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Harvesting: Broadening the Field of Distributed Information Retrieval

  • Edward A. Fox
  • Marcos A. Gonçalves
  • Ming Luo
  • Yuxin Chen
  • Aaron Krowne
  • Baoping Zhang
  • Kate McDevitt
  • Manuel Pérez-Qui ñones
  • Ryan Richardson
  • Lillian N. Cassel
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2924)

Abstract

This chapter argues that in addition to federated search and gathering (as by Web crawlers), harvesting is an important approach to address the needs for distributed IR. We highlight the use of the Open Archives Initiative Protocol for Metadata Harvesting, illustrating its use in three projects: OAD, NDLTD, and CITIDEL. We explain how traditional services can be extended in a user-centered fashion, providing details of our new: ESSEX search engine, multischeming browsing, and quality-oriented filtering (using rules and SVMs). We conclude with an overview of work in progress on logging and component architectures, as well as a summary of our findings.

Keywords

Digital Library Virginia Tech Subject Field Federate Search Open Archive Initiative 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Edward A. Fox
    • 1
  • Marcos A. Gonçalves
    • 1
  • Ming Luo
    • 1
  • Yuxin Chen
    • 1
  • Aaron Krowne
    • 1
  • Baoping Zhang
    • 1
  • Kate McDevitt
    • 1
  • Manuel Pérez-Qui ñones
    • 1
  • Ryan Richardson
    • 1
  • Lillian N. Cassel
    • 2
  1. 1.Digital Library Research LaboratoryVirginia TechBlacksburgUSA
  2. 2.Dept. of Computing SciencesVillanova UniversityVillanovaUSA

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