We consider the problem of actively learning the mean values of distributions associated with a finite number of options. The decision maker can select which option to generate t...
This paper describes the results of some experiments exploring statistical methods to infer syntactic categories from a raw corpus in an unsupervised fashion. It shares certain po...
This paper describes an approach to providing lexical information for natural language processing in unrestricted domains. A system of approximately 1200 morphological rules is us...
Abstract-- Text categorization is the task of assigning predefined categories to natural language text. With the widely used `bag of words' representation, previous researches...
This paper explores automatically detecting student zoning out while performing a spoken learning task. Standard supervised machine learning techniques were used to create classi...