Daojian Zeng1, Jian Tian2, Ruoyao Peng1, Jianhua Dai1,*, Hui Gao3, Peng Peng4
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 4161-4173, 2021, DOI:10.32604/cmc.2021.017028
Abstract Event extraction is one of the most challenging tasks in information extraction. It is a common phenomenon where multiple events exist in the same sentence. However, extracting multiple events is more difficult than extracting a single event. Existing event extraction methods based on sequence models ignore the interrelated information between events because the sequence is too long. In addition, the current argument extraction relies on the results of syntactic dependency analysis, which is complicated and prone to error transmission. In order to solve the above problems, a joint event extraction method based on global event-type guidance and attention enhancement was… More >
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