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Studies with ensemble systems have gained attention recently and, most of them, propose new methods for the design (generation) of different components in these systems. In parallel, new contributions of meta-learning have been presented as an efficient alternative to automatic recommendation of algorithms. In this paper, we apply meta-learning in the process of recommendation of important parameters...
Knowledge about algorithm similarity is an important aspect of meta-learning, where the information gathered from previous learning tasks can be used to guide the selection of algorithms for new datasets. Usually this task is done by comparing global performance measures across different datasets or alternatively, comparing the performance of algorithms at the instance-level. In both cases, the previous...
This paper evaluates some strategies to approximate the performance of dynamic ensembles based on NN-rule to the oracle performance. For this purpose, we use a multi-objective optimization algorithm, based on Differential Evolution, to generate automatically a pool of accurate and diverse classifiers in the form of Extreme Learning Machines. However, the rule defined for selecting the classifiers...
In multi-label datasets, the number of labels associated with each instance is an important feature to be observed. Two relevant characteristics related to datasets' number of labels are cardinality and density. In this work, we use artificial datasets generated through a framework named Mldatagem, freely-available in the internet. This framework enables configuring some other characteristics of the...
Part-of-Speech Tagging is a fundamental task on many Natural Language Processing systems. This task consists in identifying the syntactic category, i.e. the part of speech, of each word in a sentence. Despite the fact that the current state-of-the-art accuracy for this task is around 97%, any improvement has an immediate impact on more complex tasks, like Parsing, Semantic Role Labeling and Information...
The rapid change of trading values from tangible assets to Intelectual Property has put both businesses and academia in a race to acquire and protect the rights to exploit such property. This is mainly accomplished in the form of patent issuing by the governments, being time consuming and complicated due to the vast amount of documents that need to be analyzed in order to assert the novelty or validity...
We propose polarity detection from colloquial expressions distinctive of a bilingual population. The hybrid language we address it's called "Jopara", composed by Spanish and Guaraní, spoken in Paraguay, similar to the "Louisiana's Creole" in the United States. We categorize polarity in three classes (positive, negative and neutral) and address this problem by applying both lexicon-based...
Local Coherence is a very important aspect in multi-document summarization, since good summaries not only condense the most relevant information, but also present it in a well-organized structure. One of the most investigated models for local coherence is the Entity-based model, which has been successfully used, once it facilitates the computational approach for coherence measurement. Particularly,...
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