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(1 - 5 of 5)
- Title
- SEMANTIC BIAS AS AN APPLICATION OF THE UNIVERSAL GRAMMAR MODEL IN THE RUSSIAN LANGUAGE.
- Creator
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Gural, Iryna, Modianos, Doan T., Villegas, Alvaro, University of Central Florida
- Abstract / Description
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The theory of the Universal Grammar developed by Chomsky has been known for many years. The main idea behind the theory was that the processing of the language does not depend on the culture but it universal among all the languages. Further psycholinguistic studies developed the ideas about schematic comprehension of the language, giving rise to the idea of the "garden path effect". Research focused on the processing of the ambiguous sentences and found the tendency for readers to prefer...
Show moreThe theory of the Universal Grammar developed by Chomsky has been known for many years. The main idea behind the theory was that the processing of the language does not depend on the culture but it universal among all the languages. Further psycholinguistic studies developed the ideas about schematic comprehension of the language, giving rise to the idea of the "garden path effect". Research focused on the processing of the ambiguous sentences and found the tendency for readers to prefer interpretations of specific sentence areas as objects. The current study summarizes the ideas of psycholinguistic study and incorporates a novel language structure to study readers' syntactic preferences. In addition, conducting the study in Russian language accompanies previous research in other languages, also arguing in favor of the Universal Grammar model given the hypothesis was supported. It was hypothesized that readers would prefer the comparison of the two direct objects over the subjects, which would be reflected by faster reading times. Self-paced reading ask was administered to the participants in order to measure their reading times. The analysis found no significant differences in the reading times of the critical area, thus hypothesis was not supported. Possible explanations, limitations, and further directions are discussed.
Show less - Date Issued
- 2019
- Identifier
- CFH2000513, ucf:45697
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFH2000513
- Title
- Automatically Acquiring a Semantic Network of Related Concepts.
- Creator
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Szumlanski, Sean, Gomez, Fernando, Wu, Annie, Hughes, Charles, Sims, Valerie, University of Central Florida
- Abstract / Description
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We describe the automatic acquisition of a semantic network in which over 7,500 of the most frequently occurring nouns in the English language are linked to their semantically related concepts in the WordNet noun ontology. Relatedness between nouns is discovered automatically from lexical co-occurrence in Wikipedia texts using a novel adaptation of an information theoretic inspired measure. Our algorithm then capitalizes on salient sense clustering among these semantic associates to...
Show moreWe describe the automatic acquisition of a semantic network in which over 7,500 of the most frequently occurring nouns in the English language are linked to their semantically related concepts in the WordNet noun ontology. Relatedness between nouns is discovered automatically from lexical co-occurrence in Wikipedia texts using a novel adaptation of an information theoretic inspired measure. Our algorithm then capitalizes on salient sense clustering among these semantic associates to automatically disambiguate them to their corresponding WordNet noun senses (i.e., concepts). The resultant concept-to-concept associations, stemming from 7,593 target nouns, with 17,104 distinct senses among them, constitute a large-scale semantic network with 208,832 undirected edges between related concepts. Our work can thus be conceived of as augmenting the WordNet noun ontology with RelatedTo links.The network, which we refer to as the Szumlanski-Gomez Network (SGN), has been subjected to a variety of evaluative measures, including manual inspection by human judges and quantitative comparison to gold standard data for semantic relatedness measurements. We have also evaluated the network's performance in an applied setting on a word sense disambiguation (WSD) task in which the network served as a knowledge source for established graph-based spreading activation algorithms, and have shown: a) the network is competitive with WordNet when used as a stand-alone knowledge source for WSD, b) combining our network with WordNet achieves disambiguation results that exceed the performance of either resource individually, and c) our network outperforms a similar resource, WordNet++ (Ponzetto (&) Navigli, 2010), that has been automatically derived from annotations in the Wikipedia corpus.Finally, we present a study on human perceptions of relatedness. In our study, we elicited quantitative evaluations of semantic relatedness from human subjects using a variation of the classical methodology that Rubenstein and Goodenough (1965) employed to investigate human perceptions of semantic similarity. Judgments from individual subjects in our study exhibit high average correlation to the elicited relatedness means using leave-one-out sampling (r = 0.77, ? = 0.09, N = 73), although not as high as average human correlation in previous studies of similarity judgments, for which Resnik (1995) established an upper bound of r = 0.90 (? = 0.07, N = 10). These results suggest that human perceptions of relatedness are less strictly constrained than evaluations of similarity, and establish a clearer expectation for what constitutes human-like performance by a computational measure of semantic relatedness. We also contrast the performance of a variety of similarity and relatedness measures on our dataset to their performance on similarity norms and introduce our own dataset as a supplementary evaluative standard for relatedness measures.
Show less - Date Issued
- 2013
- Identifier
- CFE0004759, ucf:49767
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0004759
- Title
- A STUDY OF SEMANTIC PROCESSING PERFORMANCE.
- Creator
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Dever, Daryn A, Szalma, James, Neigel, Alexis, University of Central Florida
- Abstract / Description
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Examining the role of individual differences, especially variations in human motivation, in vigilance tasks will result in a better understanding of sustained semantic attention and processing, which has, to date, received limited study in the literature (see Fraulini, Hancock, Neigel, Claypoole, & Szalma, 2017; Epling, Russell, & Helton, 2016; Thomson et al., 2016). This present study seeks to understand how individual differences in intrinsic motivation affect performance in a short...
Show moreExamining the role of individual differences, especially variations in human motivation, in vigilance tasks will result in a better understanding of sustained semantic attention and processing, which has, to date, received limited study in the literature (see Fraulini, Hancock, Neigel, Claypoole, & Szalma, 2017; Epling, Russell, & Helton, 2016; Thomson et al., 2016). This present study seeks to understand how individual differences in intrinsic motivation affect performance in a short semantic vigilance task. Performance across two conditions (lure vs. standard condition) were compared in the present study of 79 undergraduate students at the University of Central Florida. The results indicated significant main effects of intrinsic motivation on pre- and post-task stress factors, workload, and performance measures, which included correct detections, false alarms, and response time. Sensitivity and response bias, which are indices of signal detection theory, were also examined in the present study. Intrinsic motivation influenced sensitivity, but not response bias, which was affected by period on watch. The theoretical and practical implications of this research are also discussed.
Show less - Date Issued
- 2017
- Identifier
- CFH2000245, ucf:45984
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFH2000245
- Title
- GREEN BUILDING: PUBLIC OPINION, SEMANTICS, AND HEURISTIC PROCESSING.
- Creator
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Webb, Christina, Schraufnagel, Scot, University of Central Florida
- Abstract / Description
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Research on public support for green building has, to date, been incomplete. Understanding the demographics of individuals that support green building has remained secondary to merely determining real opinions on the topic. The identity of supporters and the motivation behind their support is the focus of this research. Specifically, is support for green building dependent on the way in which the issue is framed? This research aims to focus on those that are spreading the message about green...
Show moreResearch on public support for green building has, to date, been incomplete. Understanding the demographics of individuals that support green building has remained secondary to merely determining real opinions on the topic. The identity of supporters and the motivation behind their support is the focus of this research. Specifically, is support for green building dependent on the way in which the issue is framed? This research aims to focus on those that are spreading the message about green building, industry experts, and the mass public. By exposing how green building experts talk about the issue, we may begin to understand why public support for green building has yet to reach the kind of mainstream acceptance other planning and design techniques have,such as New Urbanism. I predict that green building experts perceived low levels of public awareness, with the exception of those within the Northwest region, which I believ will perceive higher levels of awareness. In addition, I assume that industry experts will be most focused on energy efficiency as a primary concept of green building. As for the public, I hypothesize that those aware of green building and individuals age 50 and older will be more likely to support green building. With the introduction of source cues, I expect that support for green building will decrease when respondents received either an environmentalism cue or a government program cue. Using survey instruments, I was able to determine that all green building experts perceive public awareness as low and do, in fact, focus their efforts on energy efficiency. With regards to the public, support was highest among those that are aware, as well as those age 50 and older. In addition, insertion of source cues decreased support for green building, with the government program source cue providing the lowest levels of support for green building.
Show less - Date Issued
- 2005
- Identifier
- CFE0000600, ucf:46525
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0000600
- Title
- THE ACQUISITION OF LEXICAL KNOWLEDGE FROM THE WEB FOR ASPECTS OF SEMANTIC INTERPRETATION.
- Creator
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Schwartz, Hansen, Gomez, Fernando, University of Central Florida
- Abstract / Description
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This work investigates the effective acquisition of lexical knowledge from the Web to perform semantic interpretation. The Web provides an unprecedented amount of natural language from which to gain knowledge useful for semantic interpretation. The knowledge acquired is described as common sense knowledge, information one uses in his or her daily life to understand language and perception. Novel approaches are presented for both the acquisition of this knowledge and use of the knowledge in...
Show moreThis work investigates the effective acquisition of lexical knowledge from the Web to perform semantic interpretation. The Web provides an unprecedented amount of natural language from which to gain knowledge useful for semantic interpretation. The knowledge acquired is described as common sense knowledge, information one uses in his or her daily life to understand language and perception. Novel approaches are presented for both the acquisition of this knowledge and use of the knowledge in semantic interpretation algorithms. The goal is to increase accuracy over other automatic semantic interpretation systems, and in turn enable stronger real world applications such as machine translation, advanced Web search, sentiment analysis, and question answering. The major contributions of this dissertation consist of two methods of acquiring lexical knowledge from the Web, namely a database of common sense knowledge and Web selectors. The first method is a framework for acquiring a database of concept relationships. To acquire this knowledge, relationships between nouns are found on the Web and analyzed over WordNet using information-theory, producing information about concepts rather than ambiguous words. For the second contribution, words called Web selectors are retrieved which take the place of an instance of a target word in its local context. The selectors serve for the system to learn the types of concepts that the sense of a target word should be similar. Web selectors are acquired dynamically as part of a semantic interpretation algorithm, while the relationships in the database are useful to stand-alone programs. A final contribution of this dissertation concerns a novel semantic similarity measure and an evaluation of similarity and relatedness measures on tasks of concept similarity. Such tasks are useful when applying acquired knowledge to semantic interpretation. Applications to word sense disambiguation, an aspect of semantic interpretation, are used to evaluate the contributions. Disambiguation systems which utilize semantically annotated training data are considered supervised. The algorithms of this dissertation are considered minimally-supervised; they do not require training data created by humans, though they may use human-created data sources. In the case of evaluating a database of common sense knowledge, integrating the knowledge into an existing minimally-supervised disambiguation system significantly improved results -- a 20.5\% error reduction. Similarly, the Web selectors disambiguation system, which acquires knowledge directly as part of the algorithm, achieved results comparable with top minimally-supervised systems, an F-score of 80.2\% on a standard noun disambiguation task. This work enables the study of many subsequent related tasks for improving semantic interpretation and its application to real-world technologies. Other aspects of semantic interpretation, such as semantic role labeling could utilize the same methods presented here for word sense disambiguation. As the Web continues to grow, the capabilities of the systems in this dissertation are expected to increase. Although the Web selectors system achieves great results, a study in this dissertation shows likely improvements from acquiring more data. Furthermore, the methods for acquiring a database of common sense knowledge could be applied in a more exhaustive fashion for other types of common sense knowledge. Finally, perhaps the greatest benefits from this work will come from the enabling of real world technologies that utilize semantic interpretation.
Show less - Date Issued
- 2011
- Identifier
- CFE0003688, ucf:48805
- Format
- Document (PDF)
- PURL
- http://purl.flvc.org/ucf/fd/CFE0003688
