Seleção seqüencial de descritores por análise da semântica para recuperação de imagens baseada no conteúdo

With the rapid growth of databases of various types (text, multimedia, etc..), There exist a need to propose methods for ordering, access and retrieve data in a simple and fast way. The images databases, in addition to these needs, require a representation of the images so that the semantic content characteristics are considered. Accordingly, several proposals such as the textual annotations based retrieval has been made. In the annotations approach, the recovery is based on the comparison between the textual description that a user can make of images and descriptions of the images stored in database. Among its drawbacks, it is noted that the textual description is very dependent on the observer, in addition to the computational effort required to describe all the images in database. Another approach is the content based image retrieval - CBIR, where each image is represented by low-level features such as: color, shape, texture, etc. In this sense, the results in the area of CBIR has been very promising. However, the representation of the images semantic by low-level features is an open problem. New algorithms for the extraction of features as well as new methods of indexing have been proposed in the literature. However, these algorithms become increasingly complex. So, doing an analysis, it is natural to ask whether there is a relationship between semantics and low-level features extracted in an image? and if there is a relationship, which descriptors better represent the semantic? which leads us to a new question: how to use descriptors to represent the content of the images?. The work presented in this thesis, proposes a method to analyze the relationship between low-level descriptors and semantics in an attempt to answer the questions before. Still, it was observed that there are three possibilities of indexing images: Using composed characteristic vectors, using parallel and independent index structures (for each descriptor or set of them) and using characteristic vectors sorted in sequential order. Thus, the first two forms have been widely studied and applied in literature, but there were no records of the third way has even been explored. So this thesis also proposes to index using a sequential structure of descriptors and also the order of these descriptors should be based on the relationship that exists between each descriptor and semantics of the users. Finally, the proposed index in this thesis revealed better than the traditional approachs and yet, was showed experimentally that the order in this sequence is important and there is a direct relationship between this order and the relationship of low-level descriptors with the semantics of the users

A interpretação semântica dos auxiliares modais poder, precisar e dever: uma abordagem da semântica cognitiva

Apresentamos, neste trabalho, com base na semântica cognitiva, uma análise do significado, em contexto, dos auxiliares modais poder, precisar e dever. Analisamos 120 textos produzidos por candidatos ao vestibular e por alunos do ensino fundamental, como resposta da questão número três da prova discursiva de Língua Portuguesa do vestibular 2005 da UFRN, que pede aos candidatos para explicitar a diferença de sentido entre três frases, observando o uso desses três verbos. Consideramos que um item lexical não é incorporado a uma representação lingüística semântica fixa, limitada e única, mas antes, é ligado a uma representação lingüística semântica flexível e aberta que provê acesso a muitas concepções e sistemas conceituais dependente de cada contexto determinado. Com base em seu significado, um item lexical evoca um grupo de domínios cognitivos, que por sua vez, apresentam um determinado conteúdo conceitual. Isto implica em afirmar que a rede de significados lexicais vai variar conforme o conhecimento de mundo de cada um (LANGACKER, 2000). A relevância deste trabalho é proporcionar uma contribuição para a descrição semântica do português

Efeito da coesão semântica sobre a discriminação de itens emocionais em testes de memória de reconhecimento de palavras

Highly emotional itens are best remembered in emotional memory tasks than neutral items. An example of emotional item that benefits declarative memory processes are the taboo words. These words undergo from a conventional prohibition, imposed by tradition or custom. Literature suggests that the strongest recollection these words is due to emotional arousal, as well as, the fact that they form a cohesive semantic group, which is a positive additive effect. However, studies with semantic lists show that cohesion can have a negative effect of interference, impairing memory. We analyzed, in two experiments, the effect of arousal and semantic cohesion of taboo words on recognition tests, comparing with into two other word categories: semantically related and without emotional arousal (semantic category) and neutral, with low semantic relation (objects). Our results indicate that cohesion has interfered whith the performance of the test by increasing the number of false alarms. This effect was strongly observed in the semantic category of words in both experiments, but also in the neutral and taboo words, when both were explicitly considered as semantic categories through the instruction of the test in Experiment 2. Despite the impairment induced by semantic cohesion in both experiments, the taboo words were more discriminated than others, and this result agrees with the indication of the emotional arousal as the main factor for the best recollection of emotional items in memory tests

Uma ontologia para a descrição da semântica da IMML

This work presents an ontology to describe the semantics of IMML (Interactive Message Modeling Language) an XML-based User Interface Description Language. The ontology presents the description of all IMML elements including a natural language description and semantic rules and relationships. The ontology is implemented in OWL-DL, a standard language to ontology description that is recommended by W3C. Our main goal is to describe the semantic using languages and tools that can be processed by computers. As a consequence, we develop tools to the validation of a user interface specification and also to present the semantic description in different views