Sequential patterns for text categorization
Intelligent Data Analysis
Fast discovery of sequential patterns in large databases using effective time-indexing
Information Sciences: an International Journal
Fast extraction of gradual association rules: a heuristic based method
CSTST '08 Proceedings of the 5th international conference on Soft computing as transdisciplinary science and technology
Efficient mining of sequential patterns with time constraints: Reducing the combinations
Expert Systems with Applications: An International Journal
Sequential Patterns for Maintaining Ontologies over Time
OTM '08 Proceedings of the OTM 2008 Confederated International Conferences, CoopIS, DOA, GADA, IS, and ODBASE 2008. Part II on On the Move to Meaningful Internet Systems
Softening the blow of frequent sequence analysis: soft constraints and temporal accuracy
International Journal of Web Engineering and Technology
On mining multi-time-interval sequential patterns
Data & Knowledge Engineering
Knowledge gathering of fuzzy multi-time-interval sequential patterns
Information Sciences: an International Journal
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In this paper we consider the problem of discovering sequential patterns by handling time constraints. While sequential patterns could be seen as temporal relationships between facts embedded in the database, generalized sequential patterns aim at providing the end user with a more flexible handling of the transactions embedded in the database. We propose a new efficient algorithm, called GTC (Graph for Time Constraints) for mining such patterns in very large databases. It is based on the idea that handling time constraints in the earlier stage of the algorithm can be highly beneficial since it minimizes computational costs by preprocessing data sequences. Our test shows that the proposed algorithm performs significantly faster than a stateof- the-art sequence mining algorithm.