The rate of occurrence of words is not uniform but varies from document to document. Despite this observation, parameters for conventional n-gram language models are usually derived using the assumption of a constant word rate. In this paper we investigate the use of variable word rate assumption, modelled by a Poisson distribution or a continuous mixture of Poissons. We present an approach to ...

In this paper we consider the detection of opinion spam as a stylistic classification task because, given a particular domain, the deceptive and truthful opinions are similar in content but differ in the way opinions are written (style). Particularly, we propose using character ngrams as features since they have shown to capture lexical content as well as stylistic information. We evaluated our...

This article reports pilot study results evaluating the accuracy of carbohydrate counting among adolescents with type 1 diabetes. This crosssectional observational study included 48 adolescents ages 12–18 years (mean 15.2 ± 1.8 years) with type 1 diabetes of > 1 year in duration (mean A1C 8.0 ± 1.0%) who used insulin:carbohydrate (I:C) ratios for at least one meal per day. The adolescents were ...

Statistical language models should improve as the size of the n-grams increases from 3 to 5 or higher. However, the number of parameters and calculations, and the storage requirement increase very rapidly if we attempt to store all possible combinations of n-grams. To avoid these problems, the reduced n-grams’ approach previously developed by O’Boyle (1993) can be applied. A reduced n-gram lang...

In spoken document retrieval, speech recognition is applied to a collection to obtain either words or subword units, such as phonemes, that can be matched against queries. We have explored retrieval based on phoneme n-grams. The use of phonemes addresses the out-of-vocabulary problem, while use of n-grams allows approximate matching on inaccurate phoneme transcriptions. Our experiments explored...