Discovering metric temporal constraint networks on temporal databases

Conclusions: A temporal data mining technique for discovering frequent temporal patterns in collections of time-stamped event sequences is presented. The resulting patterns describe different and distinguishable temporal arrangements among sets of event types in terms of repetitive appearance and similarity of the dispositions between the same events. ASTPminer allows users to participate in the mining process by introducing domain knowledge in the form of a temporal pattern using the STP formalism. This knowledge constrains the search to patterns consistent with the provided pattern and improves the performance of the procedure.
Source: Artificial Intelligence in Medicine - Category: Bioinformatics Authors: Tags: Research Articles Source Type: research