图 书 馆
具有丰富信息的知识图谱构建、推理和搜索的异常领域数据挖掘Data Mining in Unusual Domains with Information-rich Knowledge Graph Construction, Inference and Search |
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| 课程网址: | http://videolectures.net/kdd2017_tutorial7_data_mining/ |
| 主讲教师: | Pedro Szekely; Mayank Kejriwal |
| 开课单位: | 南加州大学 |
| 开课时间: | 2017-11-21 |
| 课程语种: | 英语 |
| 中文简介: |  |
| 课程简介: | The growth of the Web is a success story that has spurred much research in knowledge discovery and data mining. Data mining over Web domains that are unusual is an even harder problem. There are several factors that make a domain unusual. In particular, such domains have significant long tails and exhibit concept drift, and are characterized by high levels of heterogeneity. Notable examples of unusual Web domains include both illicit domains, such as human trafficking advertising, illegal weapons sales, counterfeit goods transactions, patent trolling and cyberattacks, and also non-illicit domains such as humanitarian and disaster relief. Data mining in such domains has the potential for widespread social impact, and is also very challenging technically. In this tutorial, we provide an overview, using demos, examples and case studies, of the research landscape for data mining in unusual domains, including recent work that has achieved state-of-the-art results in constructing knowledge graphs in a variety of unusual domains, followed by inference and search using both command line and graphical interfaces. Link to tutorial: |
| 关 键 词: | 知识图谱; 数据挖掘; 领域知识 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2023-05-25：chenxin01 |
| 最后编审: | 2023-05-25：chenxin01 |
| 阅读次数: | 26 |