Resource Sharing Behavior in a Socialized Peer-to-Peer Internet Environment

Hsiang-Yuan Hsueh, Jing-Shiuan Hua, Shih-Ming Huang, H. Will
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引用次数: 1

Abstract

Retrieving resources which are interesting, useful, relevant, and valuable to users is always a challenge for researchers and vendors of Information Retrieval in a Peer-to-Peer (P2PIR) environment. Current research of document-based P2PIR focused mainly on the feasibility of extending IR operations and the concept of social network analysis (SNA) has been adopted as a methodology to model interrelationships among actors in ad hoc environments. The authors demonstrate the possibility to discover characteristics of users in a P2P environment by means of the Zipf long-tail distribution. It can efficiently categorize the shared information with small portions of its contents. The results indicate that for any document corpus shared by users in a P2P environment the long-tail distribution applies also. Since behavioral profiles of users can be systematically and efficiently discovered by analysis based on the long-tail distribution, the research result of this socialized approach to resource discovery in a P2P environment can provide a feasible and efficient solution.
社会化对等网络环境下的资源共享行为
在点对点(Peer-to-Peer, P2PIR)环境下,获取用户感兴趣、有用、相关和有价值的资源一直是信息检索研究人员和供应商面临的挑战。目前基于文档的P2PIR研究主要集中在扩展IR操作的可行性上,社会网络分析(SNA)的概念已被采用作为一种方法来模拟特设环境中参与者之间的相互关系。作者展示了利用Zipf长尾分布发现P2P环境中用户特征的可能性。它可以有效地将共享信息与内容的一小部分进行分类。结果表明,对于P2P环境中用户共享的任何文档语料库,长尾分布也适用。由于基于长尾分布的分析可以系统有效地发现用户的行为特征,因此这种社会化的P2P环境下资源发现方法的研究结果可以提供一种可行而高效的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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