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Ramotowska, Sonia; Steinert-Threlkeld, Shane; Maanen, Leendert; Szymanik, Jakub – Cognitive Science, 2023
According to logical theories of meaning, a meaning of an expression can be formalized and encoded in truth conditions. Vagueness of the language and individual differences between people are a challenge to incorporate into the meaning representations. In this paper, we propose a new approach to study truth-conditional representations of vague…
Descriptors: Computation, Models, Semantics, Decision Making
Allen, Laura K.; Snow, Erica L.; McNamara, Danielle S. – Grantee Submission, 2015
This study builds upon previous work aimed at developing a student model of reading comprehension ability within the intelligent tutoring system, iSTART. Currently, the system evaluates students' self-explanation performance using a local, sentence-level algorithm and does not adapt content based on reading ability. The current study leverages…
Descriptors: Reading Comprehension, Reading Skills, Natural Language Processing, Intelligent Tutoring Systems
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Hsu, Anne S.; Chater, Nick; Vitanyi, Paul M. B. – Cognition, 2011
There is much debate over the degree to which language learning is governed by innate language-specific biases, or acquired through cognition-general principles. Here we examine the probabilistic language acquisition hypothesis on three levels: We outline a novel theoretical result showing that it is possible to learn the exact "generative model"…
Descriptors: Linguistics, Prediction, Natural Language Processing, Language Acquisition
Rajkumar, Rajakrishnan – ProQuest LLC, 2012
Natural Language Generation (NLG) is the process of generating natural language text from an input, which is a communicative goal and a database or knowledge base. Informally, the architecture of a standard NLG system consists of the following modules (Reiter and Dale, 2000): content determination, sentence planning (or microplanning) and surface…
Descriptors: Natural Language Processing, Linguistics, Language Processing, Models
Boyd-Graber, Jordan – ProQuest LLC, 2010
Topic models like latent Dirichlet allocation (LDA) provide a framework for analyzing large datasets where observations are collected into groups. Although topic modeling has been fruitfully applied to problems social science, biology, and computer vision, it has been most widely used to model datasets where documents are modeled as exchangeable…
Descriptors: Language Patterns, Semantics, Linguistics, Multilingualism
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Bateman, John; Tenbrink, Thora; Farrar, Scott – Discourse Processes: A Multidisciplinary Journal, 2007
This article argues that a clear division between two sources of information--one oriented to world knowledge, the other to linguistic semantics--offers a framework within which mechanisms for modelling the highly flexible relation between language and interpretation necessary for natural discourse can be specified and empirically validated.…
Descriptors: Semantics, Linguistics, Teaching Methods, Models