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Applied Intelligence

, Volume 35, Issue 3, pp 375–398 | Cite as

A large-scale distributed framework for information retrieval in large dynamic search spaces

  • Eugene SantosJr.
  • Eunice E. Santos
  • Hien NguyenEmail author
  • Long Pan
  • John Korah
Article

Abstract

One of the main problems facing human analysts dealing with large amounts of dynamic data is that important information may not be assessed in time to aid the decision making process. We present a novel distributed processing framework called Intelligent Foraging, Gathering and Matching (I-FGM) that addresses this problem by concentrating on resource allocation and adapting to computational needs in real-time. It serves as an umbrella framework in which the various tools and techniques available in information retrieval can be used effectively and efficiently. We implement a prototype of I-FGM and validate it through both empirical studies and theoretical performance analysis.

Keywords

Information search and retrieval Distributed processing Multi-agent architecture Dynamic anytime processing Content analysis and indexing 

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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Eugene SantosJr.
    • 1
  • Eunice E. Santos
    • 2
  • Hien Nguyen
    • 3
    Email author
  • Long Pan
    • 4
  • John Korah
    • 2
  1. 1.Thayer School of EngineeringDartmouth CollegeHanoverUSA
  2. 2.Department of Computer ScienceUniversity of Texas at El PasoEl PasoUSA
  3. 3.Mathematical and Computer Sciences DepartmentUniversity of WisconsinWhitewaterUSA
  4. 4.Department of Computer ScienceVirginia Polytechnic Institute & State UniversityBlacksburgUSA

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