| 摘要: |
| 目前大多数的Peer-to-Peer(P2P)系统只支持基于文件标识的搜索,用户不能根据文件的内容进行搜索.Top-k查询被广泛地应用于搜索引擎中,获得了巨大的成功.可是,由于P2P系统是一个动态的、分散的系统,在纯的P2P环境下进行top-k查询是具有挑战性的.提出了一种基于直方图的分层top-k查询算法.首先,采用层次化的方法实现分布式的top-k查询,将结果的合并和排序分散到P2P网络中的各个节点上,充分利用了网络中的资源.其次,根据节点返回的结果为节点构建直方图,利用直方图估计节点可能的分数上限,对节点进行选择,提高了查询效率.实验证明,top-k查询提高了查询效果,而直方图则提高了查询效率. |
| 关键词: P2P网络 top-k查询 搜索 直方图 |
| DOI： |
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| 基金项目:Supported bvthe National Natural Science Foundation of China under Grant No.604963205,60473069(国家自然科学基金);the National High-Tech Research and Development Plan of China under Grant No.2002AA4Z3130(国家高技术研究发展计划(863));the National Grand Fundamental Research 973 Program of China under Grant No.2001CCA03000(国家重点基础研究发展规划(973));the Key Science-Technology Project of Beijing of China under Grant No.H030130040011(北京市科技计划重大项目) |
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| Efficient Top-k Query Processing in Pure Peer-to-Peer Network |
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HE Ying-Jie,WANG Shan,DU Xiao-Yong
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| Abstract: |
| Most of the existing peer-to-peer (P2P) systems only support simple title-based search, and users cannot search the data based on their content. Top-k query is widely used in the search engine and gains great success. However, Processing top-k query in pure P2P network is very challenging because a P2P system is a dynamic and decentralized system. An efficient hierarchical top-k query processing algorithm based on histogram is proposed. First, a distributed query processing model for top-k query is proposed. It does top-k query in a hierarchical way. Ranking and merging of documents are distributed across the peers, which takes full advantage of the computing resource of the network. Next, a histogram is constructed for each peer according to the top k results returned by the peer, and used to estimate the possible upper bound of the score for the peer. By the histogram information, the most possible peers are selected to send the query, so as to greatly improve the search efficiency. Experimental results show that the top-k query improves the query effectiveness, and the histogram improves the query efficiency. |
| Key words: P2P network top-k query search histogram |
