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基于模糊数据模型的智能查询优化算法

Intelligent Query Optimization Algorithms Based on Fuzzy Data Model
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摘要 为实现对数据库信息查询时使用自然语言与计算机交流,提出了一种智能查询优化算法-IIOP算法;首创提出将模糊查询与相似查询结合的思想,其中模糊匹配查询更符合人脑思维特性,更合理有效;为提高查询效率,在进行查询时首先对原始数据序列提取能反映数据变化趋势的特征极值点,然后仅对特征极值点进行相似查询,极大减少了数据存储量,提高了查询计算速度。该算法经实验验证切实有效可行,相对其它算法能明显提高查询速度和准确率。 To achieve using natural language and computer communication information on the database query,presented an intelligent query optimization algorithms-IIOP algorithm. First proposed to combine fuzzy query and similarity query ideas,which match the query fuzzy thinking more in line with characteristics of the human brain,more reasonable and effective; To improve query efficiency in carrying out inquiries,first extract the original data sequence can reflect the characteristics of the data trend of extreme poin...
作者 左利云
出处 《微型电脑应用》 2010年第5期9-10,13+72,共4页 Microcomputer Applications
基金 广东省科技计划项目(2007B010400042) 广东省自然科学基金(06029274) 茂名市科技计划项目(20091009) 茂名学院基金项目(203492)
关键词 模糊查询 相似查询 特征极值点 Fuzzy Query Similar Query Characteristics of Extreme Points
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