463
个编辑
更改
→Research
如果学习的模式不能达到预期的标准，那么就需要重新评估和修改预处理和数据挖掘的步骤。如果所学的模式确实符合所需的标准，那么最后一步就是解释所学的模式并将其转化为知识。
如果学习的模式不能达到预期的标准，那么就需要重新评估和修改预处理和数据挖掘的步骤。如果所学的模式确实符合所需的标准，那么最后一步就是解释所学的模式并将其转化为知识。
==Research==
==研究 Research==
The premier professional body in the field is the [[Association for Computing Machinery]]'s (ACM) Special Interest Group (SIG) on Knowledge Discovery and Data Mining ([[SIGKDD]]).<ref>{{cite web|url=http://academic.research.microsoft.com/?SearchDomain=2&SubDomain=7&entitytype=2|title=Microsoft Academic Search: Top conferences in data mining | publisher=[[Microsoft Academic Search]]}}</ref><ref>{{cite web|url=https://scholar.google.de/citations?view_op=top_venues&hl=en&vq=eng_datamininganalysis|title=Google Scholar: Top publications - Data Mining & Analysis|publisher=[[Google Scholar]]}}</ref> Since 1989, this ACM SIG has hosted an annual international conference and published its proceedings,<ref>[http://www.kdd.org/conferences.php Proceedings] {{Webarchive|url=https://web.archive.org/web/20100430120252/http://www.kdd.org/conferences.php |date=2010-04-30 }}, International Conferences on Knowledge Discovery and Data Mining, ACM, New York.</ref> and since 1999 it has published a biannual [[academic journal]] titled "SIGKDD Explorations".<ref>[http://www.kdd.org/explorations/about.php SIGKDD Explorations], ACM, New York.</ref>
The premier professional body in the field is the [[Association for Computing Machinery]]'s (ACM) Special Interest Group (SIG) on Knowledge Discovery and Data Mining ([[SIGKDD]]).<ref>{{cite web|url=http://academic.research.microsoft.com/?SearchDomain=2&SubDomain=7&entitytype=2|title=Microsoft Academic Search: Top conferences in data mining | publisher=[[Microsoft Academic Search]]}}</ref><ref>{{cite web|url=https://scholar.google.de/citations?view_op=top_venues&hl=en&vq=eng_datamininganalysis|title=Google Scholar: Top publications - Data Mining & Analysis|publisher=[[Google Scholar]]}}</ref> Since 1989, this ACM SIG has hosted an annual international conference and published its proceedings,<ref>[http://www.kdd.org/conferences.php Proceedings] {{Webarchive|url=https://web.archive.org/web/20100430120252/http://www.kdd.org/conferences.php |date=2010-04-30 }}, International Conferences on Knowledge Discovery and Data Mining, ACM, New York.</ref> and since 1999 it has published a biannual [[academic journal]] titled "SIGKDD Explorations".<ref>[http://www.kdd.org/explorations/about.php SIGKDD Explorations], ACM, New York.</ref>
数据挖掘专题也出现在许多数据管理 / 数据库会议上，如 ICDE 会议、 SIGMOD 会议和甚大数据库国际会议
数据挖掘专题也出现在许多数据管理 / 数据库会议上，如 ICDE 会议、 SIGMOD 会议和甚大数据库国际会议
==标准 Standards==
==标准 Standards==