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Acquiring trustworthy knowledge for conversation agents based on a Web knowledge trust model

机译:基于Web知识信任模型的会话代理获取可信知识

摘要

This paper presents a proposal to facilitate the use of online documents from the World Wide Web (WWW) - to acquire knowledge for Intelligent Conservation Agents (CA). Information extracted from public web pages has — long been an issue that web pages may contain incorrect information or are outright hoaxes. Therefore, we propose a Web Knowledge Trust Model (WKTM) to find 'trustworthy' websites and to ensure the credibility and reliability of the knowledge extracted from the web-derived corpora. The results indicate that WKMT is useful for evaluating the trustworthiness of web sites and it is useful for the developing of key criteria for a conversation agent's domain knowledge base.
机译:本文提出了一项建议,以促进使用来自万维网(WWW)的在线文档-获取智能保护代理(CA)的知识。从公共网页提取的信息一直是一个问题,即网页可能包含错误的信息或完全是骗局。因此,我们提出了一种Web知识信任模型(WKTM),以查找“可信赖”的网站,并确保从Web语料库中提取的知识的可信度和可靠性。结果表明,WKMT可用于评估网站的可信度,并且可用于开发对话代理的域知识库的关键标准。

著录项

  • 作者

    Goh O.S.; Fung C.C.;

  • 作者单位
  • 年度 2008
  • 总页数
  • 原文格式 PDF
  • 正文语种 {"code":"en","name":"English","id":9}
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