A natural language approach to content-based video indexing and retrieval for interactive e-Learning

Dongsong Zhang, Jay F. Nunamaker

Research output: Contribution to journalArticle

37 Scopus citations

Abstract

As a powerful and expressive nontextual media that can capture and present information, instructional videos are extensively used in e-Learning (Web-based distance learning). Since each video may cover many subjects, it is critical for an e-Learning environment to have content-based video searching capabilities to meet diverse individual learning needs. In this paper, we present an interactive multimedia-based e-Learning environment that enables users to interact with it to obtain knowledge in the form of logically segmented video clips. We propose a natural language approach to content-based video indexing and retrieval to identify appropriate video clips that can address users' needs. The method integrates natural language processing, named entity extraction, frame-based indexing, and information retrieval techniques to explore knowledge-on-demand in a video-based interactive e-Learning environment. A preliminary evaluation shows that precision and recall of this approach are better than those of the traditional keyword based approach.

Original languageEnglish (US)
Pages (from-to)450-458
Number of pages9
JournalIEEE Transactions on Multimedia
Volume6
Issue number3
DOIs
StatePublished - Jun 1 2004

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Keywords

  • Learning by asking
  • Natural language processing
  • Video indexing and retrieval

ASJC Scopus subject areas

  • Signal Processing
  • Media Technology
  • Computer Science Applications
  • Electrical and Electronic Engineering

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