Advances in Knowledge Discovery in Databases

Introduction.- Synthesizing conditional patterns in a database.- Synthesizing arbitrary Boolean expressions induced by frequent itemsets.- Measuring association among items in a database.- Mining association rules induced by item and quantity purchased.- Mining patterns different related databases.- Mining icebergs in different time-stamped data sources.-Synthesizing exceptional patterns in different data Sources.- Clustering items in time-stamped databases.- Synthesizing some extreme association rules from multiple databases.- Clustering local frequency items in multiple data sources.- Mining patterns of select items in different data sources.- Mining calendar-based periodic patterns in time-stamped data.- Measuring influence of an item in time-stamped databases.- Clustering multiple databases induced by local patterns.- Enhancing quality of patterns in multiple related databases.- Concluding remarks.