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AbIx: An Approach to Content-Based Approximate Query Processing in Peer-to-Peer Data Systems
作者姓名:Chao-Kun Wang  Jian-Min Wang  Jia-Guang Sun  Sheng-Fei Shi  and Hong Gao
作者单位:[1]School of Software, Tsinghua University, Beijing 100084, China [2]School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China
基金项目:Supported by the National Natural Science Foundation of China under Grant No. 60473077 and the Program for New Century Excellent Talents in University.
摘    要:In recent years there has been a significant interest in peer-to-peer (P2P) environments in the community of data management. However, almost all work, so far, is focused on exact query processing in current P2P data systems. The autonomy of peers also is not considered enough. In addition, the system cost is very high because the information publishing method of shared data is based on each document instead of document set. In this paper, abstract indices (AbIx) are presented to implement content-based approximate queries in centralized, distributed and structured P2P data systems. It can be used to search as few peers as possible but get as many returns satisfying users' queries as possible on the guarantee of high autonomy of peers. Also, abstract indices have low system cost, can improve the query processing speed, and support very frequent updates and the set information publishing method. In order to verify the effectiveness of abstract indices, a simulator of 10,000 peers, over 3 million documents is made, and several metrics are proposed. The experimental results show that abstract indices work well in various P2P data systems.

关 键 词:对等数据系统  近似查询处理  信息检索  摘要索引
收稿时间:1 May 2006
修稿时间:2006-05-012007-01-21

AbIx: An Approach to Content-Based Approximate Query Processing in Peer-to-Peer Data Systems
Chao-Kun Wang,Jian-Min Wang,Jia-Guang Sun,Sheng-Fei Shi,and Hong Gao.AbIx: An Approach to Content-Based Approximate Query Processing in Peer-to-Peer Data Systems[J].Journal of Computer Science and Technology,2007,22(2):280-286.
Authors:Chao-Kun Wang  Jian-Min Wang  Jia-Guang Sun  Sheng-Fei Shi  Hong Gao
Affiliation:1School of Software, Tsinghua University, Beijing 100084, China ;2 School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China
Abstract:In recent years there has been a significant interest in peer-to-peer (P2P) environments in the community of data management. However, almost all work, so far, is focused on exact query processing in current P2P data systems. The autonomy of peers also is not considered enough. In addition, the system cost is very high because the information publishing method of shared data is based on each document instead of document set. In this paper, abstract indices (AbIx) are presented to implement content-based approximate queries in centralized, distributed and structured P2P data systems. It can be used to search as few peers as possible but get as many returns satisfying users' queries as possible on the guarantee of high autonomy of peers. Also, abstract indices have low system cost, can improve the query processing speed, and support very frequent updates and the set information publishing method. In order to verify the effectiveness of abstract indices, a simulator of 10,000 peers, over 3 million documents is made, and several metrics are proposed. The experimental results show that abstract indices work well in various P2P data systems.
Keywords:approximate query processing  content-based information retrieval  peer-to-peer data systems  abstract indices
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