https://wikipediaquality.com/index.php?title=Computing_Semantic_Relatedness_from_Human_Navigational_Paths:_a_Case_Study_on_Wikipedia&feed=atom&action=historyComputing Semantic Relatedness from Human Navigational Paths: a Case Study on Wikipedia - Revision history2024-03-29T07:50:30ZRevision history for this page on the wikiMediaWiki 1.30.0https://wikipediaquality.com/index.php?title=Computing_Semantic_Relatedness_from_Human_Navigational_Paths:_a_Case_Study_on_Wikipedia&diff=22739&oldid=prevAmelia: + categories2019-12-09T05:44:37Z<p>+ categories</p>
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</table>Ameliahttps://wikipediaquality.com/index.php?title=Computing_Semantic_Relatedness_from_Human_Navigational_Paths:_a_Case_Study_on_Wikipedia&diff=21658&oldid=prevEliana: Embed for English Wikipedia, HTML2019-10-26T22:08:44Z<p>Embed for English Wikipedia, HTML</p>
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<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>== Overview ==</div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>== Overview ==</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>In this article, the authors present a novel approach for computing semantic [[relatedness]] and conduct a large-scale study of it on [[Wikipedia]]. Unlike existing semantic analysis methods that utilize Wikipedia's content or link structure, the authors propose to use human navigational paths on Wikipedia for this task. The authors obtain 1.8 million human navigational paths from a semi-controlled navigation experiment-a Wikipedia-based navigation game, in which users are required to find short paths between two articles in a given Wikipedia article network. The authors' results are intriguing: They suggest that i semantic relatedness computed from human navigational paths may be more precise than semantic relatedness computed from Wikipedia's plain link structure alone and ii that not all navigational paths are equally useful. Intelligent selection based on path characteristics can improve accuracy. The authors' work makes an argument for expanding the existing arsenal of data sources for calculating semantic relatedness and to consider the utility of human navigational paths for this task.</div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>In this article, the authors present a novel approach for computing semantic [[relatedness]] and conduct a large-scale study of it on [[Wikipedia]]. Unlike existing semantic analysis methods that utilize Wikipedia's content or link structure, the authors propose to use human navigational paths on Wikipedia for this task. The authors obtain 1.8 million human navigational paths from a semi-controlled navigation experiment-a Wikipedia-based navigation game, in which users are required to find short paths between two articles in a given Wikipedia article network. The authors' results are intriguing: They suggest that i semantic relatedness computed from human navigational paths may be more precise than semantic relatedness computed from Wikipedia's plain link structure alone and ii that not all navigational paths are equally useful. Intelligent selection based on path characteristics can improve accuracy. The authors' work makes an argument for expanding the existing arsenal of data sources for calculating semantic relatedness and to consider the utility of human navigational paths for this task.</div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"></ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">== Embed ==</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">=== Wikipedia Quality ===</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"><code></ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"><nowiki></ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">Singer, Philipp; Niebler, Thomas; Strohmaier, Markus; Hotho, Andreas. (2013). "[[Computing Semantic Relatedness from Human Navigational Paths: a Case Study on Wikipedia]]". IGI Global. DOI: 10.4018/ijswis.2013100103. </ins></div></td></tr>
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<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"><code></ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"><nowiki></ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">{{cite journal |last1=Singer |first1=Philipp |last2=Niebler |first2=Thomas |last3=Strohmaier |first3=Markus |last4=Hotho |first4=Andreas |title=Computing Semantic Relatedness from Human Navigational Paths: a Case Study on Wikipedia |date=2013 |doi=10.4018/ijswis.2013100103 |url=https://wikipediaquality.com/wiki/Computing_Semantic_Relatedness_from_Human_Navigational_Paths:_a_Case_Study_on_Wikipedia |journal=IGI Global}}</ins></div></td></tr>
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<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"><code></ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;"><nowiki></ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">Singer, Philipp; Niebler, Thomas; Strohmaier, Markus; Hotho, Andreas. (2013). &amp;quot;<a href="https://wikipediaquality.com/wiki/Computing_Semantic_Relatedness_from_Human_Navigational_Paths:_a_Case_Study_on_Wikipedia">Computing Semantic Relatedness from Human Navigational Paths: a Case Study on Wikipedia</a>&amp;quot;. IGI Global. DOI: 10.4018/ijswis.2013100103. </ins></div></td></tr>
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</table>Elianahttps://wikipediaquality.com/index.php?title=Computing_Semantic_Relatedness_from_Human_Navigational_Paths:_a_Case_Study_on_Wikipedia&diff=19225&oldid=prevHazel: infobox2019-07-18T20:27:05Z<p>infobox</p>
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<td colspan="2" style="background-color: white; color:black; text-align: center;">Revision as of 20:27, 18 July 2019</td>
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<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">{{Infobox work</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">| title = Computing Semantic Relatedness from Human Navigational Paths: a Case Study on Wikipedia</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">| date = 2013</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">| authors = [[Philipp Singer]]<br />[[Thomas Niebler]]<br />[[Markus Strohmaier]]<br />[[Andreas Hotho]]</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">| doi = 10.4018/ijswis.2013100103</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">| link = https://www.igi-global.com/article/computing-semantic-relatedness-from-human-navigational-paths-a-case-study-on-wikipedia/102707</ins></div></td></tr>
<tr><td colspan="2"> </td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div><ins style="font-weight: bold; text-decoration: none;">}}</ins></div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>'''Computing Semantic Relatedness from Human Navigational Paths: a Case Study on Wikipedia''' - scientific work related to [[Wikipedia quality]] published in 2013, written by [[Philipp Singer]], [[Thomas Niebler]], [[Markus Strohmaier]] and [[Andreas Hotho]].</div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>'''Computing Semantic Relatedness from Human Navigational Paths: a Case Study on Wikipedia''' - scientific work related to [[Wikipedia quality]] published in 2013, written by [[Philipp Singer]], [[Thomas Niebler]], [[Markus Strohmaier]] and [[Andreas Hotho]].</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>== Overview ==</div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>== Overview ==</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>In this article, the authors present a novel approach for computing semantic [[relatedness]] and conduct a large-scale study of it on [[Wikipedia]]. Unlike existing semantic analysis methods that utilize Wikipedia's content or link structure, the authors propose to use human navigational paths on Wikipedia for this task. The authors obtain 1.8 million human navigational paths from a semi-controlled navigation experiment-a Wikipedia-based navigation game, in which users are required to find short paths between two articles in a given Wikipedia article network. The authors' results are intriguing: They suggest that i semantic relatedness computed from human navigational paths may be more precise than semantic relatedness computed from Wikipedia's plain link structure alone and ii that not all navigational paths are equally useful. Intelligent selection based on path characteristics can improve accuracy. The authors' work makes an argument for expanding the existing arsenal of data sources for calculating semantic relatedness and to consider the utility of human navigational paths for this task.</div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>In this article, the authors present a novel approach for computing semantic [[relatedness]] and conduct a large-scale study of it on [[Wikipedia]]. Unlike existing semantic analysis methods that utilize Wikipedia's content or link structure, the authors propose to use human navigational paths on Wikipedia for this task. The authors obtain 1.8 million human navigational paths from a semi-controlled navigation experiment-a Wikipedia-based navigation game, in which users are required to find short paths between two articles in a given Wikipedia article network. The authors' results are intriguing: They suggest that i semantic relatedness computed from human navigational paths may be more precise than semantic relatedness computed from Wikipedia's plain link structure alone and ii that not all navigational paths are equally useful. Intelligent selection based on path characteristics can improve accuracy. The authors' work makes an argument for expanding the existing arsenal of data sources for calculating semantic relatedness and to consider the utility of human navigational paths for this task.</div></td></tr>
</table>Hazelhttps://wikipediaquality.com/index.php?title=Computing_Semantic_Relatedness_from_Human_Navigational_Paths:_a_Case_Study_on_Wikipedia&diff=18823&oldid=prevLillian: Adding wikilinks2019-07-12T06:56:47Z<p>Adding wikilinks</p>
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<td colspan="2" style="background-color: white; color:black; text-align: center;">Revision as of 06:56, 12 July 2019</td>
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<tr><td class='diff-marker'>−</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>'''Computing Semantic Relatedness from Human Navigational Paths: a Case Study on Wikipedia''' - scientific work related to Wikipedia quality published in 2013, written by Philipp Singer, Thomas Niebler, Markus Strohmaier and Andreas Hotho.</div></td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>'''Computing Semantic Relatedness from Human Navigational Paths: a Case Study on Wikipedia''' - scientific work related to <ins class="diffchange diffchange-inline">[[</ins>Wikipedia quality<ins class="diffchange diffchange-inline">]] </ins>published in 2013, written by <ins class="diffchange diffchange-inline">[[</ins>Philipp Singer<ins class="diffchange diffchange-inline">]]</ins>, <ins class="diffchange diffchange-inline">[[</ins>Thomas Niebler<ins class="diffchange diffchange-inline">]]</ins>, <ins class="diffchange diffchange-inline">[[</ins>Markus Strohmaier<ins class="diffchange diffchange-inline">]] </ins>and <ins class="diffchange diffchange-inline">[[</ins>Andreas Hotho<ins class="diffchange diffchange-inline">]]</ins>.</div></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"></td></tr>
<tr><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>== Overview ==</div></td><td class='diff-marker'> </td><td style="background-color: #f9f9f9; color: #333333; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #e6e6e6; vertical-align: top; white-space: pre-wrap;"><div>== Overview ==</div></td></tr>
<tr><td class='diff-marker'>−</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #ffe49c; vertical-align: top; white-space: pre-wrap;"><div>In this article, the authors present a novel approach for computing semantic relatedness and conduct a large-scale study of it on Wikipedia. Unlike existing semantic analysis methods that utilize Wikipedia's content or link structure, the authors propose to use human navigational paths on Wikipedia for this task. The authors obtain 1.8 million human navigational paths from a semi-controlled navigation experiment-a Wikipedia-based navigation game, in which users are required to find short paths between two articles in a given Wikipedia article network. The authors' results are intriguing: They suggest that i semantic relatedness computed from human navigational paths may be more precise than semantic relatedness computed from Wikipedia's plain link structure alone and ii that not all navigational paths are equally useful. Intelligent selection based on path characteristics can improve accuracy. The authors' work makes an argument for expanding the existing arsenal of data sources for calculating semantic relatedness and to consider the utility of human navigational paths for this task.</div></td><td class='diff-marker'>+</td><td style="color:black; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #a3d3ff; vertical-align: top; white-space: pre-wrap;"><div>In this article, the authors present a novel approach for computing semantic <ins class="diffchange diffchange-inline">[[</ins>relatedness<ins class="diffchange diffchange-inline">]] </ins>and conduct a large-scale study of it on <ins class="diffchange diffchange-inline">[[</ins>Wikipedia<ins class="diffchange diffchange-inline">]]</ins>. Unlike existing semantic analysis methods that utilize Wikipedia's content or link structure, the authors propose to use human navigational paths on Wikipedia for this task. The authors obtain 1.8 million human navigational paths from a semi-controlled navigation experiment-a Wikipedia-based navigation game, in which users are required to find short paths between two articles in a given Wikipedia article network. The authors' results are intriguing: They suggest that i semantic relatedness computed from human navigational paths may be more precise than semantic relatedness computed from Wikipedia's plain link structure alone and ii that not all navigational paths are equally useful. Intelligent selection based on path characteristics can improve accuracy. The authors' work makes an argument for expanding the existing arsenal of data sources for calculating semantic relatedness and to consider the utility of human navigational paths for this task.</div></td></tr>
</table>Lillianhttps://wikipediaquality.com/index.php?title=Computing_Semantic_Relatedness_from_Human_Navigational_Paths:_a_Case_Study_on_Wikipedia&diff=18453&oldid=prevCamila: Computing Semantic Relatedness from Human Navigational Paths: a Case Study on Wikipedia - creating a new article2019-07-06T15:03:31Z<p>Computing Semantic Relatedness from Human Navigational Paths: a Case Study on Wikipedia - creating a new article</p>
<p><b>New page</b></p><div>'''Computing Semantic Relatedness from Human Navigational Paths: a Case Study on Wikipedia''' - scientific work related to Wikipedia quality published in 2013, written by Philipp Singer, Thomas Niebler, Markus Strohmaier and Andreas Hotho.<br />
<br />
== Overview ==<br />
In this article, the authors present a novel approach for computing semantic relatedness and conduct a large-scale study of it on Wikipedia. Unlike existing semantic analysis methods that utilize Wikipedia's content or link structure, the authors propose to use human navigational paths on Wikipedia for this task. The authors obtain 1.8 million human navigational paths from a semi-controlled navigation experiment-a Wikipedia-based navigation game, in which users are required to find short paths between two articles in a given Wikipedia article network. The authors' results are intriguing: They suggest that i semantic relatedness computed from human navigational paths may be more precise than semantic relatedness computed from Wikipedia's plain link structure alone and ii that not all navigational paths are equally useful. Intelligent selection based on path characteristics can improve accuracy. The authors' work makes an argument for expanding the existing arsenal of data sources for calculating semantic relatedness and to consider the utility of human navigational paths for this task.</div>Camila