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Knowledge Discovery in Databases (KDD) - Revision history
2024-03-28T22:17:17Z
Revision history for this page on the wiki
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Iwolf at 09:23, 9 October 2007
2007-10-09T09:23:28Z
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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>{{Quotation|'''KDD''' refers to the overall process of discovering useful knowledge from data, and [[Data Mining|data mining]] refers to a particular step in this process. <br>[...]<br>The basic problem addressed by the '''KDD''' process is one of mapping low-level data into other forms that might be more compact, more abstract, or more useful.<br>[...]<br>KDD focuses on the overall process of knowledge discovery from data, including how the data are stored and accessed, how algorithms can be scaled to massive data sets ultimate and still run efficiently, how results can be interpreted and visualized, and how the overall man-machine interaction can usefully be modeled and supported.|[Fayyad et al., 1996]}}</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>{{Quotation|'''KDD''' refers to the overall process of discovering useful knowledge from data, and [[Data Mining|data mining]] refers to a particular step in this process. <br>[...]<br>The basic problem addressed by the '''KDD''' process is one of mapping low-level data into other forms that might be more compact, more abstract, or more useful.<br>[...]<br>KDD focuses on the overall process of knowledge discovery from data, including how the data are stored and accessed, how algorithms can be scaled to massive data sets ultimate and still run efficiently, how results can be interpreted and visualized, and how the overall man-machine interaction can usefully be modeled and supported.|[Fayyad et al., 1996]}}</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;">[[Image:Fayyad96kdd-process.png|thumb|600px|An Overview of the Steps That Compose the KDD Process [dFayyad et al., 1996]]]</ins></div></td></tr>
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Iwolf
https://infovis-wiki.net/w/index.php?title=Knowledge_Discovery_in_Databases_(KDD)&diff=17150&oldid=prev
Iwolf at 09:01, 9 October 2007
2007-10-09T09:01:57Z
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<td colspan="2" style="background-color: #fff; color: #202122; text-align: center;">Revision as of 10:01, 9 October 2007</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" 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>{{Quotation|'''KDD''' refers to the overall process of discovering useful knowledge from data, and [[Data Mining|data mining]] refers to a particular step in this process. [...] The basic problem addressed by the '''KDD''' process is one of mapping low-level data into other forms that might be more compact, more abstract, or more useful.|[Fayyad et al., 1996]}}</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>{{Quotation|'''KDD''' refers to the overall process of discovering useful knowledge from data, and [[Data Mining|data mining]] refers to a particular step in this process. <ins style="font-weight: bold; text-decoration: none;"><br></ins>[...]<ins style="font-weight: bold; text-decoration: none;"><br></ins>The basic problem addressed by the '''KDD''' process is one of mapping low-level data into other forms that might be more compact, more abstract, or more useful<ins style="font-weight: bold; text-decoration: none;">.<br>[...]<br>KDD focuses on the overall process of knowledge discovery from data, including how the data are stored and accessed, how algorithms can be scaled to massive data sets ultimate and still run efficiently, how results can be interpreted and visualized, and how the overall man-machine interaction can usefully be modeled and supported</ins>.|[Fayyad et al., 1996]}}</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>== References ==</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>== References ==</div></td></tr>
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Iwolf
https://infovis-wiki.net/w/index.php?title=Knowledge_Discovery_in_Databases_(KDD)&diff=17149&oldid=prev
Iwolf at 08:59, 9 October 2007
2007-10-09T08:59:10Z
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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>{{Quotation|'''KDD''' is an integration of multiple technologies for data management such as database management and data warehousing, statistic machine learning, decision support, and others such as visualisation and parallel computing.|[De Martino et al., 2002]}}</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>{{Quotation|'''KDD''' is an integration of multiple technologies for data management such as database management and data warehousing, statistic machine learning, decision support, and others such as visualisation and parallel computing.|[De Martino et al., 2002]}}</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 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;">{{Quotation|'''KDD''' refers to the overall process of discovering useful knowledge from data, and [[Data Mining|data mining]] refers to a particular step in this process. [...] The basic problem addressed by the '''KDD''' process is one of mapping low-level data into other forms that might be more compact, more abstract, or more useful.|[Fayyad et al., 1996]}}</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>== References ==</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>== References ==</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 Martino et al., 2002] M. De Martino, A. Bertone, R. Albertoni, H. Hauska, U. Demsar, M. Dunkars. Technical Report of Data Mining, INVISIP IST-2000-29640, Information Visualisation for Site Planning, WP No2: Technology Analysis, D2.2, 28.2.2002</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 Martino et al., 2002] M. De Martino, A. Bertone, R. Albertoni, H. Hauska, U. Demsar, M. Dunkars. Technical Report of Data Mining, INVISIP IST-2000-29640, Information Visualisation for Site Planning, WP No2: Technology Analysis, D2.2, 28.2.2002</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;">*[Fayyad et al., 1996] U. Fayyad, G. P.-Shapiro, and P. Smyth. From data mining to knowledge discovery in databases. AI Magazine, 17(3):37-54, Fall 1996. http://citeseer.ist.psu.edu/fayyad96from.html </ins></div></td></tr>
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Iwolf
https://infovis-wiki.net/w/index.php?title=Knowledge_Discovery_in_Databases_(KDD)&diff=10420&oldid=prev
Iwolf at 06:29, 28 August 2006
2006-08-28T06:29:35Z
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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 Martino et al., 2002] M. De Martino, A. Bertone, R. Albertoni, H. Hauska, U. Demsar, M. Dunkars. Technical Report of Data Mining, INVISIP IST-2000-29640, Information Visualisation for Site Planning, WP No2: Technology Analysis, D2.2, 28.2.2002</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 Martino et al., 2002] M. De Martino, A. Bertone, R. Albertoni, H. Hauska, U. Demsar, M. Dunkars. Technical Report of Data Mining, INVISIP IST-2000-29640, Information Visualisation for Site Planning, WP No2: Technology Analysis, D2.2, 28.2.2002</div></td></tr>
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Iwolf
https://infovis-wiki.net/w/index.php?title=Knowledge_Discovery_in_Databases_(KDD)&diff=10419&oldid=prev
Iwolf at 06:29, 28 August 2006
2006-08-28T06:29:25Z
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<p><b>New page</b></p><div>{{Definition|'''KDD''' refers to the overall process of discovering useful knowledge from data. [De Martino et al., 2002]}}<br />
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{{Quotation|'''KDD''' is an integration of multiple technologies for data management such as database management and data warehousing, statistic machine learning, decision support, and others such as visualisation and parallel computing.|[De Martino et al., 2002]}}<br />
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== References ==<br />
*[De Martino et al., 2002] M. De Martino, A. Bertone, R. Albertoni, H. Hauska, U. Demsar, M. Dunkars. Technical Report of Data Mining, INVISIP IST-2000-29640, Information Visualisation for Site Planning, WP No2: Technology Analysis, D2.2, 28.2.2002</div>
Iwolf