Neural Attentive Bag-of-Entities Model for Text Classification

CoNLL 2019 2019 Ikuya YamadaHiroyuki Shindo

This study proposes a Neural Attentive Bag-of-Entities model, which is a neural network model that performs text classification using entities in a knowledge base. Entities provide unambiguous and relevant semantic signals that are beneficial for capturing semantics in texts... (read more)

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Evaluation Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK COMPARE
Text Classification 20NEWS NABoE-full Accuracy 88.1 # 2
Text Classification R8 NABoE-full Accuracy 97.9 # 1