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500N-KPCrowd - Revision history
2026-11-02T02:50:30Z
Revision history for this page on the wiki
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https://www.hlt.inesc-id.pt/wiki/index.php?title=500N-KPCrowd&diff=7980&oldid=prev
Ldsm: /* Further Reading */
2017-07-22T18:37:26Z
<p><span dir="auto"><span class="autocomment">Further Reading</span></span></p>
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 18:37, 22 July 2017</td>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>The corpus is free for non-commercial use. </div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>The corpus is free for non-commercial use. </div></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; 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><del style="font-weight: bold; text-decoration: none;"></del></div></td><td colspan="2" class="diff-side-added"></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; 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><del style="font-weight: bold; text-decoration: none;">Please contact '''Luis Marujo''' for other uses.</del></div></td><td colspan="2" class="diff-side-added"></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Please cite this paper if you write any paper using the data below:</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Please cite this paper if you write any paper using the data below:</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Luis Marujo and Anatole Gershman and Jaime Carbonell and Robert Frederking and João Paulo da Silva Neto, '''Supervised Topical Key Phrase Extraction of News Stories using Crowdsourcing, Light Filtering and Co-reference Normalization''', 8th International Conference on Language Resources and Evaluation (LREC 2012), May. 2012 , ELRA. [http://www.inesc-id.pt/ficheiros/publicacoes/8262.pdf pdf] [http://www.inesc-id.pt/intranet/publicacoes/bibtex.php?bibtex=8262 bibTeX]</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Luis Marujo and Anatole Gershman and Jaime Carbonell and Robert Frederking and João Paulo da Silva Neto, '''Supervised Topical Key Phrase Extraction of News Stories using Crowdsourcing, Light Filtering and Co-reference Normalization''', 8th International Conference on Language Resources and Evaluation (LREC 2012), May. 2012 , ELRA. [http://www.inesc-id.pt/ficheiros/publicacoes/8262.pdf pdf] [http://www.inesc-id.pt/intranet/publicacoes/bibtex.php?bibtex=8262 bibTeX]</div></td></tr>
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Ldsm
https://www.hlt.inesc-id.pt/wiki/index.php?title=500N-KPCrowd&diff=7979&oldid=prev
Ldsm: /* Download */
2017-07-22T18:37:00Z
<p><span dir="auto"><span class="autocomment">Download</span></span></p>
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 18:37, 22 July 2017</td>
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Luis Marujo and Anatole Gershman and Jaime Carbonell and Robert Frederking and João Paulo da Silva Neto, '''Supervised Topical Key Phrase Extraction of News Stories using Crowdsourcing, Light Filtering and Co-reference Normalization''', 8th International Conference on Language Resources and Evaluation (LREC 2012), May. 2012 , ELRA. [http://www.inesc-id.pt/ficheiros/publicacoes/8262.pdf pdf] [http://www.inesc-id.pt/intranet/publicacoes/bibtex.php?bibtex=8262 bibTeX]</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>Luis Marujo and Anatole Gershman and Jaime Carbonell and Robert Frederking and João Paulo da Silva Neto, '''Supervised Topical Key Phrase Extraction of News Stories using Crowdsourcing, Light Filtering and Co-reference Normalization''', 8th International Conference on Language Resources and Evaluation (LREC 2012), May. 2012 , ELRA. [http://www.inesc-id.pt/ficheiros/publicacoes/8262.pdf pdf] [http://www.inesc-id.pt/intranet/publicacoes/bibtex.php?bibtex=8262 bibTeX]</div></td></tr>
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<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; 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><del style="font-weight: bold; text-decoration: none;">== Download ==</del></div></td><td colspan="2" class="diff-side-added"></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; 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><del style="font-weight: bold; text-decoration: none;">Contact author</del></div></td><td colspan="2" class="diff-side-added"></td></tr>
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Ldsm
https://www.hlt.inesc-id.pt/wiki/index.php?title=500N-KPCrowd&diff=7977&oldid=prev
Ldsm at 18:32, 22 July 2017
2017-07-22T18:32:37Z
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<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Download ==</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Download ==</div></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; 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><del style="font-weight: bold; text-decoration: none;">[http://www.l2f.inesc-id.pt/~ldsm/500N-KPCrowd.zip 500N-KPCrowd]</del></div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; 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;">Contact author</ins></div></td></tr>
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Ldsm
https://www.hlt.inesc-id.pt/wiki/index.php?title=500N-KPCrowd&diff=7197&oldid=prev
Ldsm at 00:43, 19 December 2013
2013-12-19T00:43:44Z
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 00:43, 19 December 2013</td>
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<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; 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>'''500M-KPCrowd''' corpus <del style="font-weight: bold; text-decoration: none;">is </del>made of 500 <del style="font-weight: bold; text-decoration: none;">News </del>articles (50 stories for each of the 10 categories selected) manually annotated with Key Phrases by 20 Amazon's Mechanical Turk workers. </div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; 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>'''500M-KPCrowd''' <ins style="font-weight: bold; text-decoration: none;">is a </ins>corpus made of 500 <ins style="font-weight: bold; text-decoration: none;">news </ins>articles (50 stories for each of the 10 categories selected) manually annotated with Key Phrases by 20 Amazon's Mechanical Turk workers. </div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; 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>The news articles were retrieved from <del style="font-weight: bold; text-decoration: none;">the </del>online news sources.</div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; 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>The news articles were retrieved from online news sources.</div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Statistics ==</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Statistics ==</div></td></tr>
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Ldsm
https://www.hlt.inesc-id.pt/wiki/index.php?title=500N-KPCrowd&diff=7113&oldid=prev
Ldsm at 18:32, 10 September 2013
2013-09-10T18:32:36Z
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 18:32, 10 September 2013</td>
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<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; 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>500M-KPCrowd corpus is made of 500 News articles (50 stories for each of the 10 categories selected) manually annotated with Key Phrases by 20 Amazon's Mechanical Turk workers. </div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; 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>500M-KPCrowd<ins style="font-weight: bold; text-decoration: none;">''' </ins>corpus is made of 500 News articles (50 stories for each of the 10 categories selected) manually annotated with Key Phrases by 20 Amazon's Mechanical Turk workers. </div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>The news articles were retrieved from the online news sources.</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>The news articles were retrieved from the online news sources.</div></td></tr>
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Ldsm
https://www.hlt.inesc-id.pt/wiki/index.php?title=500N-KPCrowd&diff=7112&oldid=prev
Ldsm at 18:32, 10 September 2013
2013-09-10T18:32:17Z
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 18:32, 10 September 2013</td>
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<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; 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>500M-KPCrowd corpus is made of 500 News articles (50 stories for each of the 10 categories) manually annotated with Key Phrases by 20 Amazon Mechanical Turk workers. </div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; 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>500M-KPCrowd corpus is made of 500 News articles (50 stories for each of the 10 categories <ins style="font-weight: bold; text-decoration: none;">selected</ins>) manually annotated with Key Phrases by 20 Amazon<ins style="font-weight: bold; text-decoration: none;">'s </ins>Mechanical Turk workers. </div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker" data-marker="−"></td><td style="color: #202122; 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>The news articles were retrieved from the <del style="font-weight: bold; text-decoration: none;">WWW and are e</del></div></td><td class="diff-marker" data-marker="+"></td><td style="color: #202122; 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>The news articles were retrieved from the <ins style="font-weight: bold; text-decoration: none;">online news sources.</ins></div></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><br></td></tr>
<tr><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Statistics ==</div></td><td class="diff-marker"></td><td style="background-color: #f8f9fa; color: #202122; font-size: 88%; border-style: solid; border-width: 1px 1px 1px 4px; border-radius: 0.33em; border-color: #eaecf0; vertical-align: top; white-space: pre-wrap;"><div>== Statistics ==</div></td></tr>
</table>
Ldsm
https://www.hlt.inesc-id.pt/wiki/index.php?title=500N-KPCrowd&diff=7111&oldid=prev
Ldsm: Created page with "500M-KPCrowd corpus is made of 500 News articles (50 stories for each of the 10 categories) manually annotated with Key Phrases by 20 Amazon Mechanical Turk workers. The news a..."
2013-09-10T18:30:39Z
<p>Created page with "500M-KPCrowd corpus is made of 500 News articles (50 stories for each of the 10 categories) manually annotated with Key Phrases by 20 Amazon Mechanical Turk workers. The news a..."</p>
<p><b>New page</b></p><div>500M-KPCrowd corpus is made of 500 News articles (50 stories for each of the 10 categories) manually annotated with Key Phrases by 20 Amazon Mechanical Turk workers. <br />
<br />
The news articles were retrieved from the WWW and are e<br />
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== Statistics ==<br />
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* Number of stories: 450 / 50 (Train / Test)<br />
* Average number of Amazon Mechanical Turk workers per news: 20<br />
* Number of Topics: 10<br />
* Average Number of Key Phrases per news story: 40<br />
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== Further Reading ==<br />
The corpus is free for non-commercial use. <br />
<br />
Please contact '''Luis Marujo''' for other uses.<br />
<br />
Please cite this paper if you write any paper using the data below:<br />
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Luis Marujo and Anatole Gershman and Jaime Carbonell and Robert Frederking and João Paulo da Silva Neto, '''Supervised Topical Key Phrase Extraction of News Stories using Crowdsourcing, Light Filtering and Co-reference Normalization''', 8th International Conference on Language Resources and Evaluation (LREC 2012), May. 2012 , ELRA. [http://www.inesc-id.pt/ficheiros/publicacoes/8262.pdf pdf] [http://www.inesc-id.pt/intranet/publicacoes/bibtex.php?bibtex=8262 bibTeX]<br />
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== Download ==<br />
[http://www.l2f.inesc-id.pt/~ldsm/500N-KPCrowd.zip 500N-KPCrowd]</div>
Ldsm