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Alkhawaldeh, Rami Suleiman; Jose, Joemon M.; P, Deepak
Languages: English
Types: Other
Subjects:
Resource Selection (or Query Routing) is an important step\ud in P2P IR. Though analogous to document retrieval in the\ud sense of choosing a relevant subset of resources, resource selection\ud methods have evolved independently from those for\ud document retrieval. Among the reasons for such divergence\ud is that document retrieval targets scenarios where underlying\ud resources are semantically homogeneous, whereas peers\ud would manage diverse content. We observe that semantic\ud heterogeneity is mitigated in the clustered 2-tier P2P\ud IR architecture resource selection layer by way of usage of\ud clustering, and posit that this necessitates a re-look at the\ud applicability of document retrieval methods for resource selection\ud within such a framework. This paper empirically\ud benchmarks document retrieval models against the state-ofthe-art\ud resource selection models for the problem of resource\ud selection in the clustered P2P IR architecture, using classical\ud IR evaluation metrics. Our benchmarking study illustrates\ud that document retrieval models significantly outperform\ud other methods for the task of resource selection in the\ud clustered P2P IR architecture. This indicates that clustered\ud P2P IR framework can exploit advancements in document\ud retrieval methods to deliver corresponding improvements in\ud resource selection, indicating potential convergence of these\ud fields for the clustered P2P IR architecture.
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    • [1] R. S. Alkhawaldeh and J. M. Jose. Experimental study on semi-structured peer-to-peer information retrieval network. In
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