Accessing nearby copies of replicated objects in a distributed environment
Proceedings of the ninth annual ACM symposium on Parallel algorithms and architectures
Search and replication in unstructured peer-to-peer networks
ICS '02 Proceedings of the 16th international conference on Supercomputing
Information Retrieval
Content-based retrieval in hybrid peer-to-peer networks
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
An architecture for information retrieval over semi-collaborating Peer-to-Peer networks
Proceedings of the 2004 ACM symposium on Applied computing
A suite of testbeds for the realistic evaluation of peer-to-peer information retrieval systems
ECIR'05 Proceedings of the 27th European conference on Advances in Information Retrieval Research
Comparing different architectures for query routing in peer-to-peer networks
ECIR'06 Proceedings of the 28th European conference on Advances in Information Retrieval
Peer-to-Peer Information Retrieval: An Overview
ACM Transactions on Information Systems (TOIS)
Large-scale similarity-based join processing in multimedia databases
MMM'12 Proceedings of the 18th international conference on Advances in Multimedia Modeling
Shard ranking and cutoff estimation for topically partitioned collections
Proceedings of the 21st ACM international conference on Information and knowledge management
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In this paper we provide a full-scale evaluation of a cluster-based architecture for P2P IR, focusing on retrieval effectiveness. We observe that there is a significant difference in performance between the architecture we examine and a centralised index. After inspecting our experimental methodology and our results, we provide evidence that suggests that this discrepancy is due to the information clustering algorithms employed throughout. The construction errors of the resource descriptions as well as the failure of the clustering mechanisms to discover the structure of the smallest of peer-collections lead to erroneous query routing. We proceed further to show experimentally how content replication and relevance-feedback mechanisms can help to alleviate the problem.