Abstract:Abstract. Hidden markov models (HMMs) and prediction by partial matching models (PPM) have been successfully used in language processing tasks including learning-based token identification. Most of the existing systems are domainand language-dependent. The power of retargetability and applicability of these systems is limited. This paper investigates the effect of the combination of HMMs and PPM on token identification. We implement a system that bridges the two well known methods through words new to the iden… Show more
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