Difference between revisions of "Fact Discovery in Wikipedia"

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

Latest revision as of 20:39, 14 June 2019

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.