图 书 馆
|
|
|
| 课程网址: | http://videolectures.net/ecmlpkdd09_segond_bngutd/ |
| 主讲教师: | Marc Segond |
| 开课单位: | 欧洲软计算中心 |
| 开课时间: | 2009-10-20 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | According to Koestler, the notion of a bisociation denotes a connection between pieces of information from habitually separated domains or categories. In this paper, we consider a methodology to find such bisociations using a network representation of knowledge, which is called a BisoNet, because it promises to contain bisociations. In a fi rst step, we consider how to create BisoNets from several textual databases taken from di fferent domains using simple text-mining techniques. To achieve this, we introduce a procedure to link nodes of a BisoNet and to endow such links with weights, which is based on a new measure for comparing text frequency vectors. In a second step, we try to rediscover known bisociations, which were originally found by a human domain expert, namely indirect relations between migraine and magnesium as they are hidden in medical research articles published before 1987. We observe that these bisociations are easily rediscovered by simply following the strongest links. Future work includes extending our methods to non-textual data, improving the similarity measure, and applying more sophisticated graph mining methods. |
| 关 键 词: | 文本挖掘; 双联; 图形挖掘 |
| 课程来源: | 视频讲座网 |
| 最后编审: | 2020-06-15：wuyq |
| 阅读次数: | 64 |