A Semantic Summarization Approach to Data Warehouseing and Online Analytical Processing

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 semantic summarization 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