Refining the results of automatic e-textbook construction by clustering

J. Chen, Qing Li, L. Feng

Research output: Journal article publicationJournal articleAcademic researchpeer-review

1 Citation (Scopus)

Abstract

The abundance of knowledge-rich information on the World Wide Web makes compiling an online e-textbook both possible and necessary. In our previous work, we proposed an approach to automatically generate an e-textbook by mining the ranked lists of the search engine. However, the performance of the approach was degraded by Web pages that were relevant but not actually discussing the desired concept. In this article, we extend the previous work by applying a clustering approach before the mining process. The clustering approach serves as a post-processing stage to the original results retrieved by the search engine, and aims to reach an optimum state in which all Web pages assigned to a concept are discussing that exact concept. Copyright © 2007, Idea Group Inc.
Original languageEnglish
Pages (from-to)18-28
Number of pages11
JournalInternational Journal of Distance Education Technologies
Volume5
Issue number2
DOIs
Publication statusPublished - 1 Jan 2007
Externally publishedYes

Keywords

  • Clustering algorithm
  • e-textbook
  • Representation model
  • Web learning

ASJC Scopus subject areas

  • Education
  • Computer Science Applications
  • Computer Networks and Communications

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