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A topic-driven graph-of-words convolutional network for improving text classification
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In recent times, we have witnessed dramatic progresses and emergence of advanced deep neural architectures in natural language processing (NLP) domain. The advanced sequence-to-sequence (seq2seq)/transformer based architectures have demonstrated remarkable improvements in multiple NLP’s tasks, including text categorization. But these advanced deep sequential text embedding techniques have still suffered limitations regarding with the capability of preserving the long-range dependencies between w
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Bài báo tạp chí
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