Fuzzy Sets and Systems - Special issue: fuzzy sets: where do we stand? Where do we go?
NIPS '97 Proceedings of the 1997 conference on Advances in neural information processing systems 10
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets: Theoretical Aspects of Reasoning about Data
Rough Sets and Data Mining: Analysis of Imprecise Data
Rough Sets and Data Mining: Analysis of Imprecise Data
Data Analysis and Mining in Ordered Information Tables
ICDM '01 Proceedings of the 2001 IEEE International Conference on Data Mining
Using Background Knowledge as a Bias to Control the Rule Discovery Process
PKDD '00 Proceedings of the 4th European Conference on Principles of Data Mining and Knowledge Discovery
Boolean Reasoning for Feature Extraction Problems
ISMIS '97 Proceedings of the 10th International Symposium on Foundations of Intelligent Systems
WI based multi-aspect data analysis in a brain informatics portal
AIS-ADM'07 Proceedings of the 2nd international conference on Autonomous intelligent systems: agents and data mining
Spiral multi-aspect hepatitis data mining
AM'03 Proceedings of the Second international conference on Active Mining
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Ordered information is a kind of useful background knowledge to guide a discovery process toward finding different types of novel rules and improving their quality for many real world data mining tasks. In the paper, we investigate ways of using ordered information for gastric cancer data mining, based on rough set theory and granular computing. With respect to the notion of ordered information tables, we describe how to mine ordering rules and how to form granules of values of attributes in a pre/post-processing step for improving the quality of the mined classification rules. Experimental results in gastric cancer data mining show the usefulness and effectiveness of our approaches.