MF-Chord: Supporting Multi-Attribute Multi-keyword Fuzzy-Matching Queries
Most educational resource grids are required to support multi-attribute multi-keyword fuzzy-matching queries. But such queries are not efficiently supported in current structured P2P systems. Towards an efficient P2P system capable of processing multiattribute multi-keyword fuzzy-matching queries with high recall ratio and load balancing, we propose a new resource indexing model which is expanded from Chord and called MF-Chord. Besides one-dimensional fingerprint which includes main keywords information of each attribute of the resource, MF-Chord generates opposite-fingerprint for every resource, which is the partial reversal of the fingerprint and is used to balance the query load. Reforming the finger tables of nodes and the query-request-message format, MFChord dynamically generates the query-requestforwarding- tree for every query and realizes the efficient multi-attribute multi-keyword fuzzy-matching query function. Through theoretical Analysis, we prove that MF-Chord has high recall ratio in limited hops. The experiment results show that the recall ratio of MF-Chord is more than 80％ even when the maximum hop count is set to 7 and there are 80000 nodes in the system.
ZHAO Xiu-Mei LIU Fang-Ai
School of Information Science and Engineering, Shandong Normal University, Jinan, 250014,China Scho School of Information Science and Engineering, Shandong Normal University, Jinan, 250014, China
国际会议
2009 IEEE International Symposium on IT in Medicine & Education( IEEE 教育与医药信息化国际会议)
济南
英文
522-528
2009-08-14（万方平台首次上网日期，不代表论文的发表时间）