Knowledge Discovery from Interval Sequence Data

This book addresses several issues related to the§pattern discovery from interval sequence data. This§area of research has received relatively little§attention and there are still many issues that need§to be addressed. Three main issues that this book§considers include the definition of what constitutes§an interesting pattern in interval sequence data, the§efficient mining for patterns in the data, and the§identification of interesting patterns from a large§number of discovered patterns.§§In order to deal with these issues, we formulates the§problem of discovering rules, which we term richer§temporal association rules, from interval sequence§databases. Furthermore, we develops an efficient§algorithm, ARMADA, for discovering richer temporal§association rules. The algorithm utilizes a simple§index, and only requires at most two database scans.§A retrieval system is proposed to facilitate the§selection of interesting rules from a set of§discovered richer temporal association rules. This§book is useful for readers who are interested in§utilizing data mining methods for analyzing interval§sequence data.