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Integrating Lightweight Reasoning into Class-Based Query Refinement for Object Search

机译:将轻量级推理集成到用于对象搜索的基于类的查询优化中

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摘要

More and more RDF data have been published online to be consumed. Ordinary Web users also expect to experience more intelligent services promised by the Semantic Web, such as object search based on structured data. We implemented the Falcons search engine to meet the challenge. To enable keyword search, for each object, we construct and index a virtual document that includes textual descriptions of its neighboring resources. Typing information is used to serve class-based query refinement, and class-inclusion reasoning is performed to discover implicit types of objects. A method of recommending subclasses is implemented to enable navigating class hierarchies for incremental query refinement. We also report on lessons learned from Web-scale experiments.
机译:越来越多的RDF数据已在线发布以供使用。普通Web用户还希望体验语义Web承诺的更多智能服务,例如基于结构化数据的对象搜索。我们实施了Falcons搜索引擎来应对挑战。为了启用关键字搜索,对于每个对象,我们构建并索引一个虚拟文档,该虚拟文档包括其相邻资源的文本描述。键入信息用于服务于基于类的查询细化,并且执行类包含推理来发现对象的隐式类型。实现了一种推荐子类的方法,以实现导航类层次结构以进行增量查询优化。我们还将报告从网络规模的实验中学到的经验教训。

著录项

  • 来源
    《The Semantic Web - ASWC 2008》|2008年|449-463|共15页
  • 会议地点 Bangkok(TH);Bangkok(TH)
  • 作者

    Gong Cheng; Yuzhong Qu;

  • 作者单位

    Institute of Web Science, School of Computer Science and Engineering Southeast University, Nanjing 210096, P.R. China;

    Institute of Web Science, School of Computer Science and Engineering Southeast University, Nanjing 210096, P.R. China;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 计算机网络;
  • 关键词

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