Full-text federated search of text-based digital libraries in peer-to-peer networks |
| |
| Authors: | Jie Lu Jamie Callan |
| |
| Institution: | (1) Language Technologies Institute, School of Computer Science, Carnegie Mellon University, Pittsburgh, PA, USA |
| |
| Abstract: | Peer-to-peer (P2P) networks integrate autonomous computing resources without requiring a central coordinating authority, which
makes them a potentially robust and scalable model for providing federated search capability to large-scale networks of text-based
digital libraries. However, peer-to-peer networks have so far provided very limited support for full-text federated search
with relevance-based document ranking. This paper provides solutions to full-text federated search of text-based digital libraries
in hierarchical peer-to-peer networks. Existing approaches to full-text search are adapted and new methods are developed for
the problems of resource representation, resource selection, and result merging 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 of text-based digital libraries in peer-to-peer
networks. |
| |
| Keywords: | Full-text Federated search Text-based digital libraries Peer-to-peer networks |
| 本文献已被 SpringerLink 等数据库收录！ |
|
