Proceedings of the 2013 SIAM International Conference on Data Mining:
Gespeichert in:
| Weitere beteiligte Personen: | , , , , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | Nichtbestimmte Sprache |
| Veröffentlicht: |
Philadelphia, Pennsylvania
Society for Industrial and Applied Mathematics, SIAM
[2013]
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| Schlagwörter: | |
| Links: | https://doi.org/10.1137/1.9781611972832 https://doi.org/10.1137/1.9781611972832 https://doi.org/10.1137/1.9781611972832 https://doi.org/10.1137/1.9781611972832 https://doi.org/10.1137/1.9781611972832 |
| Abstract: | Data mining is an important tool in science, engineering, industrial processes, healthcare, business, and medicine. The datasets in these fields are large, complex, and often noisy. Extracting knowledge requires the use of sophisticated, high performance and principled analysis techniques and algorithms, based on sound theoretical and statistical foundations. These techniques in turn require implementations that are carefully tuned for performance; powerful visualization technologies; interface systems that are usable by scientists, engineers, and physicians as well as researchers; and infrastructures that support them. This conference provides a venue for researchers who are addressing these problems to present their work in a peer-reviewed forum. It also provides an ideal setting for graduate students and others new to the field to learn about cutting-edge research by hearing outstanding invited speakers and attending presentations and tutorials (included with conference registration). A set of focused workshops are also held on the last day of the conference. The proceedings of the conference arepublished in archival form, and are also made available on the SIAM web site |
| Umfang: | 1 Online-Ressource (811 Seiten) Illustrationen |
| ISBN: | 9781611972832 |
| DOI: | 10.1137/1.9781611972832 |
Internformat
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| 520 | 3 | |a Data mining is an important tool in science, engineering, industrial processes, healthcare, business, and medicine. The datasets in these fields are large, complex, and often noisy. Extracting knowledge requires the use of sophisticated, high performance and principled analysis techniques and algorithms, based on sound theoretical and statistical foundations. These techniques in turn require implementations that are carefully tuned for performance; powerful visualization technologies; interface systems that are usable by scientists, engineers, and physicians as well as researchers; and infrastructures that support them. This conference provides a venue for researchers who are addressing these problems to present their work in a peer-reviewed forum. It also provides an ideal setting for graduate students and others new to the field to learn about cutting-edge research by hearing outstanding invited speakers and attending presentations and tutorials (included with conference registration). A set of focused workshops are also held on the last day of the conference. The proceedings of the conference arepublished in archival form, and are also made available on the SIAM web site | |
| 653 | 0 | |a Data mining ; Congresses | |
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Datensatz im Suchindex
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| discipline | Informatik |
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| spellingShingle | Proceedings of the 2013 SIAM International Conference on Data Mining |
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| title | Proceedings of the 2013 SIAM International Conference on Data Mining |
| title_auth | Proceedings of the 2013 SIAM International Conference on Data Mining |
| title_exact_search | Proceedings of the 2013 SIAM International Conference on Data Mining |
| title_full | Proceedings of the 2013 SIAM International Conference on Data Mining Joydeep Ghosh , Zoran Obradovic , Jennifer Dy , Zhi-Hua Zhou , Chandrika Kamath and Srinivasan Parthasarathy, editors |
| title_fullStr | Proceedings of the 2013 SIAM International Conference on Data Mining Joydeep Ghosh , Zoran Obradovic , Jennifer Dy , Zhi-Hua Zhou , Chandrika Kamath and Srinivasan Parthasarathy, editors |
| title_full_unstemmed | Proceedings of the 2013 SIAM International Conference on Data Mining Joydeep Ghosh , Zoran Obradovic , Jennifer Dy , Zhi-Hua Zhou , Chandrika Kamath and Srinivasan Parthasarathy, editors |
| title_short | Proceedings of the 2013 SIAM International Conference on Data Mining |
| title_sort | proceedings of the 2013 siam international conference on data mining |
| topic_facet | Konferenzschrift |
| url | https://doi.org/10.1137/1.9781611972832 |
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