Studying CSSR Algorithm Applicability on NLP Tasks

CSSR algorithm learns automata representing the patterns of a process from sequential data. This paper studies the applicability of CSSR to some Noun Phrase detection. The ability of the algorithm to capture the patterns behind this tasks and the conditions under which it performs better are studied. Also, an approach to use the acquired models to annotate new sentences is pointed out and, at the sight of all results, the applicability of CSSR to NLP tasks is discussed.