摘要
多特征方用于计算复杂数据挖掘查询,具有多粒度上多个依赖聚集计算的典型特点。现有的立方体粒度计算技术可以有效计算分布和代数多特征方,整体多特征方还没有提出有效的计算方法。在分析整体多特征方查询特点的基础上提出了一种优化算法:先将立方体分块,再采用冰山查询技术动态选择数据,最后采用查询结果重用技术。实验表明,该优化算法能有效提高整体多特征方查询的性能。
Multi-feature cubes (MF-cubes) compute complex data mining queries involving multiple dependent aggregates at multiple granularities. Currently, most proposed cube computing algorithms efficiently process the distributive and algebraic MF-cubes. Yet, there is few algorithm for computing holistic MF-cubes. An algorithm is proposed to compute the Holistic MF-cubes, which combined three efficient techniques: Partition of data cube into smaller sub-cubes; A dynamic subset data selection strategy-iceberg query; Reuse the overlap result of previous queries. The experimental results show that the algorithm is highly efficient to the holistic MF-cubes queries.
出处
《计算机工程与设计》
CSCD
北大核心
2007年第6期1257-1260,共4页
Computer Engineering and Design
基金
澳大利亚ARC基金项目(DP0559536
DP0667060)
国家自然科学基金重大项目(60496327)
国家自然科学基金项目(60463003)
关键词
复杂查询
整体多特征方
冰山查询
多粒度计算
查询结果重用
complex queries
holistic multi-feature cubes
iceberg query
multiple granular computing
reuse query results