8 resultados para regressão semântica

em Universidade Federal do Rio Grande do Norte(UFRN)


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Telecommunication is one of the most dynamic and strategic areas in the world. Many technological innovations has modified the way information is exchanged. Information and knowledge are now shared in networks. Broadband Internet is the new way of sharing contents and information. This dissertation deals with performance indicators related to maintenance services of telecommunications networks and uses models of multivariate regression to estimate churn, which is the loss of customers to other companies. In a competitive environment, telecommunications companies have devised strategies to minimize the loss of customers. Loosing customers presents a higher cost than obtaining new ones. Corporations have plenty of data stored in a diversity of databases. Usually the data are not explored properly. This work uses the Knowledge Discovery in Databases (KDD) to establish rules and new models to explain how churn, as a dependent variable, are related to a diversity of service indicators, such as time to deploy the service (in hours), time to repair (in hours), and so on. Extraction of meaningful knowledge is, in many cases, a challenge. Models were tested and statistically analyzed. The work also shows results that allows the analysis and identification of which quality services indicators influence the churn. Actions are also proposed to solve, at least in part, this problem

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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

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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

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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

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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

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The main goal of Regression Test (RT) is to reuse the test suite of the latest version of a software in its current version, in order to maximize the value of the tests already developed and ensure that old features continue working after the new changes. Even with reuse, it is common that not all tests need to be executed again. Because of that, it is encouraged to use Regression Tests Selection (RTS) techniques, which aims to select from all tests, only those that reveal faults, this reduces costs and makes this an interesting practice for the testing teams. Several recent research works evaluate the quality of the selections performed by RTS techniques, identifying which one presents the best results, measured by metrics such as inclusion and precision. The RTS techniques should seek in the System Under Test (SUT) for tests that reveal faults. However, because this is a problem without a viable solution, they alternatively seek for tests that reveal changes, where faults may occur. Nevertheless, these changes may modify the execution flow of the algorithm itself, leading some tests no longer exercise the same stretch. In this context, this dissertation investigates whether changes performed in a SUT would affect the quality of the selection of tests performed by an RTS, if so, which features the changes present which cause errors, leading the RTS to include or exclude tests wrongly. For this purpose, a tool was developed using the Java language to automate the measurement of inclusion and precision averages achieved by a regression test selection technique for a particular feature of change. In order to validate this tool, an empirical study was conducted to evaluate the RTS technique Pythia, based on textual differencing, on a large web information system, analyzing the feature of types of tasks performed to evolve the SUT

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The main hypothesis of this thesis is that the deve lopment of industrial automation applications efficiently, you need a good structuri ng of data to be handled. Then, with the aim of structuring knowledge involved in the contex t of industrial processes, this thesis proposes an ontology called OntoAuto that conceptua lly models the elements involved in the description of industrial processes. To validat e the proposed ontology, several applica- tions are presented. In the first, two typical indu strial processes are modeled conceptually: treatment unit DEA (Diethanolamine) and kiln. In th e second application, the ontology is used to perform a semantic filtering alarms, which together with the analysis of correla- tions, provides temporal relationships between alar ms from an industrial process. In the third application, the ontology was used for modeli ng and analysis of construction cost and operation processes. In the fourth application, the ontology is adopted to analyze the reliability and availability of an industrial plant . Both for the application as it involves costs for the area of reliability, it was necessary to create new ontologies, and OntoE- con OntoConf, respectivamentem, importing the knowl edge represented in OntoAuto but adding specific information. The main conclusions of the thesis has been that on tology approaches are well suited for structuring the knowledge of industrial process es and based on them, you can develop various advanced applications in industrial automat ion.

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Cloud computing can be defined as a distributed computational model by through resources (hardware, storage, development platforms and communication) are shared, as paid services accessible with minimal management effort and interaction. A great benefit of this model is to enable the use of various providers (e.g a multi-cloud architecture) to compose a set of services in order to obtain an optimal configuration for performance and cost. However, the multi-cloud use is precluded by the problem of cloud lock-in. The cloud lock-in is the dependency between an application and a cloud platform. It is commonly addressed by three strategies: (i) use of intermediate layer that stands to consumers of cloud services and the provider, (ii) use of standardized interfaces to access the cloud, or (iii) use of models with open specifications. This paper outlines an approach to evaluate these strategies. This approach was performed and it was found that despite the advances made by these strategies, none of them actually solves the problem of lock-in cloud. In this sense, this work proposes the use of Semantic Web to avoid cloud lock-in, where RDF models are used to specify the features of a cloud, which are managed by SPARQL queries. In this direction, this work: (i) presents an evaluation model that quantifies the problem of cloud lock-in, (ii) evaluates the cloud lock-in from three multi-cloud solutions and three cloud platforms, (iii) proposes using RDF and SPARQL on management of cloud resources, (iv) presents the cloud Query Manager (CQM), an SPARQL server that implements the proposal, and (v) comparing three multi-cloud solutions in relation to CQM on the response time and the effectiveness in the resolution of cloud lock-in.