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An Interval-Based Knowledge Model and Query Language for Temporal Information

机译：基于时间间隔的知识模型和时间信息查询语言

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摘要

Time plays a crucial role in describing dynamic domain and resources on the Web. Most of current ontology languages, without notion of time or change, can only describe domain knowledge in a static sense. In order to bring structure to time-varying information, we propose an interval-based knowledge model (IKM), which is composed of a temporal knowledge schema, temporal integrity constraints and an interpretation structure. In the IKM, a group of expressive temporal constructs are provided to capture the temporal features of concepts, attributes and relationships; a group of rules are defined to enrich expressivity of the model; formal meaning is given to the model via an interpretation with model-theoretical semantics. A high-level query language is defined on the model, too.
机译：时间在描述Web上的动态域和资源方面起着至关重要的作用。当前大多数本体语言都没有时间或变化的概念，只能以静态方式描述领域知识。为了使时变信息具有结构性，我们提出了一种基于时间间隔的知识模型（IKM），该模型由时间知识模式，时间完整性约束和解释结构组成。在IKM中，提供了一组表达性的时间结构，以捕获概念，属性和关系的时间特征。定义了一组规则以丰富模型的表达能力；通过具有模型理论语义的解释为模型提供形式上的含义。在模型上也定义了高级查询语言。

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  • 来源
    《Multi-agent systems for society》|2005年|310-323|共14页
  • 会议地点 Kuala Lumpur(MY);Kuala Lumpur(MY)
  • 作者

    He Huang; Zhongzhi Shi; Xiaoxiao He; Lirong Qiu; Jiewen Luo;

  • 作者单位

    Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, P.O. Box 2704-28, Beijing 100080 China Graduate School of the Chinese Academy of Sciences, Beijing, China;

    Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, P.O. Box 2704-28, Beijing 100080 China;

    Graduate School of the Chinese Academy of Sciences, Beijing, China;

    Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, P.O. Box 2704-28, Beijing 100080 China Graduate School of the Chinese Academy of Sciences, Beijing, China;

    Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, P.O. Box 2;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 人工智能理论;
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