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The 3C architecture: An XML Topic Maps based holistic information access architecture for integrating content, context and common knowledge about multimedia.

机译:3C体系结构:一种基于XML主题图的整体信息访问体系结构,用于集成有关多媒体的内容,上下文和常识。

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摘要

This thesis presents the 3C (content, context, and common-background) knowledge integration architecture, which provides the underlying framework for a new paradigm of multimedia information access. This paradigm, named the “Holistic” information access paradigm, is context-sensitive, concept-based, and proactive. The approach is “Context-sensitive” in the sense that it incorporates the characteristics of the information seeker as well as his/her intended use for the sought information. Common (domain) knowledge documents are used to characterize the seeker as well as the information task and are represented as domain based ontologies.; It is “Concept-based” as the user interacts with the system through an ontology of concepts instead of a vocabulary of words/phrases. The approach is also “Proactive” in the sense that it incorporates retrieval and classification in advance, based on background domain knowledge documents designated by the information seeker. Content knowledge is obtained via audio-visual analyzers such as object detectors and feature extraction modules. Context knowledge is extracted through shallow and deep text mining methods. These components are integrated via an XML-based standard knowledge representation scheme XML Topic Maps (XTM).
机译:本文提出了3C(内容,上下文和公共背景)知识集成体系结构,它为多媒体信息访问的新范例提供了基础框架。此范例称为“整体”信息访问范例,它是上下文相关的,基于概念的并且是主动的。从某种意义上说,该方法是“上下文相关的”,它结合了信息搜索者的特征以及他/她对搜索到的信息的预期用途。公共(领域)知识文档用于表征搜索者以及信息任务,并表示为基于领域的本体。当用户通过概念的本体而不是单词/短语的词汇与系统交互时,它是“基于概念的”。从基于信息搜索者指定的背景领域知识文档预先结合了检索和分类的意义上说,该方法也是“主动的”。内容知识是通过视听分析器(例如对象检测器和特征提取模块)获得的。上下文知识是通过浅层和深层文本挖掘方法提取的。这些组件通过基于XML的标准知识表示方案XML Topic Maps(XTM)集成。

著录项

  • 作者

    Boppana, Pallavi.;

  • 作者单位

    The University of Texas at Arlington.;

  • 授予单位 The University of Texas at Arlington.;
  • 学科 Computer Science.
  • 学位 M.S.
  • 年度 2003
  • 页码 57 p.
  • 总页数 57
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 自动化技术、计算机技术;
  • 关键词

  • 入库时间 2022-08-17 11:45:01

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