Temporal reasoning based on semi-intervals
Artificial Intelligence
PODS '96 Proceedings of the fifteenth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
ACM Transactions on Information Systems (TOIS)
Maintaining knowledge about temporal intervals
Communications of the ACM
SPADE: an efficient algorithm for mining frequent sequences
Machine Learning
Discovery of Frequent Episodes in Event Sequences
Data Mining and Knowledge Discovery
A Survey of Temporal Knowledge Discovery Paradigms and Methods
IEEE Transactions on Knowledge and Data Engineering
Mining Sequential Patterns: Generalizations and Performance Improvements
EDBT '96 Proceedings of the 5th International Conference on Extending Database Technology: Advances in Database Technology
ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
ICDE '98 Proceedings of the Fourteenth International Conference on Data Engineering
PrefixSpan: Mining Sequential Patterns by Prefix-Projected Growth
Proceedings of the 17th International Conference on Data Engineering
Association Rules & Evolution in Time
SETN '02 Proceedings of the Second Hellenic Conference on AI: Methods and Applications of Artificial Intelligence
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
DaWaK '99 Proceedings of the First International Conference on Data Warehousing and Knowledge Discovery
Discovering Temporal Patterns for Interval-Based Events
DaWaK 2000 Proceedings of the Second International Conference on Data Warehousing and Knowledge Discovery
Fast Discovery of Sequential Patterns by Memory Indexing
DaWaK 2000 Proceedings of the 4th International Conference on Data Warehousing and Knowledge Discovery
Discovering Calendar-Based Temporal Association Rules
TIME '01 Proceedings of the Eighth International Symposium on Temporal Representation and Reasoning (TIME'01)
Linear Temporal Sequences and Their Interpretation Using Midpoint Relationships
IEEE Transactions on Knowledge and Data Engineering
Data mining with Temporal Abstractions: learning rules from time series
Data Mining and Knowledge Discovery
Domain ontology driven data mining: a medical case study
Proceedings of the 2007 international workshop on Domain driven data mining
Precedence Temporal Networks to represent temporal relationships in gene expression data
Journal of Biomedical Informatics
Temporal Data Mining with Temporal Constraints
AIME '07 Proceedings of the 11th conference on Artificial Intelligence in Medicine
Temporal mining for interactive workflow data analysis
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Mining frequent arrangements of temporal intervals
Knowledge and Information Systems
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Temporal association rule mining promises the ability to discover time-dependent correlations or patterns between events in large volumes of data. To date, most temporal data mining research has focused on events existing at a point in time rather than over a temporal interval. In comparison to static rules, mining with respect to time points provides semantically richer rules. However, accommodating temporal intervals offers rules that are richer still. In this paper we outline a new algorithm to discover frequent temporal patterns and to generate richer interval-based temporal association rules.