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ALMOB
2006

Mining, compressing and classifying with extensible motifs

13 years 4 months ago
Mining, compressing and classifying with extensible motifs
Background: Motif patterns of maximal saturation emerged originally in contexts of pattern discovery in biomolecular sequences and have recently proven a valuable notion also in the design of data compression schemes. Informally, a motif is a string of intermittently solid and wild characters that recurs more or less frequently in an input sequence or family of sequences. Motif discovery techniques and tools tend to be computationally imposing, however, special classes of "rigid" motifs have been identified of which the discovery is affordable in low polynomial time. Results: In the present work, "extensible" motifs are considered such that each sequence of gaps comes endowed with some elasticity, whereby the same pattern may be stretched to fit segments of the source that match all the solid characters but are otherwise of different lengths. A few applications of this notion are then described. In applications of data compression by textual substitution, extensibl...
Alberto Apostolico, Matteo Comin, Laxmi Parida
Added 10 Dec 2010
Updated 10 Dec 2010
Type Journal
Year 2006
Where ALMOB
Authors Alberto Apostolico, Matteo Comin, Laxmi Parida
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