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自然语言和语义网

POWERSET - Natural Language and the Semantic Web
课程网址: http://videolectures.net/iswc07_pell_nlpsw/  
主讲教师: Barney Pell
开课单位: Powerset公司
开课时间: 2007-11-15
课程语种: 英语
中文简介:
语义网承诺通过将机器可读的语义信息添加到通常只能由人解释的内容中,来彻底改变对信息的访问。此外,它还将通过添加语义信息来创建机器可读的服务描述,从而彻底改变对服务的访问。由于鸡和蛋的问题,这一雄心勃勃的愿景迟迟未能实现。在人们构建应用程序之前需要标记,在值得做标记的艰苦工作之前需要应用程序。自然语言处理(NLP)已经发展到可以打破僵局并打开语义网的可能性的地步。首先,NLP系统现在可以从非结构化文本自动创建注释。这提供了语义web应用程序所需的数据。其次,NLP系统本身就是语义网络信息的消费者,因此为人们创建和维护这些信息提供了经济动力。例如,如Powerset所示,新一代自然语言搜索系统可以利用语义网络标记和本体来增强对底层文本内容的解释。它们还可以直接公开语义web服务以响应自然语言查询。
课程简介: The Semantic Web promises to revolutionize access to information by adding machine-readable semantic information to content which is normally interpretable only by people. In addition, it will also revolutionize access to services by adding semantic information to create machine-readable service descriptions. This ambitious vision has been slow to take off because of a chicken and egg problem. Markup is required before people will build applications, applications are required before it is worth the hard work of doing markup. Natural language processing (NLP) has advanced to the point where it can break the impasse and open up the possibilities of the Semantic Web. First, NLP systems can now automatically create annotations from unstructured text. This provides the data that semantic web applications require. Second, NLP systems are themselves consumers of semantic web information and thus provide economic motivation for people to create and maintain such information. For example, a new generation of natural language search systems, as illustrated by Powerset, can take advantage of semantic web markup and ontologies to augment their interpretation of underlying textual content. They can also expose semantic web services directly in response to natural language queries.
关 键 词: 应用程序; 自然语言搜索系统; 非结构化文本
课程来源: 视频讲座网
数据采集: 2022-11-10:chenjy
最后编审: 2022-11-10:chenjy
阅读次数: 46