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自然语言处理支持跨学科的众包

Natural language processing supported transdisciplinary crowdsourcing
课程网址: http://videolectures.net/machine_pinter_natural_language/  
主讲教师: Balázs Pintér
开课单位: 厄特沃什·罗兰大学
开课时间: 2013-08-06
课程语种: 英语
中文简介:
我们概述了一个基于Web的架构,它服务于跨学科知识的构建,并由机器智能支持。体系结构的核心是概念库和机器智能之间的交互。存储库是一个与wiki集成的本体;本体中的每个概念都以wiki的自然语言文本为基础。机器智能利用结构化稀疏编码,帮助用户与概念库交互。最重要的是,它通过解释wiki中未知的术语来帮助不同领域的从业者相互理解,并且有助于创建和维护内容。这两个组件一起发展:随着概念存储库的增长,智能性能更好。此外,半自动扩展概念库变得更容易。为了支持广泛的贡献,确保积累的知识的高质量,内容分为两类:草稿和文章。任何注册的人都可以创建和编辑草稿,但只有通过投票程序并经编辑委员会批准的草稿才能成为文章。文章与科学论文非常相似:它们接受同行评审,并包含经过验证的知识。两个社区已经开始在机器人手术和教育领域使用这些门户。
课程简介: We outline a Web-based architecture that serves the construction of transdisciplinary knowledge and is supported by machine intelligence. At the heart of the architecture is the interaction between a repository of concepts and the machine intelligence. The repository is an ontology integrated with a Wiki; each concept in the ontology is grounded in the natural language text of the Wiki. The machine intelligence exploits structured sparse coding and helps users interact with the concept repository. Most importantly, it helps practitioners of different fields understand each other by explaining unknown terminology in the Wiki, and it facilitates creating and maintaining content. These two components evolve together: as the concept repository grows, the intelligence performs better. Furthermore, extending the concept repository semi-automatically becomes easier. To support wide contribution and ensure the high quality of the accumulated knowledge, content is divided into two types: drafts and articles. Anyone who registers can create and edit drafts, but only drafts that pass a voting procedure and are approved by an Editorial Board can become articles. Articles are very similar to scientific papers: they undergo peer-review and contain verified knowledge. Two communities have already started using these portals in the domains of robotic surgery and education.
关 键 词: 跨学科知识的建设; 机器智能; 知识库; 概念库交互
课程来源: 视频讲座网
最后编审: 2020-03-27:chenxin
阅读次数: 57