20 resultados para Sentiment Analysis Opinion Mining Text Mining Twitter


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The multi-relational Data Mining approach has emerged as alternative to the analysis of structured data, such as relational databases. Unlike traditional algorithms, the multi-relational proposals allow mining directly multiple tables, avoiding the costly join operations. In this paper, is presented a comparative study involving the traditional Patricia Mine algorithm and its corresponding multi-relational proposed, MR-Radix in order to evaluate the performance of two approaches for mining association rules are used for relational databases. This study presents two original contributions: the proposition of an algorithm multi-relational MR-Radix, which is efficient for use in relational databases, both in terms of execution time and in relation to memory usage and the presentation of the empirical approach multirelational advantage in performance over several tables, which avoids the costly join operations from multiple tables. © 2011 IEEE.

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This investigation reports the results of a study realized in an area related to the development of sand mining activities, which belongs to Sibelco Mineração Ltd. The site is located around Analândia municipality, nearly in the center of São Paulo State, Brazil. Hydrochemical analyses of groundwater were realized under different periods of time, with the aim of evaluating the possibility of release of several constituents to the liquid phase, which may be a source of pollution of the surface hydrological resources and of the deeper Guarani aquifer. This is because the site is located at the recharge area of Guarani aquifer and some tributaries from Corumbataí river may also be suffering contamination, implying on the impoverishment of the water quality that are very important resources in the region, as they are extensively used for drinking purposes, among others.© 2011 WIT Press.

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The increase in the number of spatial data collected has motivated the development of geovisualisation techniques, aiming to provide an important resource to support the extraction of knowledge and decision making. One of these techniques are 3D graphs, which provides a dynamic and flexible increase of the results analysis obtained by the spatial data mining algorithms, principally when there are incidences of georeferenced objects in a same local. This work presented as an original contribution the potentialisation of visual resources in a computational environment of spatial data mining and, afterwards, the efficiency of these techniques is demonstrated with the use of a real database. The application has shown to be very interesting in interpreting obtained results, such as patterns that occurred in a same locality and to provide support for activities which could be done as from the visualisation of results. © 2013 Springer-Verlag.

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This study aimed to evaluate the sediment quality in the estuarine protected area known as Canan,ia-Iguape-Peruibe (CIP-PA), located on the southeastern coast of Brazil. The study was designed considering possible negative effects induced by the city of Canan,ia on the sediment quality of surrounding areas. This evaluation was performed using chemical and ecotoxicological analyses. Sediments were predominantly sandy, with low CaCO3 contents. Amounts of organic matter varied, but higher contents occurred closer to the city, as well as did Fe and Total Recoverable Oils and Greases (TROGs) concentrations. Contamination by Cd and Cu was revealed in some samples, while concentrations of Zn were considered low. Chronic toxicity was detected in all tested sediments and acute toxicity occurred only in sediments collected near the city. The principal component analysis (PCA) revealed an association among Cd, Cu, Fe, TROG, fines, organic matter, CaCO3, and chronic toxicity, whereas acute toxicity was found to be associated with Zn and mud. However, because Zn levels were low, acute toxicity was likely due to a contaminant that was not measured. Results show that there is a broad area within the CIP-PA that is under the influence of mining activities (chronic toxicity, moderate contamination by metals), whereas poorer conditions occur closer to Canan,ia (acute toxicity); thus, the urban area seems to constitute a relevant source of contaminants for the estuarine complex. These results show that contamination is already capable of producing risks for the local aquatic biota, which suggests that the CIP-PA effectiveness in protecting estuarine biota may be threatened.

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The increase in new electronic devices had generated a considerable increase in obtaining spatial data information; hence these data are becoming more and more widely used. As well as for conventional data, spatial data need to be analyzed so interesting information can be retrieved from them. Therefore, data clustering techniques can be used to extract clusters of a set of spatial data. However, current approaches do not consider the implicit semantics that exist between a region and an object’s attributes. This paper presents an approach that enhances spatial data mining process, so they can use the semantic that exists within a region. A framework was developed, OntoSDM, which enables spatial data mining algorithms to communicate with ontologies in order to enhance the algorithm’s result. The experiments demonstrated a semantically improved result, generating more interesting clusters, therefore reducing manual analysis work of an expert.