图 书 馆
用于电子邮件活动检测的贝叶斯聚类Bayesian Clustering for Email Campaign Detection |
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| 课程网址: | http://videolectures.net/icml09_haider_bcecd/ |
| 主讲教师: | Peter Haider |
| 开课单位: | 波茨坦大学 |
| 开课时间: | 2009-08-26 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | We discuss the problem of clustering elements according to the sources that have generated them. For elements that are characterized by independent binary attributes, a closed-form Bayesian solution exists. We derive a solution for the case of dependent attributes that is based on a transformation of the instances into a space of independent feature functions. We derive an optimization problem that produces a mapping into a space of independent binary feature vectors; the features can reflect arbitrary dependencies in the input space. This problem setting is motivated by the application of spam filtering for email service providers. Spam traps deliver a real-time stream of messages known to be spam. If elements of the same campaign can be recognized reliably, entire spam and phishing campaigns can be contained. We present a case study that evaluates Bayesian clustering for this application. |
| 关 键 词: | 聚类元素; 独立二进制; 贝叶斯解 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2019-04-23：lxf |
| 阅读次数: | 14 |