Testing Complex Temporal Relationships Involving Multiple Granularities and Its Application to Data Mining
Summary: Defines event-structure temporal-constraint graphs with multiple granularities (TCGs), proves TCG consistency NP-hard and provides an approximation algorithm. Introduces timed automata with granularities (TAGs) to detect TCG instantiations in sequences for temporal-pattern mining. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Claudio Bettini (University of Milan)
- 2. X. Sean Wang (George Mason University)
- 3. Sushil Jajodia (George Mason University)
BibTeX Citation
@inproceedings{bettini_pods96,
address = {New York, NY, USA},
series = {{PODS} '96},
title = {{Testing Complex Temporal Relationships Involving Multiple Granularities and Its Application to Data Mining}},
url = {https://dl.acm.org/doi/10.1145/237661.237680},
doi = {10.1145/237661.237680},
booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
publisher = {Association for Computing Machinery},
author = {Bettini, Claudio and Wang, X. Sean and Jajodia, Sushil},
year = {1996}
}
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