Materiais

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Doc2Vec tools

Ferramenta para treinamento de modelos Doc2Vec.

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gBoED

Representações de documentos baseadas em expressões do domínio

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Pred.Arg - Representações com Papéis Semânticos

Ferramenta para gerar representações de documentos com base em papéis semânticos.

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RotuLabic

RotuLabic is a system developed to support manual labeling of documents. The system uses a transductive learning algorithm to recommend labels to the user and, thus, supports the manual labeling work. Currently, the system interface is available only in Portuguese.

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ICT - Inductive Classification Tool

Inductive Classification Tool was developed in Java language and aims to generate results using traditional inductive algorithms and their different parameter for datasets represented in ARFF format.

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TPT - Text Preprocessing Tool

This is a Java tool which transforms text files in a document-term matrix.

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SKET - Statistical Keyword Extraction Tool

This tool extracts keywords from single documents using statistical methods.

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FEATuRE - Features gEnerator based on AssociaTion RulEs

The required steps to generate the bag-of-related words are implemented in this tool. Thre is also functionalities to analyse the generated bag-of-related-words.

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Mldatagen - A multi-label dataset generator

This framework, which is described in ICMC-USP technical report, can to generate synthetic multi-label datasets using two strategies: hyperspheres or hypercubes. For each label in a dataset, these strategies randomly generate a geometric shape (hypersphere or hypercube), which is populated with points (instances or examples) randomly generated. Afterwards, each instance is labeled according to the shapes it belongs to, which defines the instance multi-label.

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