Building the data warehouse (2nd ed.)
Building the data warehouse (2nd ed.)
An overview of data warehousing and OLAP technology
ACM SIGMOD Record
Decision Support Systems - Special issue on WITS '97
Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Totals
Data Mining and Knowledge Discovery
On the Computation of Multidimensional Aggregates
VLDB '96 Proceedings of the 22th International Conference on Very Large Data Bases
The Catch data warehouse: support for community health care decision-making
Decision Support Systems
On the discovery of significant statistical quantitative rules
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Using Datacube Aggregates for Approximate Querying and Deviation Detection
IEEE Transactions on Knowledge and Data Engineering
Decision support for selecting optimal logistic regression models
Expert Systems with Applications: An International Journal
Hi-index | 12.06 |
In the questionnaire analysis, how to find a statistically significant difference between two or more groups in a continuous measure is one of the major problems in researches. However, it is difficult for researchers to solve the issue of finding possible statistically significant difference. There are two causes of this issue. The one is that the process of finding the statistically significant differences is highly dependent on researchers' intuition and experience, and the other is that the original questionnaire data may not be good enough to find the statistically significant differences. In this paper, we build a data warehouse and a forward-chaining rule-base expert system with three kinds of indicators, Increase, StepDown, and Dice, for drilling down the data warehouse to assist researchers in exploring the data to select appropriate statistics methods to find possible significant differences. The prototype of this expert system has been implemented, and the results of experiment about satisfaction survey showed finding the significant difference becomes easier, and users were interested in the idea of this system.