行业3:如何共现可以补充语义?Industry 3: How Co-Occurrence can Complement Semantics? |
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课程网址: | http://videolectures.net/iswc06_popov_hoccs/ |
主讲教师: | Atanas Kiryakov, Borislav Popov |
开课单位: | 语义技术实验室 |
开课时间: | 2007-02-25 |
课程语种: | 英语 |
中文简介: | 文本分析是结构化知识语义注释和提取的一种明显方式。一项基本任务是承认对实体 (人员、地点、组织等) 的引用。下一步是关系提取, 例如, 确定一个组织位于特定城市。自动提取这种关系是一个棘手的语言问题--解决方案要么非常局部, 要么实施成本很高, 要么速度缓慢。另一方面, 关系对于用于导航和搜索目的的提取知识的可用性至关重要。我们演示了如何在语义注释之上执行高效的共现分析, 以用于多种目的: 关系提取、多面搜索和受欢迎时间线。分面搜索界面允许通过通过共现分析和语义关系获得的实体引用来增强全文搜索。尽管这种分析几乎可以在任何领域使用, 但它们在 kim 平台内的开发是由新闻分析和研究的要求推动的。我们在100万篇新闻文章的基础上展示了这些界面的使用--这是过去五年主要国际新闻的一部分。这种共现分析具有帮助标识解析的潜力, 这被认为是几个任务的关键问题: 跨文档共同引用解析、记录链接、对象链接和数据集成。 |
课程简介: | Analysis of texts is an obvious way for semantic annotation and extraction of structured knowledge. A basic task is the recognition of references to entities (people, locations, organizations, etc). A next step is relation extraction, e.g. identifying that an organization is located in a particular city. Automatic extraction of such relations is a tough linguistic problem - the solutions are either very partial, expensive to implement, or slow. On the other hand, relationships are crucial for the usability of the extracted knowledge for navigation and search purposes. We demonstrate how efficient co-occurrence analysis, performed on top of semantic annotation, can be used for several purposes: relation extraction, faceted search, and popularity timelines. The faceted search interface allows an easy way for augmenting full-text search by means of entity references, derived through co-occurrence profiling and semantic relationships. Although this sort of analytics can be used in virtually any domain, their development within the KIM platform was driven by the requirements for news analysis and research. We demonstrate the usage of these interfaces on top of 1 million news articles - a corpus of the major international news for the last five years. This sort of co-occurrence analysis has the potential of aiding identity resolution, which is recognized to be a crucial problem for several tasks: cross-document co-reference resolution, record linkage, object linking, and data integration. |
关 键 词: | 语义网; 信息提取; 文本挖掘 |
课程来源: | 视频讲座网 |
最后编审: | 2021-05-14:yumf |
阅读次数: | 45 |