Thesis (Ed. D.)--West Virginia University, 1998. / Title from document title page. Document formatted into pages; contains ix, 244 p. : ill. (some col.). Includes abstract. Includes bibliographical references.

Thesis (Ph. D.)--University of Washington, 2004. / Vita. Includes bibliographical references (p.141-159 ).

Master-Arbeit Univ. St. Gallen, 2008.

Thesis (M.S.)--Brigham Young University. Dept. of Computer Science, 2006. / Includes bibliographical references (p. 43-46).

This study examines the relationship between language and cognition with a focus on Chinese numeral classifiers (CNCs). NCs are ideally suited to exploring the link between language and semantic categorization, as classifier selection depends on the physical attributes of the associated noun (e.g., Mandarin zhi is used for long and rigid objects and tiao for long and flexible objects). Previous studies on numeral classifiers have addressed the language-cognition link by comparing the cognitive performance of monolingual as well as bilingual speakers of different languages (Lucy, 1992; Saalbach & Imai, 2005; Gao & Malt, 2009). In contrast, the present study sought to address the cognitive effects of numeral classifiers via a training study that investigated whether exposure to CNCs influenced Native-English speakers’ object categorization preferences, inhibitory control and memory retrieval. The participants of this study were 99 Native-English speaking College students. They were randomly assigned to an experimental group, which received training on four commonly used CNCs during the initial phase of the experiment, or a control group, which did not receive similar treatment during the initial phase. After the initial phase, the experimental group and the control group were assessed on a Forced Choice Task, a Go/No-Go Task and a Memory Task. A Mixed-design ANOVA indicated that the experimental group displayed a preference for objects sharing the same classifier in the Forced Choice Task and the Go/ No-Go Task (i.e. Go trials) when compared to the controls. The effect of exposure to numeral classifiers on inhibitory control was supported with a significantly lower false alarm rate (in the No-Go trials) for the experimental group. However, no group differences were observed in the results of the analysis of the participants’ median reaction times in the Go/No-Go tasks. Similarly, the differences between the two groups’ scores on the Memory Task was not found to be significant. The results of the study indicated that exposure to CNCs influenced Native-English speakers’ categorization. The results also revealed partial support for the influence of exposure to CNCs on inhibitory processing, but not in the case of object clustering.

abstract: Semantic web is the web of data that provides a common framework and technologies for sharing and reusing data in various applications. In semantic web terminology, linked data is the term used to describe a method of exposing and connecting data on the web from different sources. The purpose of linked data and semantic web is to publish data in an open and standard format and to link this data with existing data on the Linked Open Data Cloud. The goal of this thesis to come up with a semantic framework for integrating and publishing linked data on the web. Traditionally integrating data from multiple sources usually involves an Extract-Transform-Load (ETL) framework to generate datasets for analytics and visualization. The thesis proposes introducing a semantic component in the ETL framework to semi-automate the generation and publishing of linked data. In this thesis, various existing ETL tools and data integration techniques have been analyzed and deficiencies have been identified. This thesis proposes a set of requirements for the semantic ETL framework by conducting a manual process to integrate data from various sources such as weather, holidays, airports, flight arrival, departure and delays. The research questions that are addressed are: (i) to what extent can the integration, generation, and publishing of linked data to the cloud using a semantic ETL framework be automated; (ii) does use of semantic technologies produce a richer data model and integrated data. Details of the methodology, data collection, and application that uses the linked data generated are presented. Evaluation is done by comparing traditional data integration approach with semantic ETL approach in terms of effort involved in integration, data model generated and querying the data generated. / Dissertation/Thesis / Masters Thesis Computer Science 2016

Made available in DSpace on 2014-06-12T15:54:41Z (GMT). No. of bitstreams: 2 arquivo1991_1.pdf: 2164656 bytes, checksum: 1155c56e11920c8db2f44538c0dec97f (MD5) license.txt: 1748 bytes, checksum: 8a4605be74aa9ea9d79846c1fba20a33 (MD5) Previous issue date: 2008 / Em ambientes corporativos e heterogêneos, o compartilhamento de recursos para a resolução de problemas é fortemente associado à segurança da informação. Um aspecto crítico a ser considerado para as organizações é a exigência de uma eficaz e eficiente aquisição e distribuição de conhecimento a respeito de riscos, vulnerabilidades e ameaças que podem ser, portanto, exploradas e causar incidentes de segurança e impactar negativamente nos negócios. Os diversos ambientes de atuação humana necessitam de meios transparentes para planejar e gerenciar problemas relacionados à segurança da informação. Há um aumento significativo na complexidade de se projetar e planejar segurança necessitando que meios de manipulação da informação sejam adotados. Para isso, esta dissertação propõe uma ontologia para este domínio de segurança computacional, denominada CoreSec. O estudo visa demonstrar que uma vez que o conhecimento é formalizado, é possível reusá-lo, realizar inferência, processá-lo computacionalmente, como também torna-se passível de comunicação entre seres humanos e agentes inteligentes. Nossa proposta considera que a segurança da informação será mais eficiente se esta for baseada em um modelo formal de informações do domínio, tal como uma ontologia, podendo ser aplicada para auxiliar as atividades dos responsáveis de segurança, na análise e avaliação de riscos, elicitação de requisitos de segurança, análise de vulnerabilidades e desenvolvimento de ontologias mais específicas para o domínio de segurança da informação

Talmy (1975, 1985, 1991 and 2000b) studies Motion events encoded by verbs from the perspective of lexicalisation(T). Talmy (2000b) proposes six basic semantic elements to describe Motion events; they are Figure, Motion, Path, Ground, Manner, and Cause. For example, in the sentence He entered the room, enter is the main verb and encodes Motion “move” and Path “into”. So the main verb encodes the Path information. Such phenomena are very common in Spanish; however, in English and in Chinese Path is usually expressed by satellites, a category of surface element. Enter is exceptional in English. Although it is a word in English it was borrowed from French. The surface elements which encode the Path information determine a language’s type. For example, if Path is encoded by main verbs in language A, then this language A is a verb-framed language; if Path is typically expressed by satellites in language B, then language B is a satellite-framed language. These are the two most widespread types of languages in this typology. According to Talmy, English is a satellite-framed language (S-framed language); Spanish a verb-framed language (V-framed language); and Chinese a satellite-framed language. Slobin (1996, 1997, 2002, 2004 and 2006) argues that Chinese is an equipollent-framed language (E-framed language), a third language type he added to Talmy’s typology. The evidence for this is the serial verb construction (SVC) in Chinese. SVCs can be briefly defined as a syntactic pattern where two or more verbs are used together to express a single conceptual event and there are no markers of subordination and coordination. Slobin uses feī chū (fly exit) as an example of the SVC and he insists that feī (fly) and chū (exit) share the same grammatical status and are equal to each other in that neither of them can be omitted for a complete expression of the event of flying out. The first verb encodes the Manner information and the latter one expresses the Path information. Omitting either part, the expression is ungrammatical. Having briefly reviewed these two models of language typology, many questions have arisen. Is it necessary to have a third language type to account for Chinese? Or is Chinese an Eframed language or a S-framed language? What is the language typology of Chinese? This is the main research question I aim to answer in this thesis. The main question concerns the nature of Chinese SVCs. In my thesis, I discuss the features of Chinese SVCs as preparation for a working definition of SVC for my empirical work to collect the SVC data from the Lancaster Corpus of Mandarin Chinese (LCMC). I show that the components in Chinese SVCs are not equal in semantics. There are constraints on the positions for different semantic parameters. In addition, the surface forms of components for SVCs do not share equal status for the asymmetrical SVCs. This further shows that components within Chinese SVCs are not in equal grammatical status. My data shows that Path can be encoded by main verbs as well as by satellites in Chinese. Having illustrated that Chinese SVC is not evidence for Chinese to be an E-framed language, then, is Chinese a S-framed language similar to English or a V-framed language like Spanish? Özçalışkan (2004) claims that Path verbs, verbs encoding [Motion + Path], is a closed class. How many Path verbs are there in Chinese and are these Path verbs comparable with those in English and in Spanish? I give a comprehensive list of Chinese Path verbs and then focus on some of them to track the process of the lexicalisation(T). I found that there are no significant differences in number for the 13 types of Path verbs in Chinese, English and Spanish and that the lexicalised(T) Path is comparable. These findings indicate that Chinese uses both main verbs and satellites to express the Path information in motion events. Additionally, the grammaticalization trend of Chinese Path verbs and the shift from independent Path verbs into Path satellites and grammatical relation markers also show that Chinese is not part of any of the parallel system, the split system, or the intermixed system for expressing motion events. Chinese is in the transferring period from a S-framed language to a V-framed language.

Semantic richness is a multidimensional and dynamic construct that can be defined as the amount of semantic information a word possesses. In this thesis, the semantic richness dimensions of number of associates, number of semantic neighbours, and body-object interaction were investigated. Forty-eight young adults were randomly assigned to perform either lexical decision (LDT) or semantic categorization tasks (SCT). The goal of this thesis was to investigate behavioural and electrophysiological differences (using the Event-Related Potential technique) between semantically rich words and semantically impoverished words. Results revealed that the amplitude of the N400 ERP component was smaller for words with high number of associates and high number of semantic neighbours compared to words with low number of associates or low number of semantic neighbours, respectively, but only during LDT. Behavioural results, however, only showed an accuracy and reaction time advantage (during item analyses) for words with many associates. In contrast, N400 amplitudes did not differ for words with high body-object interaction rating when compared to words with low body-object interaction rating in any of the tasks, although a behavioural reaction time advantage was observed in item analyses of the LDT. These results suggest that words with many associates or semantic neighbours may be processed more efficiently and be easier to integrate within the neural semantic network than words with few associates or semantic neighbours. In addition, the N400 effect was seen in the LDT but not in the SCT, suggesting that semantic richness information may be used in a top-down manner in order to fulfill the task requirements using available neural resources in a more efficient manner.

Keyphrases describe a document in a coherent and simple way, giving the prospective reader a way to quickly determine whether the document satisfies their information needs. The pervasion of huge amount of information on Web, with only a small amount of documents have keyphrases extracted, there is a definite need to discover automatic keyphrase extraction systems. Typically, a document written by human develops around one or more general concepts or sub-concepts. These concepts or sub-concepts should be structured and semantically related with each other, so that they can form the meaningful representation of a document. Considering the fact, the phrases or concepts in a document are related to each other, a new approach for keyphrase extraction is introduced that exploits the semantic relations in the document. For measuring the semantic relations between concepts or sub-concepts in the document, I present a comprehensive study aimed at using collaboratively constructed semantic resources like Wikipedia and its link structure. In particular, I introduce a graph-based keyphrase extraction system that exploits the semantic relations in the document and features such as term frequency. I evaluated the proposed system using novel measures and the results obtained compare favorably with previously published results on established benchmarks.