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The problem of noisy and unbalanced train- ing data for supervised keyphrase extraction results from the subjectivity of keyphrase as- signment, which we quantify by crowdsourc- ing keyphrases for news …...

AbstractIn this work, we explore the way to perform named entity recognition (NER) using only unlabeled data and named entity dictionaries. To this end, we formulate the task as a …...

AbstractDistantly supervision automatically generates plenty of training samples for relation extraction. However, it also incurs two major problems: noisy labels and imbalanced training data. Previous works focus more on reducing …...

AbstractDocument-level relation extraction (RE) aims to identify relations between entities across multiple sentences. Most previous methods focused on document-level RE under full supervision. However, in real-world scenario, it is expensive …...

AbstractIn this work, we explore the relationship between depression and manifestations of happiness in social media. While the majority of works surrounding depression focus on symptoms, psychological research shows that …...