首页> 外文OA文献 >Facilitating Knowledge Discovery by Mining the Content and Link Structure of the Web
【2h】

Facilitating Knowledge Discovery by Mining the Content and Link Structure of the Web

机译:通过挖掘Web的内容和链接结构促进知识发现

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

Given the vast amount of online information covering almost all aspects of human endeavor, the Internet, especially the Web, is clearly a fertile ground for data mining research from which to extract valuable knowledge. Web mining is the application of data mining techniques to extract knowledge from Web data, including Web documents, Web hyperlink structure, and Web usage logs.Traditional Web mining research has been mainly focused on addressing the information overload problem. Many information retrieval (IR) and artificial intelligence (AI) techniques have been adopted or developed to identify relevant information from the Web to meet users' specific information needs. However, most existing studies do not fully explore the social and behavioral aspects of the Web. Thus, the primary goal of this dissertation is to develop an integrated research framework that extends traditional Web mining methodologies to fully explore the technical, social, and behavioral aspects of Web knowledge discovery.My dissertation framework is composed of technical and social/behavioral components. In the technical component of my dissertation, a set of domain specific Web collection building, Web content and link structure mining, and Web knowledge presentation techniques were developed. These techniques were tested in a series of case studies to demonstrate their effectiveness and efficiency in facilitating knowledge discovery in various domains.The social/behavioral component of my dissertation is to explore the application of Web mining technology as a new means to study the social interactions and behavior of Web content providers and users. Several case studies were conducted to extract knowledge on covert organizations' resource allocation plans, information management policies, and technical sophistication using Web mining techniques. Such knowledge would be very difficult to obtain through other means.The major contributions of this dissertation are twofold. First, it proposed a set of new Web mining techniques that can help facilitate knowledge discovery in various domains. Second, it demonstrated the effectiveness and efficiency of applying Web mining techniques in extracting social and behavioral knowledge in different contexts.
机译:鉴于涵盖了人类几乎所有方面的大量在线信息,互联网,尤其是Web,显然是进行数据挖掘研究的沃土,可从中提取有价值的知识。 Web挖掘是数据挖掘技术的应用,可以从Web数据中提取知识,包括Web文档,Web超级链接结构和Web使用日志。传统的Web挖掘研究主要集中在解决信息过载问题。已经采用或开发了许多信息检索(IR)和人工智能(AI)技术来从Web识别相关信息,以满足用户的特定信息需求。但是,大多数现有研究并未完全探讨网络的社会和行为方面。因此,本论文的主要目标是开发一个扩展了传统Web挖掘方法的集成研究框架,以全面探索Web知识发现的技术,社会和行为方面。我的论文框架由技术,社会/行为组成。在本文的技术部分中,开发了一组特定于域的Web集合构建,Web内容和链接结构挖掘以及Web知识表示技术。在一系列案例研究中对这些技术进行了测试,以证明它们在促进各个领域的知识发现方面的有效性和效率。本文的社会/行为组成部分是探索将Web挖掘技术作为研究社会互动的一种新方法的应用。 Web内容提供商和用户的行为。进行了一些案例研究,以使用Web挖掘技术来提取有关秘密组织的资源分配计划,信息管理策略和技术复杂性的知识。通过其他方式很难获得这样的知识。本论文的主要贡献是双重的。首先,它提出了一套新的Web挖掘技术,可以帮助促进各个领域的知识发现。其次,它展示了应用Web挖掘技术在不同上下文中提取社交和行为知识的有效性和效率。

著录项

  • 作者

    Qin Jialun;

  • 作者单位
  • 年度 2006
  • 总页数
  • 原文格式 PDF
  • 正文语种 EN
  • 中图分类

相似文献

  • 外文文献
  • 中文文献
  • 专利

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号