Metadata harvesting for content-based distributed information retrieval
Journal of the American Society for Information Science and Technology
Peer-to-peer similarity search over widely distributed document collections
Proceedings of the 2008 ACM workshop on Large-Scale distributed systems for information retrieval
Generative model-based metasearch for data fusion in information retrieval
Proceedings of the 9th ACM/IEEE-CS joint conference on Digital libraries
Aggregation of Document Frequencies in Unstructured P2P Networks
WISE '09 Proceedings of the 10th International Conference on Web Information Systems Engineering
Improving information retrieval effectiveness in peer-to-peer networks through query piggybacking
ECDL'09 Proceedings of the 13th European conference on Research and advanced technology for digital libraries
Atlas: Storing, updating and querying RDF(S) data on top of DHTs
Web Semantics: Science, Services and Agents on the World Wide Web
Content-based peer-to-peer network overlay for full-text federated search
Large Scale Semantic Access to Content (Text, Image, Video, and Sound)
Search result caching in peer-to-peer information retrieval networks
IRFC'11 Proceedings of the Second international conference on Multidisciplinary information retrieval facility
Peer-to-Peer Information Retrieval: An Overview
ACM Transactions on Information Systems (TOIS)
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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.