基于语义向量评价的P2P内容搜索方法

Y. Yamato
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引用次数: 5

摘要

在不久的将来,由于大量的内容(-Exa字节)在网络上分布,不仅索引服务器搜索,而且P2P (Peer-to-Peer)搜索也受到重视。典型的P2P搜索技术存在搜索准确率低、流量爆炸等问题。在本文中,我利用向量空间方法和CAN拓扑的思想,提出了一种新的P2P内容搜索方法,该方法将查询有效地转发到与期望内容语义相似的内容,而不会多次转发到同一对等点。对该方法的效果进行了分析估计,并通过仿真实验进行了定性评价。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
P2P Contents Searching Method Using Evaluation of Semantic Vectors
In the near future, since the huge amounts of contents (-Exa byte) are distributed over the networks, not only index server searching but also Peer-to-Peer (P2P) searching has been emphasized. Typical P2P search technologies have some problems, such as low search precision ratio and traffic explosions. In this paper, with ideas of the vector space method and CAN topology, I propose a new P2P contents searching method in which a query is effectively forwarded only to contents that are semantically similar to the desired contents and not forwarded to the same peer more than once. The effect of this method is estimated analytically, and a qualitative evaluation is conducted by simulation experiments.
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