Tao Liao1,‡, Weicheng Fu1,†, Shunxiang Zhang1,*, Zongtian Liu2,§
Computer Systems Science and Engineering, Vol.35, No.5, pp. 311-319, 2020, DOI:10.32604/csse.2020.35.311
Abstract Event trigger recognition is a sub-task of event extraction, which is important for text classification, topic tracking and so on. In order to improve the
effectiveness of using word features as a benchmark, a new event trigger recognition method based on positive and negative weight computing is proposed.
Firstly, the associated word feature, the part-of-speech feature and the dependency feature are combined. Then, the combination of these three features with
positive and negative weight computing is used to identify triggers. Finally, the text classification is carried out based on the event triggers. Findings from
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