Mining of Sequential Patterns with Constraint in Large Databases

Constraint-based mining of sequential patterns is an active research area motivated by many application domains. In practice, the real sequence datasets can present consecutive repetitions of symbols (e.g., DNA sequences, discredited stock market data) that can lead to a very important consumption of resources during the extraction of patterns that can turn even efficient algorithms to become unusable. In this paper, the authors investigate this issue and point out that the framework developed for constrained frequent-pattern mining does not fit their missions well.

Provided by: International Journal on Computer Science and Technology (IJCST) Topic: Data Management Date Added: Dec 2012 Format: PDF

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