In order to do more semantics-based information extraction, we require specialized domain models. We develop a hybrid approach for constructing such a domain-specific ontology, which integrates key concepts from the protein-protein–interaction domain with the Gene Ontology. In addition, we present a method for using the domain-specific ontology in a discourse-based analysis module for analyzing full-text articles on protein interactions. The analysis module uses a lexical chaining technique to extract strings of semantically related words that represent the topic structure of the text. We show that the domain-specific ontology improved the performance of the lexical-chaining module. As well the topic structure as represented by the lexical chains contains important information on protein-protein interactions appearing in the same textual context.

Two semantic priming experiments in the context of lexical decision are reported that examine the joint effects of stimulus quality, semantic context, and strength of association when all these factors are intermixed in a block of trials. A three-way interaction is seen in both experiments in which the typical interaction between semantic context and stimulus quality is eliminated when the strength of association between prime-target pairs is weak. The results support a role for a control mechanism that makes use of local information available within a trial, in addition to a global control mechanism that operates across a block of trials. The interaction between semantic context and stimulus quality when prime-target pairs are strongly related is attributed to the presence of feedback from the semantic system to the lexical system whereas additive effects of semantic context and stimulus quality is attributed to this feedback being eliminated such that semantic and lexical levels are functionally separate modules.

Measures of semantic distance have received a great deal of attention recently in the field of computational lexical semantics. Although techniques for approximating the semantic distance of two concepts have existed for several decades, the introduction of the WordNet lexical database and improvements in corpus analysis have enabled significant improvements in semantic distance measures. <br /><br /> In this study we investigate a special kind of semantic distance, called <em>semantic relatedness</em>. Lexical semantic relatedness measures have proved to be useful for a number of applications, such as word sense disambiguation and real-word spelling error correction. Most relatedness measures rely on the observation that the shortest path between nodes in a semantic network provides a representation of the relationship between two concepts. The strength of relatedness is computed in terms of this path. <br /><br /> This dissertation makes several significant contributions to the study of semantic relatedness. We describe a new measure that calculates semantic relatedness as a function of the shortest path in a semantic network. The proposed measure achieves better results than other standard measures and yet is much simpler than previous models. The proposed measure is shown to achieve a correlation of <em>r</em> = 0. 897 with the judgments of human test subjects using a standard benchmark data set, representing the best performance reported in the literature. We also provide a general formal description for a class of semantic distance measures &mdash; namely, those measures that compute semantic distance from the shortest path in a semantic network. Lastly, we suggest a new methodology for developing path-based semantic distance measures that would limit the possibility of unnecessary complexity in future measures.

Understanding interactions among words is fundamental for natural language applications. However, many statistical NLP methods still ignore this important characteristic of language. For example, information retrieval models still assume word independence. This work focuses on the creation of lexical affinity models and their applications to natural language problems. The thesis develops two approaches for computing lexical affinity. In the first, the co-occurrence frequency is the calculated by point estimation. The second uses parametric models for co-occurrence distances. For the point estimation approach, we study several alternative methods for computing the degree of affinity by making use of point estimates for co-occurrence frequency. We propose two new point estimators for co-occurrence and evaluate the measures and the estimation procedures with synonym questions. In our evaluation, synonyms are checked directly by their co-occurrence and also by comparing them indirectly, using other lexical units as supporting evidence. For the parametric approach, we address the creation of lexical affinity models by using two parametric models for distance co-occurrence: an independence model and an affinity model. The independence model is based on the geometric distribution; the affinity model is based on the gamma distribution. Both fit the data by maximizing likelihood. Two measures of affinity are derived from these parametric models and applied to the synonym questions, resulting in the best absolute performance on these questions by a method not trained to the task. We also explore the use of lexical affinity in information retrieval tasks. A new method to score missing terms by using lexical affinities is proposed. In particular, we adapt two probabilistic scoring functions for information retrieval to allow all query terms to be scored. One is a document retrieval method and the other is a passage retrieval method. Our new method, using replacement terms, shows significant improvement over the original methods.

In order to do more semantics-based information extraction, we require specialized domain models. We develop a hybrid approach for constructing such a domain-specific ontology, which integrates key concepts from the protein-protein–interaction domain with the Gene Ontology. In addition, we present a method for using the domain-specific ontology in a discourse-based analysis module for analyzing full-text articles on protein interactions. The analysis module uses a lexical chaining technique to extract strings of semantically related words that represent the topic structure of the text. We show that the domain-specific ontology improved the performance of the lexical-chaining module. As well the topic structure as represented by the lexical chains contains important information on protein-protein interactions appearing in the same textual context.

Two semantic priming experiments in the context of lexical decision are reported that examine the joint effects of stimulus quality, semantic context, and strength of association when all these factors are intermixed in a block of trials. A three-way interaction is seen in both experiments in which the typical interaction between semantic context and stimulus quality is eliminated when the strength of association between prime-target pairs is weak. The results support a role for a control mechanism that makes use of local information available within a trial, in addition to a global control mechanism that operates across a block of trials. The interaction between semantic context and stimulus quality when prime-target pairs are strongly related is attributed to the presence of feedback from the semantic system to the lexical system whereas additive effects of semantic context and stimulus quality is attributed to this feedback being eliminated such that semantic and lexical levels are functionally separate modules.

The aim of this study was to investigate how young adults who stutterer allocate attentional resources during two linguistic stages in picture naming, specifically lemma and lexeme retrieval. This study reports on behavioral and brain electrophysiological data collected during a simple auditory oddball task and a Dual Picture-Word Interference/Tone Monitoring Task.

The purpose of this thesis is to provide a review and discussion of the current literature on auditory processing, speech discrimination, word recognition, and early lexical representations in children with normal hearing and those with hearing impairment in addition to identifying areas in which current research is lacking. This information is needed to consider potential interactions between various factors affecting the development of spoken word recognition. This will also provide a starting point for identifying further research needs. Since children with hearing loss do not receive the same amount of exposure to speech and language as typically developing children, it can be expected that the development of speech and word recognition in this population may progress differently. If we can identify differences in auditory processing and phonological development in children with hearing impairment, we can modify speech and language therapy to focus on more specific and effective targets. The subsequent chapters will provide a critical review of the current literature on the aforementioned topics. In Chapters 2 and 3, studies assessing differences in processing, attention to sound, intersensory perception, and sound discrimination abilities in children with normal hearing and hearing impairment will be discussed. Chapters 4 and 5 focus on word recognition skills, and early lexical representations. Chapter 6 will synthesize results of available studies and suggest areas in which more research is needed. Together, these chapters will help us gain a better understanding of the complex interactions between auditory processing, executive functioning, phonological development and later word recognition outcomes. By identifying which avenues have the greatest effect on outcomes in cochlear implant users, we can modify speech and language therapy in order to address the unique needs of this special population. / text

In the Bantu language Kinyarwanda, the morpheme –ish can be used to mark both causation and the instrumental applicative. This report pro- poses an explanation for this causative-instrumental syncretism, arguing that both causation and the introduction of an instrument are—at their core—two outgrowths of the same semantic notion. Fitting with other morphological causatives in Bantu, the causative use of –ish patterns as a lexical causative marker. The analysis presented here captures the lex- ical nature of the causative use of the morpheme by arguing that the new causal link is added sub-lexically, situating Kinyarwanda into a cross- linguistic typology of morphological causatives. / text

published_or_final_version / Linguistics / Master / Master of Arts