Temporal and Spatio-Temporal Data Mining

Spatio-temporal databases have been the subjects of a significant amount of academic and industrial research, resulting in advances including modeling, indexing and moving of objects and spatio-temporal data. This addresses one of the issues in such research, which is mining topological patterns in such databases by imposing temporal constraints into the process of mining spatial collocation patterns. Using a variety of techniques, including two partition-based algorithms designed by the authors, this gives background and advanced research into mining dense periodic patterns in time series databases, mining sequence patterns in evolving databases, mining progressive confident rules in sequence databases, understanding early works in spatio-temporal mining, mining topological patterns, mining flow patterns, mining generalized flow patterns, mining spatio-temporal trees and graph patterns, and preparing for future advances in the field. Annotation c2007 Book News, Inc., Portland, OR (booknews.com)