非结构化点对点系统中基于历史的多关键词搜索

Xiaojing Sun, Feng Hong, Zhongwen Guo
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引用次数: 1

摘要

点对点方法为Web内容搜索提供了一个完美的选择。然而,如何基于内容查询对数据进行搜索和检索仍然是对等系统的一个开放性问题。本文在非结构化点对点系统中提出了基于历史的多关键字搜索(HMS),它只要求每个点维护其邻居的部分查询信息,并利用这些信息自主地发现每个查询有多少邻居和哪些邻居可能回答。仿真结果表明,HMS可以在保证查询结果质量的同时限制查询消息的流量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
HMS: History-Based Multi-Keywords Search in Unstructured Peer-to-Peer Systems
Peer-to-peer approaches bring one perfect alternative for the Web content search. However, how to search and retrieve the data based on the content query is still an open problem for peer-to-peer systems. In this paper we propose Historybased Multi-keywords Search(HMS) in unstructured peer-to-peer systems, which only requires each peer to maintain partial query information of its neighbors, and exploit these information to autonomously find, for each query, how many neighbors and which neighbors are likely to answer. The simulations prove that HMS can limit the traffic of query messages while keeping the high quality of query results.
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