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Web语义的大规模集成
Large Scale Integration of Senses for the Semantic Web |
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| 课程网址: |
http://videolectures.net/www09_gracia_lsissw/
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| 主讲教师: |
Mathieu d’Aquin; Eduardo Mena; Jorge Gracia
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| 开课单位: |
萨拉戈萨大学
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| 开课时间: |
2009-05-20
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| 课程语种: |
英语
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| 中文简介: |
如今, web 上可用的语义数据量不断增加, 导致语义 web 应用程序的潜力进入了一个新的阶段。但是, 由于可用语义资源的异质性, 它也引入了新的问题。其中最引人注目的是冗余, 即来自不同来源的不同语义描述的过剩, 以描述相同的预期含义。在本文中, 我们提出了一种在编制大量在线语义信息索引时执行大规模感官集成 (表示为本体术语) 的技术, 以便对最相似的感官进行分组。它可以极大地减少当前语义 web 上的冗余问题。为了使这一目标可行, 我们研究了以前的感觉集成工作的适应性和可扩展性, 并将其转换为语义 web 的更大的场景。我们的评价表明, 这些技术在大规模实验中的应用表现良好, 从而使所提出的方法成为可行。
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| 课程简介: |
Nowadays, the increasing amount of semantic data available on the Web leads to a new stage in the potential of Semantic Web applications. However, it also introduces new issues due to the heterogeneity of the available semantic resources. One of the most remarkable is redundancy, that is, the excess of different semantic descriptions, coming from different sources, to describe the same intended meaning. In this paper, we propose a technique to perform a large scale integration of senses (expressed as ontology terms), in order to cluster the most similar ones, when indexing large amounts of online semantic information. It can dramatically reduce the redundancy problem on the current Semantic Web. In order to make this objective feasible, we have studied the adaptability and scalability of our previous work on sense integration, to be translated to the much larger scenario of the Semantic Web. Our evaluation shows a good behaviour of these techniques when used in large scale experiments, then making feasible the proposed approach.
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| 关 键 词: |
Web; 感官技术; 本体术语
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| 课程来源: |
视频讲座网
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| 最后编审: |
2020-06-27：zyk
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| 阅读次数: |
45
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