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Publicação
Sentiment classification using tree‐based gated recurrent units
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Orientador(es)
Resumo(s)
Natural Language Processing is one of the most challenging fields of Artificial Intelligence. The past 10 years, this field has witnessed a fascinating progress due to Deep Learning. Despite that, we haven’t achieved to build an architecture of models that can understand natural language as humans do. Many architectures have been proposed, each of them having its own strengths and weaknesses. In this report, we will cover the tree based architectures and in particular we will propose a different tree based architecture that is very similar to the Tree-Based LSTM, proposed by Tai(2015).
In this work, we aim to make a critical comparison between the proposed architecture -Tree-Based GRU- with Tree-based LSTM for sentiment classification tasks, both binary and fine-grained.
Descrição
Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Knowledge Management and Business Intelligence
Palavras-chave
Deep Learning Natural Language Processing Recursive Neural Networks Sentiment Classification