Discussion Mining: Annotation-Based Knowledge Discovery from Real World Activities
Discussion Mining: Annotation-Based Knowledge Discovery from Real World Activities
复制标题
讨论挖掘：从现实世界活动中发现基于注释的知识
DOI：
10.1007/978-3-540-30541-5_64
复制
发表时间：
2004
影响因子：
22.7
通讯作者：
H. Tomobe
中科院分区：
文献类型：
--
作者：
K. Nagao;Katsuhiko Kaji;D. Yamamoto;H. Tomobe
讨论挖掘是从离线会议的讨论内容中发现知识的一个初步研究。我们的系统半自动地为这样的会议生成会议记录，并将它们与讨论场景的视听数据相关联。然后，不仅检索讨论内容，而且我们还追求从过去的讨论中搜索与正在进行的讨论相似的讨论的方法，以及基于累积的讨论内容生成对特定问题的答案的方法。在邮件列表和在线讨论系统（如公告板系统）方面，已经进行了各种研究。但是，我们认为与以前的作品有很大不同的是，我们的作品包括面对面的线下会议。我们使用音频和视频信息从不同的角度分析会议。我们还开发了一个工具的语义注释的讨论内容。我们认为这项研究不仅仅是数据挖掘，而是一种真实世界的人类活动挖掘。
We present discussion mining as a preliminary study of knowledge discovery from discussion content of offline meetings. Our system generates minutes for such meetings semi-automatically and links them with audio-visual data of discussion scenes. Then, not only retrieval of the discussion content, but also we are pursuing the method of searching for a similar discussion to an ongoing discussion from the past ones, and the method of generation of an answer to a certain question based on the accumulated discussion content. In terms of mailing lists and online discussion systems such as bulletin board systems, various studies have been done. However, what we think is greatly different from the previous works is that ours includes face-to-face offline meetings. We analyze meetings from diversified perspectives using audio and visual information. We also developed a tool for semantic annotation on discussion content. We consider this research not just data mining but a kind of real-world human activity mining.