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Interactive Visualization of Correlations in High-Dimensional Streams - Versionsgeschichte
2024-03-29T12:53:37Z
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Uhelt@student.kit.edu am 3. Juni 2019 um 08:42 Uhr
2019-06-03T08:42:51Z
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Version vom 3. Juni 2019, 09:42 Uhr</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>|vortragender=Yimin Zhang</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>|vortragender=Yimin Zhang</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>|email=uhelt@student.kit.edu</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>|email=uhelt@student.kit.edu</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>|vortragstyp=<del style="font-weight: bold; text-decoration: none;">Proposal</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>|vortragstyp=<ins style="font-weight: bold; text-decoration: none;">Bachelorarbeit</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>|betreuer=Edouard Fouché</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>|betreuer=Edouard Fouché</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>|termin=Institutsseminar/<del style="font-weight: bold; text-decoration: none;">2018</del>-<del style="font-weight: bold; text-decoration: none;">10</del>-<del style="font-weight: bold; text-decoration: none;">26</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>|termin=Institutsseminar/<ins style="font-weight: bold; text-decoration: none;">2019</ins>-<ins style="font-weight: bold; text-decoration: none;">07</ins>-<ins style="font-weight: bold; text-decoration: none;">19</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>|kurzfassung=Correlation analysis aims at discovering and summarizing the relationship between the attributes of a data set. For example, in financial markets, the price of stocks evolves over time. Via a careful estimation of the relationship between stocks, one can try to predict which stock to buy or sell to maximize the wealth of a portfolio. </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>|kurzfassung=Correlation analysis aims at discovering and summarizing the relationship between the attributes of a data set. For example, in financial markets, the price of stocks evolves over time. Via a careful estimation of the relationship between stocks, one can try to predict which stock to buy or sell to maximize the wealth of a portfolio. </div></td></tr>
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Uhelt@student.kit.edu
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Uhelt@student.kit.edu am 18. Oktober 2018 um 19:06 Uhr
2018-10-18T19:06:01Z
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Version vom 18. Oktober 2018, 20:06 Uhr</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>|termin=Institutsseminar/2018-10-26</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>|termin=Institutsseminar/2018-10-26</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>|kurzfassung=Correlation analysis aims at discovering and summarizing the relationship between the attributes of a data set. For example, in financial markets, the price of stocks evolves over time. Via a careful estimation of the relationship between stocks, one can try to predict which stock to buy or sell to maximize the wealth of a portfolio. </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>|kurzfassung=Correlation analysis aims at discovering and summarizing the relationship between the attributes of a data set. For example, in financial markets, the price of stocks evolves over time. Via a careful estimation of the relationship between stocks, one can try to predict which stock to buy or sell to maximize the wealth of a portfolio. </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>The standard tool of correlation analysis is the computation of a correlation matrix. However, in the case of streams with many dimensions, it is difficult to extract actionable insights from the correlation matrix, as the number of pairs of attributes increases quadratically and the coefficients evolve over time in unforeseen ways. Thus, novel visualization methods are required. </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> </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>The standard tool of correlation analysis is the computation of a correlation matrix. However, in the case of streams with many dimensions, it is difficult to extract actionable insights from the correlation matrix, as the number of pairs of attributes increases quadratically and the coefficients evolve over time in unforeseen ways. Thus, novel visualization methods are required.</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;"> </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>In this thesis, we will investigate how to visualize the evolution of correlation in high-dimensional data streams in an intuitive way. We will, for example, discuss visualization methods based on force-directed graphs. Also, we will develop a web interface to visualize the correlation structure of data streams and evaluate it systematically via user studies.</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>In this thesis, we will investigate how to visualize the evolution of correlation in high-dimensional data streams in an intuitive way. We will, for example, discuss visualization methods based on force-directed graphs. Also, we will develop a web interface to visualize the correlation structure of data streams and evaluate it systematically via user studies.</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>}}</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>}}</div></td></tr>
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Uhelt@student.kit.edu
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Uhelt@student.kit.edu am 18. Oktober 2018 um 19:05 Uhr
2018-10-18T19:05:13Z
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Version vom 18. Oktober 2018, 20:05 Uhr</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>|betreuer=Edouard Fouché</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>|betreuer=Edouard Fouché</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>|termin=Institutsseminar/2018-10-26</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>|termin=Institutsseminar/2018-10-26</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>|kurzfassung=<del style="font-weight: bold; text-decoration: none;">One </del>of the <del style="font-weight: bold; text-decoration: none;">main challenges about data mining </del>is to <del style="font-weight: bold; text-decoration: none;">analyse </del>the <del style="font-weight: bold; text-decoration: none;">high-dimensional data streams</del>. In this thesis, we <del style="font-weight: bold; text-decoration: none;">would get a deep understanding </del>of correlation <del style="font-weight: bold; text-decoration: none;">analysis and become familiar with </del>high-dimensional data streams. <del style="font-weight: bold; text-decoration: none;">What´s more</del>, we <del style="font-weight: bold; text-decoration: none;">try </del>to visualize <del style="font-weight: bold; text-decoration: none;">these highly valuable </del>data <del style="font-weight: bold; text-decoration: none;">sets through a webservice </del>and evaluate it.</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>|kurzfassung=<ins style="font-weight: bold; text-decoration: none;">Correlation analysis aims at discovering and summarizing the relationship between the attributes of a data set. For example, in financial markets, the price of stocks evolves over time. Via a careful estimation of the relationship between stocks, one can try to predict which stock to buy or sell to maximize the wealth of a portfolio. </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;">The standard tool of correlation analysis is the computation </ins>of <ins style="font-weight: bold; text-decoration: none;">a correlation matrix. However, in </ins>the <ins style="font-weight: bold; text-decoration: none;">case of streams with many dimensions, it </ins>is <ins style="font-weight: bold; text-decoration: none;">difficult </ins>to <ins style="font-weight: bold; text-decoration: none;">extract actionable insights from the correlation matrix, as the number of pairs of attributes increases quadratically and </ins>the <ins style="font-weight: bold; text-decoration: none;">coefficients evolve over time in unforeseen ways. Thus, novel visualization methods are required</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>In this thesis, we <ins style="font-weight: bold; text-decoration: none;">will investigate how to visualize the evolution </ins>of correlation <ins style="font-weight: bold; text-decoration: none;">in </ins>high-dimensional data streams <ins style="font-weight: bold; text-decoration: none;">in an intuitive way. We will, for example, discuss visualization methods based on force-directed graphs</ins>. <ins style="font-weight: bold; text-decoration: none;">Also</ins>, we <ins style="font-weight: bold; text-decoration: none;">will develop a web interface </ins>to visualize <ins style="font-weight: bold; text-decoration: none;">the correlation structure of </ins>data <ins style="font-weight: bold; text-decoration: none;">streams </ins>and evaluate it <ins style="font-weight: bold; text-decoration: none;">systematically via user studies</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>}}</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>}}</div></td></tr>
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Uhelt@student.kit.edu
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Uhelt@student.kit.edu am 9. Oktober 2018 um 20:36 Uhr
2018-10-09T20:36:29Z
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Version vom 9. Oktober 2018, 21:36 Uhr</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>|vortragstyp=Proposal</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>|vortragstyp=Proposal</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>|betreuer=Edouard Fouché</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>|betreuer=Edouard Fouché</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>|termin=Institutsseminar/2018-10-<del style="font-weight: bold; text-decoration: none;">19</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>|termin=Institutsseminar/2018-10-<ins style="font-weight: bold; text-decoration: none;">26</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>|kurzfassung=One of the main challenges about data mining is to analyse the high-dimensional data streams. In this thesis, we would get a deep understanding of correlation analysis and become familiar with high-dimensional data streams. What´s more, we try to visualize these highly valuable data sets through a webservice and evaluate it.</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>|kurzfassung=One of the main challenges about data mining is to analyse the high-dimensional data streams. In this thesis, we would get a deep understanding of correlation analysis and become familiar with high-dimensional data streams. What´s more, we try to visualize these highly valuable data sets through a webservice and evaluate it.</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>}}</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>}}</div></td></tr>
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Uhelt@student.kit.edu
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Uhelt@student.kit.edu: Uhelt@student.kit.edu verschob die Seite IPD-Institutsseminar:Interactive Visualization of Correlations in High-Dimensional Streams nach Interactive Visualization of Correlations in High-Dimensional Streams
2018-10-08T14:09:47Z
<p>Uhelt@student.kit.edu verschob die Seite <a href="/mediawiki-institutsseminar/index.php?title=IPD-Institutsseminar:Interactive_Visualization_of_Correlations_in_High-Dimensional_Streams&action=edit&redlink=1" class="new" title="IPD-Institutsseminar:Interactive Visualization of Correlations in High-Dimensional Streams (Seite nicht vorhanden)">IPD-Institutsseminar:Interactive Visualization of Correlations in High-Dimensional Streams</a> nach <a href="/institutsseminar/Interactive_Visualization_of_Correlations_in_High-Dimensional_Streams" title="Interactive Visualization of Correlations in High-Dimensional Streams">Interactive Visualization of Correlations in High-Dimensional Streams</a></p>
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<td colspan="1" style="background-color: #fff; color: #202122; text-align: center;">← Nächstältere Version</td>
<td colspan="1" style="background-color: #fff; color: #202122; text-align: center;">Version vom 8. Oktober 2018, 15:09 Uhr</td>
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Uhelt@student.kit.edu
https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Interactive_Visualization_of_Correlations_in_High-Dimensional_Streams&diff=751&oldid=prev
Uhelt@student.kit.edu: Uhelt@student.kit.edu verschob die Seite Institutsseminar/2018-Oktober-19 nach IPD-Institutsseminar:Interactive Visualization of Correlations in High-Dimensional Streams: Titel ändern
2018-10-08T14:09:03Z
<p>Uhelt@student.kit.edu verschob die Seite <a href="/institutsseminar/Institutsseminar/2018-Oktober-19" class="mw-redirect" title="Institutsseminar/2018-Oktober-19">Institutsseminar/2018-Oktober-19</a> nach <a href="/mediawiki-institutsseminar/index.php?title=IPD-Institutsseminar:Interactive_Visualization_of_Correlations_in_High-Dimensional_Streams&action=edit&redlink=1" class="new" title="IPD-Institutsseminar:Interactive Visualization of Correlations in High-Dimensional Streams (Seite nicht vorhanden)">IPD-Institutsseminar:Interactive Visualization of Correlations in High-Dimensional Streams</a>: Titel ändern</p>
<table style="background-color: #fff; color: #202122;" data-mw="interface">
<tr class="diff-title" lang="de">
<td colspan="1" style="background-color: #fff; color: #202122; text-align: center;">← Nächstältere Version</td>
<td colspan="1" style="background-color: #fff; color: #202122; text-align: center;">Version vom 8. Oktober 2018, 15:09 Uhr</td>
</tr><tr><td colspan="2" class="diff-notice" lang="de"><div class="mw-diff-empty">(kein Unterschied)</div>
</td></tr></table>
Uhelt@student.kit.edu
https://sdq.kastel.kit.edu/mediawiki-institutsseminar/index.php?title=Interactive_Visualization_of_Correlations_in_High-Dimensional_Streams&diff=750&oldid=prev
Uhelt@student.kit.edu: Die Seite wurde neu angelegt: „{{Vortrag |vortragender=Yimin Zhang |email=uhelt@student.kit.edu |vortragstyp=Proposal |betreuer=Edouard Fouché |termin=Institutsseminar/2018-10-19 |kurzfassu…“
2018-10-08T14:01:09Z
<p>Die Seite wurde neu angelegt: „{{Vortrag |vortragender=Yimin Zhang |email=uhelt@student.kit.edu |vortragstyp=Proposal |betreuer=Edouard Fouché |termin=Institutsseminar/2018-10-19 |kurzfassu…“</p>
<p><b>Neue Seite</b></p><div>{{Vortrag<br />
|vortragender=Yimin Zhang<br />
|email=uhelt@student.kit.edu<br />
|vortragstyp=Proposal<br />
|betreuer=Edouard Fouché<br />
|termin=Institutsseminar/2018-10-19<br />
|kurzfassung=One of the main challenges about data mining is to analyse the high-dimensional data streams. In this thesis, we would get a deep understanding of correlation analysis and become familiar with high-dimensional data streams. What´s more, we try to visualize these highly valuable data sets through a webservice and evaluate it.<br />
}}</div>
Uhelt@student.kit.edu