We study the following three problems of computing generic or discriminating words for a given collection of documents. Given a pattern P and a threshold d, we want to report (i) all longest extensions of P which occur in at least d documents, (ii) all shortest extensions of P which occur in less than d documents, and (iii) all shortest extensions of P which occur only in d selected documents. For these problems, we propose efficient algorithms based on suffix trees and using advanced data structure techniques. For problem (i), we propose an optimal solution with constant running time per output word. © 2012 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Kucherov, G., Nekrich, Y., & Starikovskaya, T. (2012). Computing discriminating and generic words. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7608 LNCS, pp. 307–317). Springer Verlag. https://doi.org/10.1007/978-3-642-34109-0_32
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