Submitted by Filipe dos Santos (fsantos@pucsp.br) on 2016-09-02T14:31:38Z No. of bitstreams: 1 Newton Juniano Calegari.pdf: 2853517 bytes, checksum: e1eda2a1325986c6284a5054d724a19f (MD5) / Made available in DSpace on 2016-09-02T14:31:38Z (GMT). No. of bitstreams: 1 Newton Juniano Calegari.pdf: 2853517 bytes, checksum: e1eda2a1325986c6284a5054d724a19f (MD5) Previous issue date: 2016-04-02 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Pontifícia Universidade Católica de São Paulo / The tool proposed in this research aims at bringing together the Semantic Web technologies and content publishers, this way enabling the latter to contribute to creating structured data and metadata about texts and information they may make available on the Web. The general goal is to investigate the technical feasibility of developing a semantic annotation tool that enables content publishers to contribute to the Semantic Web ecosystem. Based on (BERNERS-LEE et al., 2001; ALESSO; SMITH, 2006; RODRÍGUEZ-ROCHA et al., 2015; GUIZZARDI, 2005; ISOTANI; BITTENCOURT, 2015), the Semantic Web is presented according to its technological stack. Considering the importance of the ontologies and vocabularies used to create Semantic Web applications, the essential subjects of the conceptual modelling and the ontology language used on the Web are presented. In order to provide the necessary concepts to use semantic annotations, this dissertation presents both the way annotations are used (manual, semi-automatic, and automatic) as well as the way these annotations are integrated with resources available on the Web. The state-of-the-art chapter describes recent projects and related work on the use of Semantic Web within Web-content publishing context. The methodology adopted by this research is based on (SANTAELLA; VIEIRA, 2008; GIL, 2002), in compliance with the exploratory approach for research. This research presents the proposal and the architecture of the semantic annotation tool, which uses shared vocabulary in order to create structured data based on textual content. In conclusion, this dissertation addresses the possibilities of future work, both in terms of the implementation of the tool in a real use case as well as in new scientific research / A proposta apresentada nesta pesquisa busca aproximar as tecnologias de Web Semântica dos usuários publicadores de conteúdo na Web, permitindo que estes contribuam com a geração de dados estruturados e metadados sobre textos e informações que venham disponibilizar na Web. O objetivo geral deste trabalho é investigar a viabilidade técnica de desenvolvimento de uma ferramenta de anotação semântica que permita aos usuários publicadores de conteúdo contribuírem para o ecossistema de Web Semântica. Com suporte de (BERNERS-LEE et al., 2001; ALESSO; SMITH, 2006; RODRÍGUEZ-ROCHA et al., 2015; GUIZZARDI, 2005; ISOTANI; BITTENCOURT, 2015) apresenta-se o tópico de Web Semântica de acordo com a pilha tecnológica que mostra o conjunto de tecnologias proposto para a sua realização. Considerando a importância de ontologias e vocabulários para a construção de aplicações de Web Semântica, são apresentados então os tópicos fundamentais de modelagem conceitual e a linguagem de ontologias para Web. Para fornecer a base necessária para a utilização de anotações semânticas são apresentados, além da definição, os modos de uso de anotações (manual, semi-automático e automático) e as formas de integrar essas anotações com recursos disponíveis nas tecnologias da Web Semântica. O estado da arte contempla trabalhos e projetos recentes sobre o uso de Web Semântica no contexto de publicação de conteúdo na Web. A metodologia é baseada na proposta apresentada por SANTAELLA; VIEIRA (2008), seguindo uma abordagem exploratória para a condução da pesquisa. É apresentada a proposta e os componentes de uma ferramenta de anotação semântica que utiliza vocabulários compartilhados para geração de dados estruturados a partir de conteúdo textual. Concluindo o trabalho, são apresentadas as possibilidades futuras, tanto da implementação da ferramenta em um cenário real, atestando sua viabilidade técnica, quanto novos trabalhos encaminhados a partir desta pesquisa

Com os avanços dos processos da microeletrônica temos dispositivos menores e com maior poder de computação e comunicação. Um Ambiente Pervasivo contém diferentes dispositivos, tais como sensores, atuadores, eletroeletrônicos e dispositivos móveis que interagem com a pessoa de forma natural ao conhecer o contexto. A diversidade de dispositivos e informações do Ambiente Pervasivo introduz um problema de interoperabilidade. Um Ambiente Pervasivo é dinâmico devido à mobilidade do usuário, a variedade de dispositivos. Neste trabalho, é proposto um modelo semântico de contexto para permitir interoperabilidade e fornecer suporte ao dinamismo do Ambiente Pervasivo. O modelo proposto contém características da modelagem de contexto realizadas por trabalhos anteriores, assim como sua integração com a modelagem de preferências das pessoas, políticas de privacidade e serviços. Verificou-se que o modelo de contexto proposto é adequado mediante sua aplicação em um Estudo de Caso e mediante testes realizados. Mostra-se que a modelo de contexto utilizado ontologias e Serviços Web Semânticos permite tratar com informação incompleta e inconsistente, bem como fornece suporte na interoperabilidade e ao dinamismo do Ambiente Pervasivo. / Advances in microelectronic processes have allowed smaller devices with more computation and communication power. Pervasive environment contains different devices like electronic sensor, actuators and mobile devices which interact with the person naturally after the context is known. The device and information diversity introduce an interoperability problem. Pervasive environments are dynamics because of user\'s mobility and a variety of devices. In this work, we propose a context model to allow interoperability and to give support to pervasive environment dynamism. The proposed model contains features of context modeling developed in previous works, as well as, their integration with the modeling of the people\'s preferences, privacy policies and services. It was verified that the context model is appropriate by their application in a Case Study and by accomplished tests. It is shown that the model of context using ontologies and Semantic Web Services allow us to work with inconsistent and incomplete information, as well as gives support to interoperability and dynamism of the Pervasive Environment.

Our purpose was to explore developmental changes in the organization and access to the mental lexicon between the ages of three-, five-, and seven years. Six-hundred and seventy three Mandarin-speaking participants listed all exemplars of animals and foods that came to mind within two one-minute intervals. Compared to younger participants, the older children demonstrated more correct responses and fewer errors, suggesting that they have greater knowledge of category-relevant vocabulary. They produced more subcategories, many of which involved embedding and overlapping, which suggests they have more sophisticated lexical-semantic organization. Also, they produced fewer and less closely spaced repetitions, suggesting they could more effectively monitor retrieval responses. We conclude that between the ages of three to seven, children expand and refine the organization of their mental lexicons. Improved monitoring may reflect growth in executive functioning.

Semantic role labelling (SRL) is a natural language processing (NLP) technique that maps sentences to semantic representations. This can be used in different NLP tasks. The goal of this master thesis is to investigate how to support the novel method proposed by He Tan for building corpus annotated with semantic roles. The mentioned goal provides the context for developing a general framework of the work and as a result implementing a supporting system based on the framework. Implementation is followed using Java. Defined features of the system reflect the usage of frame semantics in understanding and explaining the meaning of lexical items. This prototype system has been processed by the biomedical corpus as a dataset for the evaluation. Our supporting environment has the ability to create frames with all related associations through XML, updating frames and related information including definition, elements and example sentences and at last annotating the example sentences of the frame. The output of annotation is a semi structure schema where tokens of a sentence are labelled. We evaluated our system by means of two surveys. The evaluation results showed that our framework and system have fulfilled the expectations of users and has satisfied them in a good scale. Also feedbacks from users have defined new areas of improvement regarding this supporting environment.

Some studies of stroke patients with semantic deficits have found no effect of word frequency on semantic tasks, as well as inconsistent performance across items and tasks. A deficit in semantic control has been suggested as the source of the deficit - i.e., an inability to focus on semantic features appropriate to the task. In the present study, two stroke patients performed significantly better in single-distractor versions (low semantic control) than multiple-distractor versions of semantic tasks (high semantic control) of comprehension tasks, which appears consistent with the semantic control hypothesis. On the other hand, two aphasic patients showed substantially better performance for auditory than visual presentation of words in comprehension tasks – a finding that is not expected on the basis of semantic control. Experiment 1 evaluated whether performance on a multiple-distractor comprehension task could be predicted solely on the basis of performance on a single-distractor version using Luce’s choice axiom. Single distractor performance significantly predicted performance and no convincing evidence was obtained for a role for semantic control. Experiment 2, which examined the modality effect, showed that for one of the patients, worse performance with auditory presentation was most likely due to rapid decay of phonological representations. For the other, worse performance was most likely due to a disruption to phonological representations of words or to their connection to semantic representations. In all, the results suggest that word comprehension deficits in aphasia can result from a variety of sources and not all are due to semantic control deficits.

The semantic content (i.e., meaning of words) is the essence of retrieved autobiographical memories. In comparison to previous research, which has mainly focused on phenomenological experiences and age distribution of memory events, the present study provides a novel view on the retrieval of event information by addressing the semantic representation of memories. In the present study the semantic representation (i.e., word locations represented by vectors in a high dimensional space) of retrieved memory information were investigated, by analyzing the data with an automatic statistical algorithm. The experiment comprised a cued recall task, where participants were presented with unimodal (i.e., one sense modality) or multimodal (i.e., three sense modalities in conjunction) retrieval cues and asked to recall autobiographical memories. The memories were verbally narrated, recorded and transcribed to text. The semantic content of the memory narrations was analyzed with a semantic representation generated by latent semantic analysis (LSA). The results indicated that the semantic representation of visually evoked memories were most similar to the multimodally evoked memories, followed by auditorily and olfactorily evoked memories. By categorizing the semantic content into clusters, the present study also identified unique characteristics in the memory content across modalities.

The Semantic Web enables people and computers to interact and exchange information. Based on Semantic Web technologies, different machine learning applications have been designed. Particularly to emphasize is the possibility to create complex metadata descriptions for any problem domain, based on pre-defined ontologies. In this paper we evaluate the use of a semantic similarity measure based on pre-defined ontologies as an input for a classification analysis. A link prediction between actors of a social network is performed, which could serve as a recommendation system. We measure the prediction performance based on an ontology-based metadata modeling as well as a feature vector modeling. The findings demonstrate that the prediction accuracy based on ontology-based metadata is comparable to traditional approaches and shows that data mining using ontology-based metadata can be considered as a very promising approach.

Document clustering automatically organizes a document collection into distinct groups of similar documents on the basis of their contents. Most of existing document clustering techniques deal with monolingual documents (i.e., documents written in one language). However, with the trend of globalization and advances in Internet technology, an organization or individual often generates/acquires and subsequently archives documents in different languages, thus creating the need for multilingual document clustering (MLDC). Motivated by its significance and need, this study designs a Latent Semantic Indexing (LSI) based MLDC technique. Our empirical evaluation results show that the proposed LSI-based multilingual document clustering technique achieves satisfactory clustering effectiveness, measured by both cluster recall and cluster precision.

Although, the literature reveals that coach interior designs have been emphasized as an important factor determining their competitiveness in the market and the quality of an interior design can be effectively improved by using information about passenger expectations, few practical studies exist to assess the urban railway transport interiors from the passengers&rsquo / perspective. Consequently, designers lack reliable criteria to guide their decisions which would satisfy users. In this study, it is intended to develop a procedure to create interior design alternatives of urban railway transportation vehicles with regard to subjective needs and preferences of users. In order to acquire design criteria and recommendations for such interiors, the design alternatives are then evaluated quantitatively through the medium of semantic assessment tools. The thesis is supported with the arguments collected from literature and with the data from three empirical studies.

A semantic model oriented transformation mechanism is developed for the centralization of intra-enterprise data integration. Such a mechanism is especially crucial in the banking domain which is selected in this study. A new domain ontology is constructed to provide basis for annotations. A bottom-up approach is preferred for semantic annotations to utilize existing web service definitions. Transformations between syntactic web service XML responses and semantic model concepts are defined in transformation files. Transformation files are stored and executed in a separate central transformation repository to enhance abstraction and reusability. An RDF-Store is implemented to store transformed RDF data. Inference power of semantic model is exposed by executing semantic queries in the RDF-Store.