图 书 馆
广义展开维数Generalized Expansion Dimension |
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| 课程网址: | https://videolectures.net/videos/ptdm2012_nett_expansion_dimensio... |
| 主讲教师: | Michael Nett |
| 开课单位: | 信息不详。欢迎您在右侧留言补充。 |
| 开课时间: | 2013-01-16 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | The goal of this ICDM 2012 workshop is to help closing the gap between data mining practice and theory. To this end, we intend to explore what is the essence of exploratory data mining and how to formalize it in a useful but theoretically well-founded way. The workshop is motivated by a widely perceived discrepancy between theoretical data mining prototypes and practitioners’ requirements. A notable example is frequent pattern mining. Despite its attractive theoretical foundations, the practical use of frequent pattern mining methods has been limited. This is due to a difficulty to overcome issues, such as the pattern explosion problem and a discrepancy between usefulness and frequency. These issues have been addressed to some extent in the past 15 years, through heuristic post-processing steps and through rigorously motivated adaptations. The multitude of possible solution strategies has unfortunately to a large extent undermined the original elegance, and made it hard for practitioners to understand how to use these techniques. The problem is however not restricted to frequent pattern mining alone. The multitude of available methods for typical exploratory data mining problems such as (subspace) clustering and dimensionality reduction is such that practitioners face a daunting task in selecting a suitable method. Additionally to the usability issues, less attention has been given on pattern mining methods for relational databases. Although most real world databases are relational, most pattern mining research has focused on one-table data. |
| 关 键 词: | 数据挖掘; 模式挖掘; 模式爆炸问题 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2025-04-28：zsp |
| 最后编审: | 2025-04-28：zsp |
| 阅读次数: | 3 |