Federated search of text-based digital libraries in hierarchical peer-to-peer networks

  • Authors:
  • Jie Lu;Jamie Callan

  • Affiliations:
  • School of Computer Science, Carnegie Mellon University, Pittsburgh, PA;School of Computer Science, Carnegie Mellon University, Pittsburgh, PA

  • Venue:
  • ECIR'05 Proceedings of the 27th European conference on Advances in Information Retrieval Research
  • Year:
  • 2005

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Abstract

Peer-to-peer architectures are a potentially powerful model for developing large-scale networks of text-based digital libraries, but peer-to-peer networks have so far provided very limited support for text-based federated search of digital libraries using relevance-based ranking. This paper addresses the problems of resource representation, resource ranking and selection, and result merging for federated search of text-based digital libraries in hierarchical peer-to-peer networks. Existing approaches to text-based federated search are adapted and new methods are developed for resource representation and resource selection according to the unique characteristics of hierarchical peer-to-peer networks. Experimental results demonstrate that the proposed approaches offer a better combination of accuracy and efficiency than more common alternatives for federated search in peer-to-peer networks.