面向语言学与面向领域的关系研究 语义学

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摘要翻译：
本文研究了词汇资源与本体提供的领域知识之间的比较和链接。这是语义Web本体与文本挖掘相结合的问题之一。通过将GO生物过程概念与FrameNet语义框架相关联，研究了面向语言学的语义和特定领域的语义之间的关系。结果表明，面向语言学的语义学和面向领域的语义学在事件分类和目标词分组方面存在差距。研究结果为支持文本挖掘系统的领域本体的改进提供了有价值的信息。同时，它也会给语言理解技术带来好处。
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英文标题：
《A study on the relation between linguistics-oriented and domain-specific
  semantics》
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作者：
He Tan
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最新提交年份：
2010
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Artificial Intelligence        人工智能
分类描述：Covers all areas of AI except Vision, Robotics, Machine Learning, Multiagent Systems, and Computation and Language (Natural Language Processing), which have separate subject areas. In particular, includes Expert Systems, Theorem Proving (although this may overlap with Logic in Computer Science), Knowledge Representation, Planning, and Uncertainty in AI. Roughly includes material in ACM Subject Classes I.2.0, I.2.1, I.2.3, I.2.4, I.2.8, and I.2.11.
涵盖了人工智能的所有领域，除了视觉、机器人、机器学习、多智能体系统以及计算和语言（自然语言处理），这些领域有独立的学科领域。特别地，包括专家系统，定理证明（尽管这可能与计算机科学中的逻辑重叠），知识表示，规划，和人工智能中的不确定性。大致包括ACM学科类I.2.0、I.2.1、I.2.3、I.2.4、I.2.8和I.2.11中的材料。
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英文摘要：
  In this paper we dealt with the comparison and linking between lexical resources with domain knowledge provided by ontologies. It is one of the issues for the combination of the Semantic Web Ontologies and Text Mining. We investigated the relations between the linguistics oriented and domain-specific semantics, by associating the GO biological process concepts to the FrameNet semantic frames. The result shows the gaps between the linguistics-oriented and domain-specific semantics on the classification of events and the grouping of target words. The result provides valuable information for the improvement of domain ontologies supporting for text mining systems. And also, it will result in benefits to language understanding technology.
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PDF链接：
https://arxiv.org/pdf/1012.1635

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关键词：语言学 Intelligence Presentation Linguistics Text Mining 语义 分组 result 语言 specific