计算机与现代化 ›› 2012, Vol. 1 ›› Issue (1): 25-29,4.doi: 10.3969/j.issn.1006-2475.2012.01.007
• 人工智能 • 上一篇 下一篇
陈文俊，陈德华
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CHEN Wen-jun, CHEN De-hua
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摘要： 客户交易系统随着IT技术的发展而迅猛发展，在现实生活中起着越来越重要的作用。随着交易量的增长，客户的交易行为和交易历史数据，可以很好地帮助系统管理员提供决策支持。最优簇挖掘算法可以在一个图状结构中找到关联最紧密的子图。本文通过实现GG-LSH算法，能有效地找到客户交易系统中那些关联最紧密的客户群，从而为人们提供有效的决策支持。
关键词: 最优簇挖掘, 子图, GG-LSH算法, 决策支持
Abstract: With the development of IT technology, customer trading system is developing rapidly, and plays an increasingly important role in real life. Along with the trading number growing, using customer trading behaviors and historical trading data, a well decision support could be gained from system administrator. The algorithm of best cluster mining could find a most closely associated sub-graph from a graph structure. The most closely associated customers could be effectively found from customer trading system by way of algorithm GG-LSH, thus some effective decision supports are provided for people.
Key words: best cluster mining, sub-graph, algorithm GG-LSH, decision support
中图分类号:
TP312
陈文俊;陈德华. 易货交易中紧密客户群的挖掘[J]. 计算机与现代化, 2012, 1(1): 25-29,4.
CHEN Wen-jun;CHEN De-hua. Application of Best Clusters Mining in Customer Trading System[J]. Computer and Modernization, 2012, 1(1): 25-29,4.
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http://www.c-a-m.org.cn/CN/Y2012/V1/I1/25
