A Semantic Summarization Approach to Data Warehousing and Online Analytical Processing

本计画的目标是系统地研究及发展一个语意摘要方法，以应用于资料仓储及线上分析处理。研究内容包括：（1）数据立方体语义摘要方法的开发;（2）语义摘要立方体的有效实现和利用，包括数据存储、索引和查询应答。更广泛的影响：该项目的结果将为支持决策的有效和高效的数据探索提供新的方法。同时也将为数据挖掘、数据可视化和交互式数据探索等高级数据分析的相关研究带来有益的启示。在这个项目中开发的技术将在一个研究原型中得到说明，该原型将用于相关课程，并在互联网上提供。有关数据仓库和数据挖掘的课程将在developed.http://www.cse.buffalo.edu/faculty/jianpei/semolap上提供。

The goal of this project is to systematically study and develop a semantic summarization approach for data warehousing and online analytical processing. The research consists of (1) development of semanticsummarization methods in data cubes; and (2) efficient implementation and utilizations of semantic summarization cubes, including data storage, index and query answering. Broader impacts: The results of this project will provide novel methods for effective and efficient data exploration that supports decision making. They will also bring benefits to some other related researches on advanced data analysis, including data mining, data visualization and interactive data exploration. The techniques developed in this project will be illustrated in a research prototype, which will be used in the related courses and also made available on the internet. A course on data warehousing and data mining will be developed.http://www.cse.buffalo.edu/faculty/jianpei/semolap