Abstract
Sequence data are subject to uncertainties in many applications due to incompleteness and imprecision of data. We propose a novel formulation of probabilistic sequential pattern discovering problem and an algorithm UCMiner to discover probabilistic sequential pattern in uncertain sequence database. Extensive experiments evaluate the factors impact our techniques and shows that our approach is significantly faster than a naïve approach.
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http://archive.ics.uci.edu/ml/datasets/Molecular+Biology+%28Promoter+Gene+Sequences%29
http://archive.ics.uci.edu/ml/datasets/Molecular+Biology+%28Splice-unction+Gene+Sequences%29
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Wan, L. (2011). Discovering Probabilistic Sequential Pattern in Uncertain Sequence Database. In: Shen, G., Huang, X. (eds) Advanced Research on Computer Science and Information Engineering. CSIE 2011. Communications in Computer and Information Science, vol 153. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21411-0_20
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DOI: https://doi.org/10.1007/978-3-642-21411-0_20
Publisher Name: Springer, Berlin, Heidelberg
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