[1]刘波,杨路明,邓云龙,等.融合粒子群算法改进XML数据智能清洗策略[J].智能系统学报,2008,3(3):226-234.
LIU Bo,YANG Lu-ming,DENG Yun-long.An intelligence data cleaning strategy for XML database using PSO[J].CAAI Transactions on Intelligent Systems,2008,3(3):226-234.
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LIU Bo,YANG Lu-ming,DENG Yun-long.An intelligence data cleaning strategy for XML database using PSO[J].CAAI Transactions on Intelligent Systems,2008,3(3):226-234.
融合粒子群算法改进XML数据智能清洗策略
《智能系统学报》[ISSN 1673-4785/CN 23-1538/TP] 卷:
3
期数:
2008年第3期
页码:
226-234
栏目:
学术论文—人工智能基础
出版日期:
2008-06-25
- Title:
- An intelligence data cleaning strategy for XML database using PSO
- 文章编号:
- 1673-4785(2008)03-0226-08
- 分类号:
- TP311.13
- 文献标志码:
- A
- 摘要:
- 针对XML数据质量问题,以XML键为基础、借助多模板隐马尔可夫模型信息抽取策略与粒子群算法构建新的XML数据清洗方法;为了提高XML相似性数据并行检测效率,尝试利用波函数对粒子群算法进行相应优化.对比其他XML数据清洗算法,一系列仿真实验表明改进的XML数据清洗方法不仅自适应学习功能强、人工参与程度低、计算量小,而且时间性能有94%左右提升.
- Abstract:
- To imp rove XML data quality, this paper p roposes a new XML data cleaning method based on XML2 keys, the information draw2out strategy of multip le temp lates, the hidden Markov model (HMM) , and particle swarm op timization ( PSO). To imp rove parallel efficiencywhen detecting similar XML records, a wave function is emp loyed to imp rove the PSO algorithm. A series of simulations indicated that, compared with other XML data cleaning algorithms, the imp roved XML data cleaning algorithm has a more powerful adap tive learning capability, requires less human interaction, and reduces computational time by about 94%.
- 参考文献/References:
-
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备注/Memo
收稿日期：2007-06-25
基金项目：湖南信息职业学院科技创新资助项目(108652006011);; 湖南省教育厅科研基金资助项目(05c671)
作者简介：刘波，男，1969年生，博士研究生，主要研究方向为软件工程与数据库技术；杨路明，男，1947年生，教授，博士生导师，主要研究方向为信息系统与数据库技术，发表学术论文40余篇；邓云龙，男，1962年生，教授，博士生导师，博士，主要研究方向为软件心理学。获得科研教学成果多项，发表学术论文50余篇。
通讯作者：刘波，E-mail:ltbo99@yahoo.com.cn
更新日期/Last Update:
2009-05-14