| 面向大型数据集合的关键分类查找算法 |
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| 引用本文： | 许晓峰,金澈清,高明,周傲英. 面向大型数据集合的关键分类查找算法[J]. 计算机研究与发展, 2009, 46(Z2) |
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| 作者姓名： | 许晓峰 金澈清 高明 周傲英 |
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| 作者单位： | 1. 复旦大学计算机科学技术学院上海市智能信息处理重点实验室,上海,200433
2. 华东师范大学软件学院上海市高可信计算重点实验室,上海,200062 |
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| 基金项目： | 国家自然科学基金项目，教育部博士点新教师基金项目，上海市重点学科建设基金项目 |
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| 摘 要： | Top-k查询是Web和多媒体搜索、决策支持、分布式系统等众多领域中最重要的查询之一,它返回数据集合中k个最关键的元组.大型数据集合往往包含一系列分类型属性,获取对目标属性影响最大的k个分类型属性值对于许多应用中也非常重要.研究了这个问题,正式定义了k-AKC和PKC两种查询,并设计相应的查询处理算法.实验结果表明,改良算法PKCQ+具有较佳的有效性和高效性.
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| 关 键 词： | 分类数据 不确定数据模型 可能世界模型 Top-k查询 |
Towards Finding Key Categories Oil Massive Datasets |
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| Xu Xiaofeng,Jin Cheqing,Gao Ming,Zhou Aoying. Towards Finding Key Categories Oil Massive Datasets[J]. Journal of Computer Research and Development, 2009, 46(Z2) |
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| Authors: | Xu Xiaofeng Jin Cheqing Gao Ming Zhou Aoying |
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| Abstract: | Top-k query,which returns k most critical tuples in a dataset,is one of the most important queries in many applications such as Web and multimedia search,decision making support,distributed systems,etc.Massive datasets often have a number of categorical attributes.How to get k categorical attribute values with greatest impact to the object attribute is also critical for some applications.The problem is studied in this paper.And the two queries,k-AKC and PKC,are formally defined.In addition,the authors design the processing algorithms to answer the queries.The experimenal results show that the optimized algorithm,PKCQ+,is more effective and efficient. |
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| Keywords: | categorical data uncertain data model possible world model Top-k queries |
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