It is standardly believed that some occurrences of expressions designate singularly, while other occurrences of expressions designate plurally. For instance, the singular expression the student may be used on an occasion to talk about one particular student, while the plural expression the students may be used on an occasion to talk about several…

Natural language is highly complex and can be challenging for some learners, yet the contribution of complexity to individual differences in language learning remains poorly understood. This poor understanding appears due to both a lack of consensus among researchers regarding what complexity is, and to on-line language research often employing…

The evolution of the Web brought new interesting problems to computer scientists that we loosely classify in the fields of social and semantic computing. Social computing is related to two major paradigms: computations carried out by a large amount of people in a collective intelligence fashion (i.e. wikis), and performing computations on social…

Word frequency is a powerful predictor of language processing efficiency in healthy individuals and in computational models. Puzzlingly, frequency effects are often absent in stroke aphasia, challenging the assumption that word frequency influences the behavior of any computational system. To address this conundrum, we investigated divergent…

Question answering systems have frequently been explored for educational use. However, their value was somewhat limited due to the quality of the answers returned to the student. Recent question answering (QA) research has started to incorporate deep natural language processing (NLP) in order to improve these answers. However, current NLP…

Domain adaptation of natural language processing systems is challenging because it requires human expertise. While manual effort is effective in creating a high quality knowledge base, it is expensive and time consuming. Clinical text adds another layer of complexity to the task due to privacy and confidentiality restrictions that hinder the…

Most words are associated with multiple senses. A DVD can be round (when describing a disc), and a DVD can be an hour long (when describing a movie), and in each case DVD means something different. The possible senses of a word are often predictable, and also constrained, as words cannot take just any meaning: for example, although a movie can be…

Research in automated creation of test items for assessment purposes became increasingly important during the recent years. Due to automatic question creation it is possible to support personalized and self-directed learning activities by preparing appropriate and individualized test items quite easily with relatively little effort or even fully…

This thesis aims to define and extend a line of computational models for text comprehension that are humanly plausible. Since natural language is human by nature, computational models of human language will always be just that--models. To the degree that they miss out on information that humans would tap into, they may be improved by considering…

Much recent work in natural language processing treats linguistic analysis as an inference problem over graphs. This development opens up useful connections between machine learning, graph theory, and linguistics. The first part of this dissertation formulates syntactic dependency parsing as a dynamic Markov random field with the novel…

An ontology is an effective formal representation of knowledge used commonly in artificial intelligence, semantic web, software engineering, and information retrieval. In open and distance learning, ontologies are used as knowledge bases for e-learning supplements, educational recommenders, and question answering systems that support students with…

The deep semantic understanding necessary for complex natural language processing tasks, such as automatic question-answering or text summarization, would benefit from highly accurate word sense disambiguation (WSD). This dissertation investigates what makes an appropriate and effective sense inventory for WSD. Drawing on theories and…

For over 30 years, reference resolution, the process of determining what a noun phrase including a pronoun refers to in written and spoken language, has been an important and on-going area of research. Most existing pronominal reference resolution algorithms and systems are designed to use syntactic information and surface features (e.g. number…

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…

In this study I introduce BioFrameNet, an extension of the Berkeley FrameNet lexical database to the domain of molecular biology. I examine the syntactic and semantic combinatorial possibilities exhibited in the lexical items used in this domain in order to get a better understanding of the grammatical properties of the language used in scientific…