society. DOI: 10.1109/WI.2007.57.
 +
</nowiki>
 +
</code>
 +
 +
=== English Wikipedia ===
 +
<code>
 +
<nowiki>
 +
{{cite journal |last1=Adafre |first1=Sisay Fissaha |last2=Jijkoun |first2=Valentin |last3=Rijke |first3=M. de |title=Fact Discovery in Wikipedia |date=2007 |doi=10.1109/WI.2007.57 |url=https://wikipediaquality.com/wiki/Fact_Discovery_in_Wikipedia |journal=IEEE Computer Society}}
 +
</nowiki>
 +
</code>
 +
 +
=== HTML ===
 +
<code>
 +
<nowiki>
 +
Adafre, Sisay Fissaha; Jijkoun, Valentin; Rijke, M. de. (2007). &amp;quot;<a href="https://wikipediaquality.com/wiki/Fact_Discovery_in_Wikipedia">Fact Discovery in Wikipedia</a>&amp;quot;. IEEE Computer Society. DOI: 10.1109/WI.2007.57.
 +
</nowiki>
 +
</code>

Revision as of 14:10, 4 January 2020


Fact Discovery in Wikipedia
Authors
Sisay Fissaha Adafre
Valentin Jijkoun
M. de Rijke
Publication date
2007
DOI
10.1109/WI.2007.57
Links
Original

Fact Discovery in Wikipedia - scientific work related to Wikipedia quality published in 2007, written by Sisay Fissaha Adafre, Valentin Jijkoun and M. de Rijke.

Overview

Authors address the task of extracting focused salient information items, relevant and important for a given topic, from a large encyclopedic resource. Specifically, for a given topic (a Wikipedia article) authors identify snippets from other articles in Wikipedia that contain important information for the topic of the original article, without duplicates. Authors compare several methods for addressing the task, and find that a mixture of content-based, link-based, and layout-based features outperforms other methods, especially in combination with the use of so-called reference corpora that capture the key properties of entities of a common type.

Embed

Wikipedia Quality

Adafre, Sisay Fissaha; Jijkoun, Valentin; Rijke, M. de. (2007). "[[Fact Discovery in Wikipedia]]". IEEE Computer Society. DOI: 10.1109/WI.2007.57.

English Wikipedia

{{cite journal |last1=Adafre |first1=Sisay Fissaha |last2=Jijkoun |first2=Valentin |last3=Rijke |first3=M. de |title=Fact Discovery in Wikipedia |date=2007 |doi=10.1109/WI.2007.57 |url=https://wikipediaquality.com/wiki/Fact_Discovery_in_Wikipedia |journal=IEEE Computer Society}}

HTML

Adafre, Sisay Fissaha; Jijkoun, Valentin; Rijke, M. de. (2007). &quot;<a href="https://wikipediaquality.com/wiki/Fact_Discovery_in_Wikipedia">Fact Discovery in Wikipedia</a>&quot;. IEEE Computer Society. DOI: 10.1109/WI.2007.57.