Proceedings of the 2014 SIAM International Conference on Data Mining:
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 algori...
Gespeichert in:
| Weitere Verfasser: | , , , , , |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Philadelphia, Pennsylvania
Society for Industrial and Applied Mathematics (SIAM, 3600 Market Street, Floor 6, Philadelphia, PA 19104)
[2014]
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| Schlagworte: | |
| Online-Zugang: | TUM01 UBW01 UBY01 UER01 URL des Erstveröffentlichers |
| Zusammenfassung: | 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 |
| Beschreibung: | 1 Online-Ressource (xi, 1086 Seiten) Illustrationen |
| ISBN: | 9781611973440 |
| DOI: | 10.1137/1.9781611973440 |
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| spelling | Proceedings of the 2014 SIAM International Conference on Data Mining Mohammed Zaki, Zoran Obradovic, Pang Ning Tan, Arindam Banerjee, Chandrika Kamath and Srinivasan Parthasarathy, editors Philadelphia, Pennsylvania Society for Industrial and Applied Mathematics (SIAM, 3600 Market Street, Floor 6, Philadelphia, PA 19104) [2014] 1 Online-Ressource (xi, 1086 Seiten) Illustrationen txt rdacontent c rdamedia cr rdacarrier 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 Data mining ; Congresses Discrete mathematics and graph theory (DE-588)1071861417 Konferenzschrift gnd-content Zaki, Mohammed J. 1971- (DE-588)121766799 edt Obradovic, Zoran edt Tan, Pang-Ning (DE-588)1121324711 edt Banerjee, Arindam (DE-588)1192707273 edt Kamath, Chandrika (DE-588)138409420 edt Parthasarathy, Srinivasan (DE-588)1146804466 edt Erscheint auch als Druck-Ausgabe 978-1-61197-344-0 https://doi.org/10.1137/1.9781611973440 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Proceedings of the 2014 SIAM International Conference on Data Mining |
| subject_GND | (DE-588)1071861417 |
| title | Proceedings of the 2014 SIAM International Conference on Data Mining |
| title_auth | Proceedings of the 2014 SIAM International Conference on Data Mining |
| title_exact_search | Proceedings of the 2014 SIAM International Conference on Data Mining |
| title_exact_search_txtP | Proceedings of the 2014 SIAM International Conference on Data Mining |
| title_full | Proceedings of the 2014 SIAM International Conference on Data Mining Mohammed Zaki, Zoran Obradovic, Pang Ning Tan, Arindam Banerjee, Chandrika Kamath and Srinivasan Parthasarathy, editors |
| title_fullStr | Proceedings of the 2014 SIAM International Conference on Data Mining Mohammed Zaki, Zoran Obradovic, Pang Ning Tan, Arindam Banerjee, Chandrika Kamath and Srinivasan Parthasarathy, editors |
| title_full_unstemmed | Proceedings of the 2014 SIAM International Conference on Data Mining Mohammed Zaki, Zoran Obradovic, Pang Ning Tan, Arindam Banerjee, Chandrika Kamath and Srinivasan Parthasarathy, editors |
| title_short | Proceedings of the 2014 SIAM International Conference on Data Mining |
| title_sort | proceedings of the 2014 siam international conference on data mining |
| topic_facet | Konferenzschrift |
| url | https://doi.org/10.1137/1.9781611973440 |
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