XML-OLAP: A multidimensional analysis framework for XML warehouses

被引:0
作者
Park, BK
Han, H
Song, IY
机构
[1] Dong A Univ, Pusan, South Korea
[2] Drexel Univ, Philadelphia, PA 19104 USA
来源
DATA WAREHOUSING AND KNOWLEDGE DISCOVERY, PROCEEDINGS | 2005年 / 3589卷
关键词
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Recently, a large number of XML documents are available on the Internet. This trend motivated many researchers to analyze them multi-dimensionally in the same way as relational data. In this paper, we propose a new framework for multidimensional analysis of XML documents, which we call XML-OLAP. We base XML-OLAP on XML warehouses where every fact data as well as dimension data are stored as XML documents. We build XML cubes from XML warehouses. We propose a new multidimensional expression language for XML cubes, which we call XML-MDX. XML-MDX statements target XML cubes and use XQuery expressions to designate the measure data. They specify text mining operators for aggregating text constituting the measure data. We evaluate XML-OLAP by applying it to a U.S. patent XML warehouse. We use XML-MDX queries, which demonstrate that XML-OLAP is effective for multi-dimensionally analyzing the U.S. patents.
引用
收藏
页码:32 / 42
页数:11
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