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|Acronym=ICDM 2011 | |Acronym=ICDM 2011 | ||
|Title=11th IEEE International Conference on Data Mining | |Title=11th IEEE International Conference on Data Mining | ||
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|In Event Series=Event Series:ICDM | |In Event Series=Event Series:ICDM | ||
|Single Day Event=no | |Single Day Event=no | ||
|Start Date=2011/12/11 | |Start Date=2011/12/11 | ||
|End Date=2011/12/14 | |End Date=2011/12/14 | ||
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|Event Status=as scheduled | |Event Status=as scheduled | ||
|Event Mode=on site | |Event Mode=on site | ||
| + | |Venue=Marriott Pinnacle Downtown | ||
| + | |City=Vancouver | ||
| + | |Region=British Columbia | ||
| + | |Country=Country:CA | ||
| + | |Academic Field=Data Mining; Computer Science | ||
| + | |Official Website=http://webdocs.cs.ualberta.ca/~icdm2011/ | ||
| + | |Type=Conference | ||
| + | |pageCreator=Christiane | ||
| + | |pageEditor=Christiane | ||
| + | |contributionType=1 | ||
}} | }} | ||
{{Event Deadline | {{Event Deadline | ||
|Paper Deadline=2011/06/17 | |Paper Deadline=2011/06/17 | ||
| + | |Camera-Ready Deadline=2011/10/14 | ||
|Tutorial Deadline=2011/08/01 | |Tutorial Deadline=2011/08/01 | ||
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|Submission Deadline=2011/06/17 | |Submission Deadline=2011/06/17 | ||
}} | }} | ||
| + | {{Organizer | ||
| + | |Contributor Type=organization | ||
| + | |Organization=IEEE Computer Society, Institute of Electrical and Electronics Engineers | ||
| + | }} | ||
| + | {{Event Metric}} | ||
{{S Event}} | {{S Event}} | ||
The IEEE International Conference on Data Mining series (ICDM) has established itself as the world's premier research conference in data mining. It provides an international forum for presentation of original research results, as well as exchange and dissemination of innovative, practical development experiences. The conference covers all aspects of data mining, including algorithms, software and systems, and applications. | The IEEE International Conference on Data Mining series (ICDM) has established itself as the world's premier research conference in data mining. It provides an international forum for presentation of original research results, as well as exchange and dissemination of innovative, practical development experiences. The conference covers all aspects of data mining, including algorithms, software and systems, and applications. | ||
ICDM draws researchers and application developers from a wide range of data mining related areas such as statistics, machine learning, pattern recognition, databases and data warehousing, data visualization, knowledge-based systems, and high performance computing. By promoting novel, high quality research findings, and innovative solutions to challenging data mining problems, the conference seeks to continuously advance the state-of-the-art in data mining. Besides the technical program, the conference features workshops, tutorials, panels and, since 2007, the ICDM data mining contest. | ICDM draws researchers and application developers from a wide range of data mining related areas such as statistics, machine learning, pattern recognition, databases and data warehousing, data visualization, knowledge-based systems, and high performance computing. By promoting novel, high quality research findings, and innovative solutions to challenging data mining problems, the conference seeks to continuously advance the state-of-the-art in data mining. Besides the technical program, the conference features workshops, tutorials, panels and, since 2007, the ICDM data mining contest. | ||
Latest revision as of 13:24, 2 October 2023
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Marriott Pinnacle Downtown, Vancouver, British Columbia, Canada
The IEEE International Conference on Data Mining series (ICDM) has established itself as the world's premier research conference in data mining. It provides an international forum for presentation of original research results, as well as exchange and dissemination of innovative, practical development experiences. The conference covers all aspects of data mining, including algorithms, software and systems, and applications.
ICDM draws researchers and application developers from a wide range of data mining related areas such as statistics, machine learning, pattern recognition, databases and data warehousing, data visualization, knowledge-based systems, and high performance computing. By promoting novel, high quality research findings, and innovative solutions to challenging data mining problems, the conference seeks to continuously advance the state-of-the-art in data mining. Besides the technical program, the conference features workshops, tutorials, panels and, since 2007, the ICDM data mining contest.
