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Clustering-Based Query Routing in Cooperative Semi-Structured Peer to Peer Networks

机译：基于聚类的Coperative Semi-Suralized对等网络中的查询路由

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We consider the problem of resource selection in clustered Peer-to-Peer Information Retrieval (P2P IR) networks with cooperative peers. The clustered P2P IR framework presents a significant departure from general P2P IR architectures by employing clustering to ensure content coherence between resources at the resource selection layer, without disturbing document allocation. We propose that such a property could be leveraged in resource selection by adapting well-studied and popular inverted lists for centralized document retrieval. Accordingly, we propose the Inverted PeerCluster Index (IPI), an approach that adapts the inverted lists, in a straightforward manner, for resource selection in clustered P2P IR. IPI also encompasses a strikingly simple peer-specific scoring mechanism that exploits the said index for resource selection. Through an extensive empirical analysis on P2P IR testbeds, we establish that IPI competes well with the sophisticated state-of-the-art methods in virtually every parameter of interest for the resource selection task, in the context of clustered P2P IR.
机译：我们考虑与合作对等体的聚类对等信息检索（P2P IR）网络中的资源选择问题。群集P2P IR框架通过使用群集来确保资源选择层的资源之间的内容一致性，而不会干扰文档分配，呈现出于一般P2P IR架构的大量出发。我们建议通过适应集中文档检索的良好研究和流行的倒立列表来利用这些财产来利用资源选择。因此，我们提出了倒的PEERCLUSTER指数（IPI），一种方法，该方法以直接的方式适应簇状的P2P IR中的资源选择。 IPI还包括一个引人注目的简单对等特定的评分机制，用于利用所述资源选择的索引。通过对P2P IR验证的大量实证分析，我们在群集P2P IR的上下文中，我们建立了与资源选择任务的每个兴趣参数的复杂最先进的方法竞争。

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