Chapter 3: Search for Knowledge

机译：第三章：寻找知识

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There are major trends to advance the functionality of search engines to a more expressive semantic level. This is enabled by the advent of knowledge-sharing communities such as Wikipedia and the progress in automatically extracting entities and relationships from semistructured as well as natural-language Web sources. In addition, Semantic-Web-style ontologies, structured Deep-Web sources, and Social-Web networks and tagging communities can contribute towards a grand vision of turning the Web into a comprehensive knowledge base that can be efficiently searched with high precision. This vision and position paper discusses opportunities and challenges along this research avenue. The technical issues to be looked into include knowledge harvesting to construct large knowledge bases, searching for knowledge in terms of entities and relationships, and ranking the results of such queries.

机译：存在将搜索引擎的功能提高到更具表现力的语义水平的主要趋势。这是由于诸如Wikipedia之类的知识共享社区的出现以及从半结构化和自然语言Web源自动提取实体和关系的进展而实现的。此外，语义Web风格的本体，结构化的Deep Web消息源，Social-Web网络和标签社区可以有助于实现将Web变成可以高效，高精度地搜索的综合知识库的宏伟愿景。本愿景和立场文件讨论了该研究途径中的机遇与挑战。要研究的技术问题包括建立大型知识库的知识收集，根据实体和关系搜索知识以及对此类查询的结果进行排名。

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来源
《Search computing : Challenges and directions》|2009年|p.24-39|共16页
会议地点 Como(IT);Como(IT)
作者
Gerhard Weikum;
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作者单位

Max-Planck Institute for Informatics Saarbruecken, Germany;

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会议组织
原文格式 PDF
正文语种 eng
中图分类计算技术、计算机技术;
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Chapter 3: Search for Knowledge

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