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Inclusion in CSR Reports: The Lens from a Data-Driven Machine Learning Model
Inclusion, as one of the foundations in the diversity, equity, and inclusion initiative, concerns the degree of being treated as an ingroup member in a workplace.
Pipelined Biomedical Event Extraction Rivaling Joint Learning
Biomedical event extraction is an information extraction task to obtain events from biomedical text, whose targets include the type, the trigger, and the respective arguments involved in an event.
Joint Learning-based Causal Relation Extraction from Biomedical Literature
Causal relation extraction of biomedical entities is one of the most complex tasks in biomedical text mining, which involves two kinds of information: entity relations and entity functions.
Multi-label classification for biomedical literature: an overview of the BioCreative VII LitCovid Track for COVID-19 literature topic annotations
To close the gap, we organized the BioCreative LitCovid track to call for a community effort to tackle automated topic annotation for COVID-19 literature.
PolyU CBS-Comp at SemEval-2021 Task 1: Lexical Complexity Prediction (LCP)
In this contribution, we describe the system presented by the PolyU CBS-Comp Team at the Task 1 of SemEval 2021, where the goal was the estimation of the complexity of words in a given sentence context.
Affection Driven Neural Networks for Sentiment Analysis
Deep neural network models have played a critical role in sentiment analysis with promising results in the recent decade.
