Two experiments used eyetracking during reading to examine the processing of the matrix verb following object and subject relative clauses. The experiments show that the processing of the matrix verb following an object relative is indeed slowed compared to the processing of the same verb following a subject relative. However, this difficulty is…

Classic accounts of lexical organization posit that humans are sensitive to environmental frequency, suggesting a mechanism for word learning based on repetition. However, a recent spate of evidence has revealed that it is not simply frequency but the diversity and distinctiveness of contexts in which a word occurs that drives lexical…

This study shows that the presence of a tip-of-the-tongue (TOT) state--the sense that a word is in memory when its retrieval fails--is used as a heuristic for inferring that an inaccessible word has characteristics that are consistent with greater word perceptibility. When reporting a TOT state, people judged an unretrieved word as more likely to…

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…

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…

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…

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…

With the increasing wealth of information on the Web, information integration is ubiquitous as the same real-world entity may appear in a variety of forms extracted from different sources. This dissertation proposes supervised and unsupervised algorithms that are naturally integrated in a scalable framework to solve the entity resolution problem,…

Radiology data, in the form of images and reports, is growing at a high rate due to the introduction of new imaging modalities, new uses of existing modalities, and the growing importance of objective image information in the diagnosis and treatment of patients. This increase has resulted in an enormous set of image data that is richly annotated…

This paper reports on a guided navigation system built on the textbook search engine developed at Anadolu University to support distance education students. The search engine uses Turkish Language specific language processing modules to enable searches over course material presented in Open Education Faculty textbooks. We implemented a guided…

Processing language requires the retrieval of concepts from memory in response to an ongoing stream of information. This retrieval is facilitated if one can infer the gist of a sentence, conversation, or document and use that gist to predict related concepts and disambiguate words. This article analyzes the abstract computational problem…

A central question in online human sentence comprehension is, "How are linguistic relations established between different parts of a sentence?" Previous work has shown that this dependency resolution process can be computationally expensive, but the underlying reasons for this are still unclear. This article argues that dependency…

Tome Associates developed techniques to process natural language queries into search statements suitable for use in online text database systems. Problems discussed include word identification, handling of unknown words, system dictionaries, semantic categories and classification, truncation, stemming, disambiguation of multimeaning words, noun…

Discussion of electronic mail messages processing focuses on threads, which are conversations among two or more people carried out by exchange of messages. Suggests that effective threading systems should rely on conventions in human communication rather than on software communication, and shows that information retrieval techniques can be used…

Focuses on the structure/function relationship of the brain and language. Reviews the basic theories concerning cortical structures and language representation. Presents a call that highlights the need to examine the areas of listening, memory, and information retrieval for a more sophisticated analysis of the complex relationship between cortical…