增進搜尋效能在點對點的網路系統(Peer-to-Peer Network Systems)中是一個重要的議題。雖然結構式點對點網路系統的路由方法-分散式雜湊表(Distributed Hashing Table, DHT)可以比非結構式點對點網路系統的-泛流(Flooding)快速且有效率的傳送搜尋訊息，但是卻不適合用來提供關鍵字搜尋(Keyword Search)這項機制。將叢集(Clustering)這個方法結合至大規模的點對點網路系統可以減少過量訊息的問題並且使得系統更有擴展性。
在這篇論文中，我們提出了一個以興趣為依據(Interest-based)的點對點網路系統架構以期增進搜尋效能。搜尋訊息會先被送往興趣相關的節點，這些節點對於命中搜尋(Query Hit)有較高的機率。同時，網路模擬的結果也顯示這個架構在訊息數量、搜尋延遲和搜尋命中率相對於其他的架構有較好的效果。

Improving searching performance is an important issue in peer-to-peer network systems. Although Distributed Hashing Tables (DHTs) can route queries more efficiently than flooding, they are not suitable to support keyword search. Emerging large-scale P2P systems employ clustering to reduce message overhead and provide system scalability. In this paper, we propose a peer-to-peer network system based on interest groups to improve search performance. Query messages are first sent to interested peers that may successfully hit the queries with high probability. Simulation results show that the proposed architecture outperforms other works in terms of message overhead, search latency, and hit ratio.

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