Combining Dual Word Embeddings with Open Directory Project Based Text Classification

Aliyeva, Dinara; Kim, Kang-Min; Choi, Byungju; Lee, Sang Keun

doi:10.1109/icci-cc.2018.8482044

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“…Para classificar adequadamente um texto não estruturado é necessária uma compreensão sintática e semânita do texto, além do conhecimento de uma quantidade suficientemente grande de categorias de classificação (Aliyeva, Kim, Choi, & Lee, 2018). Os métodos tradicionais de classificação de texto também necessitam que todo documento seja convertido em um vetor numérico.…”

Section: Introductionunclassified

Utilização Prática De Word Embedding Aplicada À Classificação De Texto

Souza¹,

Gonçalves²,

Souza³

2020

Anais Do X Congresso Internacional De Conhecimento E Inovação (ciKi)

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Text classification aims to extract knowledge from unstructured text patterns. The concept of word incorporation is a representation technique that allows words with similar meanings to have a similar representation, in order to incorporate reasoning characteristics about their use and meaning. The aim of this article is to analyze the work already published on the use of embedded words applied to the classification of texts, to propose a practical application that demonstrates its effectiveness. This study contributes to proving the effectiveness of the use of word incorporation applied to text classification, having reached an accuracy rate of around 73%.

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