https://kdutch.ivdnt.org/mediawiki/index.php?title=Readability&feed=atom&action=history
Readability - Revision history
2024-03-29T07:16:09Z
Revision history for this page on the wiki
MediaWiki 1.41.0
https://kdutch.ivdnt.org/mediawiki/index.php?title=Readability&diff=6545&oldid=prev
Griet at 09:59, 16 February 2024
2024-02-16T09:59:26Z
<p></p>
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 09:59, 16 February 2024</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>==Machine learning==</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>==Machine learning==</div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></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;">The demo will process your text by deriving various text characteristics or features and predict a readability score using supervised machine learning techniques.</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" 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;">* The demo will process your text by deriving various text characteristics or features and predict a readability score using supervised machine learning techniques.</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;"><div>*[https://lt3.ugent.be/resources/machine-learning-readability/ Information]</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>*[https://lt3.ugent.be/resources/machine-learning-readability/ Information]</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;"><div>* De Clercq, Orphée and Véronique Hoste. 2016. All Mixed Up? Finding the Optimal Feature Set for General Readability Prediction and its Application to English and Dutch. Computational Linguistics, Association for Computational Linguistics, 42(3):457-490.</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>* De Clercq, Orphée and Véronique Hoste. 2016. All Mixed Up? Finding the Optimal Feature Set for General Readability Prediction and its Application to English and Dutch. Computational Linguistics, Association for Computational Linguistics, 42(3):457-490.</div></td></tr>
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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>==T-scan ==</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>==T-scan ==</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>T-Scan is an analysis tool for Dutch text, mainly focusing on text complexity.</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>T-Scan is an analysis tool for Dutch text, mainly focusing on text complexity.</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;"><div>* [https://github.com/UUDigitalHumanitieslab/tscan/raw/master/docs/tscanhandleiding.pdf Manual (in Dutch)]</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>* [https://github.com/UUDigitalHumanitieslab/tscan/raw/master/docs/tscanhandleiding.pdf Manual (in Dutch)]</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;"><div>* [https://tscan.hum.uu.nl/tscan/ Tool]</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>* [https://tscan.hum.uu.nl/tscan/ Tool]</div></td></tr>
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Griet
https://kdutch.ivdnt.org/mediawiki/index.php?title=Readability&diff=6543&oldid=prev
Griet: /* T-scan */
2024-02-16T09:57:28Z
<p><span dir="auto"><span class="autocomment">T-scan</span></span></p>
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 09:57, 16 February 2024</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>* T-Scan is an analysis tool for Dutch text, mainly focusing on text complexity.</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>* T-Scan is an analysis tool for Dutch text, mainly focusing on text complexity.</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;"><div>* [https://github.com/UUDigitalHumanitieslab/tscan/raw/master/docs/tscanhandleiding.pdf Manual (in Dutch)]</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>* [https://github.com/UUDigitalHumanitieslab/tscan/raw/master/docs/tscanhandleiding.pdf Manual (in Dutch)]</div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></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;">* [https://tscan.hum.uu.nl/tscan/ Tool]</ins></div></td></tr>
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Griet
https://kdutch.ivdnt.org/mediawiki/index.php?title=Readability&diff=6542&oldid=prev
Griet: /* Machine learning */
2024-02-16T09:57:05Z
<p><span dir="auto"><span class="autocomment">Machine learning</span></span></p>
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 09:57, 16 February 2024</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>==Machine learning==</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>==Machine learning==</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 colspan="2" class="diff-side-deleted"></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;">* The demo will process your text by deriving various text characteristics or features and predict a readability score using supervised machine learning techniques.</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;"><div>*[https://lt3.ugent.be/resources/machine-learning-readability/ Information]</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>*[https://lt3.ugent.be/resources/machine-learning-readability/ Information]</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;"><div>* De Clercq, Orphée and Véronique Hoste. 2016. All Mixed Up? Finding the Optimal Feature Set for General Readability Prediction and its Application to English and Dutch. Computational Linguistics, Association for Computational Linguistics, 42(3):457-490.</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>* De Clercq, Orphée and Véronique Hoste. 2016. All Mixed Up? Finding the Optimal Feature Set for General Readability Prediction and its Application to English and Dutch. Computational Linguistics, Association for Computational Linguistics, 42(3):457-490.</div></td></tr>
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Griet
https://kdutch.ivdnt.org/mediawiki/index.php?title=Readability&diff=6541&oldid=prev
Griet at 09:56, 16 February 2024
2024-02-16T09:56:25Z
<p></p>
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 09:56, 16 February 2024</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>* De Clercq, Orphée and Véronique Hoste. 2016. All Mixed Up? Finding the Optimal Feature Set for General Readability Prediction and its Application to English and Dutch. Computational Linguistics, Association for Computational Linguistics, 42(3):457-490.</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>* De Clercq, Orphée and Véronique Hoste. 2016. All Mixed Up? Finding the Optimal Feature Set for General Readability Prediction and its Application to English and Dutch. Computational Linguistics, Association for Computational Linguistics, 42(3):457-490.</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;"><div>*[https://lt3.ugent.be/machine-learning-readability-demo/ Demo]</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>*[https://lt3.ugent.be/machine-learning-readability-demo/ Demo]</div></td></tr>
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<tr><td colspan="2" class="diff-side-deleted"></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;">==T-scan ==</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></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;">* T-Scan is an analysis tool for Dutch text, mainly focusing on text complexity.</ins></div></td></tr>
<tr><td colspan="2" class="diff-side-deleted"></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;">* [https://github.com/UUDigitalHumanitieslab/tscan/raw/master/docs/tscanhandleiding.pdf Manual (in Dutch)]</ins></div></td></tr>
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Griet
https://kdutch.ivdnt.org/mediawiki/index.php?title=Readability&diff=6329&oldid=prev
Griet: Created page with "== Assessing readability== How to assess readability? In this demo you can assess the readability of ten texts by comparing them with each other. The idea is that you assign an absolute score - ranging from 0 (easy) to 100 (difficult) - to each text and motivate your score using the free text field. *[https://lt3.ugent.be/resources/assessing-readability/ Information] * De Clercq, Orphée and Véronique Hoste. 2016. All Mixed Up? Finding the Optimal Feature Set for Gener..."
2023-01-30T08:22:13Z
<p>Created page with "== Assessing readability== How to assess readability? In this demo you can assess the readability of ten texts by comparing them with each other. The idea is that you assign an absolute score - ranging from 0 (easy) to 100 (difficult) - to each text and motivate your score using the free text field. *[https://lt3.ugent.be/resources/assessing-readability/ Information] * De Clercq, Orphée and Véronique Hoste. 2016. All Mixed Up? Finding the Optimal Feature Set for Gener..."</p>
<p><b>New page</b></p><div>== Assessing readability==<br />
How to assess readability? In this demo you can assess the readability of ten texts by comparing them with each other. The idea is that you assign an absolute score - ranging from 0 (easy) to 100 (difficult) - to each text and motivate your score using the free text field.<br />
<br />
*[https://lt3.ugent.be/resources/assessing-readability/ Information]<br />
* De Clercq, Orphée and Véronique Hoste. 2016. All Mixed Up? Finding the Optimal Feature Set for General Readability Prediction and its Application to English and Dutch. Computational Linguistics, Association for Computational Linguistics, 42(3):457-490.<br />
*[https://lt3.ugent.be/assessing-readability-demo/ Demo]<br />
<br />
==Classical formulas==<br />
In this demo, you can enter a Dutch text of maximum 1,000 characters. The text is then analyzed: various text characteristics (word length, sentence length, TTR, ...) are outputted and different scores calculated based on classical readability formulas. In a next phase, the text is also analyzed with a syntactic parser offering insights into the grammatical complexity of the text.<br />
<br />
*[https://lt3.ugent.be/resources/classical-readability-formula-calculator/ Information]<br />
* De Clercq, Orphée and Véronique Hoste. 2016. All Mixed Up? Finding the Optimal Feature Set for General Readability Prediction and its Application to English and Dutch. Computational Linguistics, Association for Computational Linguistics, 42(3):457-490.<br />
*[https://lt3.ugent.be/readability-demo/ Demo]<br />
<br />
==Machine learning==<br />
<br />
*[https://lt3.ugent.be/resources/machine-learning-readability/ Information]<br />
* De Clercq, Orphée and Véronique Hoste. 2016. All Mixed Up? Finding the Optimal Feature Set for General Readability Prediction and its Application to English and Dutch. Computational Linguistics, Association for Computational Linguistics, 42(3):457-490.<br />
*[https://lt3.ugent.be/machine-learning-readability-demo/ Demo]</div>
Griet