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浙江大学学报(工学版)
J4  2012, Vol. 46 Issue (6): 974-979    DOI: 10.3785/j.issn.1008-973X.2012.06.003
计算机技术     
基于数据仓库内在特征的OLAP关键词查询
肖敏1,2, 陈岭1, 夏海元3, 陈根才1
1.浙江大学 计算机科学与技术学院, 浙江 杭州 310027；2.中国人民解放军75733部队, 广东 广州 510800；
3.浙江省公安厅, 浙江 杭州 310009
Data warehouse native feature based OLAP querying with keywords
XIAO Min1,2, CHEN Iing1, XIA Hai-yuan3, CHEN Gen-cai1
1. College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China;
2. PLA 75733, Guangzhou 510800, China； 3. Department of State Security, Zhejiang Province, Hangzhou 310009, China
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摘要：

 提出基于数据仓库多维模型维度及维度属性特征的联机分析处理(OLAP)关键词查询方法,将获得广泛应用的关键词查询方法和OLAP结合,可大大降低OLAP应用的门槛.该方法用列结构创建数据仓库维度全文索引,根据用户输入的查询获得按关键词划分的命中集,对命中集进行连接并排序后将产生的候选结果提供给用户.该方法基于对数据仓库用户更加关注概要性数据的特性,以及多维模型维度及其属性的非均衡型特征的分析,采用过滤不相关维度属性及重复维度列值的方法,并在传统的全文检索排序算法上增加维度层次权重系数.在MS SQL Server提供的FoodMart和AdventureWorks示例数据集上的实验对上述因素的影响做出了比较和分析,结果表明,首选候选结果命中率均优于基于关键词的分析处理方法.
Abstract:

 In order to support naive users to use on-line analytical processing (OLAP) tools, this work proposed a native feature of the dimension and its attributes for the multidimensional model of data warehouse based OLAP query method, which combined OLAP and search engine-alike methods. The method firstly created column based full-text index for dimension tables, secondly generated hit groups in terms of the keywords provided by the user, then constructed a candidate result set by joining these hit groups, and finally presented the ranked results to the user. Based on the features that a user cared much more about the aggregated data and the imbalance of the dimensions and their attributes, irrelative attributes and repeated column values were filtered in proposed method to relieve the negative effects on the ranking results. A weighted coefficient, named dimensional level coefficient (DLC) was also introduced to the text ranking arithmetic. Experiments were conducted on the FoodMart and AdventureWorks provided by Microsoft SQL Server to confirm how these factors influenced the hitting rate. The results indicated that the proposed method achieved a higher hitting rate than the keyword-driven analytical processing (KDAP) methods for the first candidate.
出版日期: 2012-07-24
:  TP 311  
基金资助:

国家“核高基”重大科技专项课题资助项目（2010ZX01042002003）;国家自然科学基金资助项目（60703040）;浙江省科技计划重大资助项目（2007C13019）.
通讯作者: 陈岭，男，副教授.     E-mail: lingchen@cs.zju.edu.cn
作者简介: 肖敏（1978—），男，博士生，从事数据仓库、商业智能和数据挖掘研究，E-mail:xiaomin1978@zju.edu.cn
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引用本文:

肖敏, 陈岭, 夏海元, 陈根才. 基于数据仓库内在特征的OLAP关键词查询[J]. J4, 2012, 46(6): 974-979.

XIAO Min, CHEN Iing, XIA Hai-yuan, CHEN Gen-cai. Data warehouse native feature based OLAP querying with keywords. J4, 2012, 46(6): 974-979.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2012.06.003    或    http://www.zjujournals.com/eng/CN/Y2012/V46/I6/974

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