音乐领域典型事件抽取方法研究

摘要

Event extraction is an important research issue in information extraction. This paper focuses on the music domain, and describes a method based on trigger clustering for event type discovering. Then we propose a method based on the filtering of keywords and triggers for event type recognition. For the event argument recognition, the method which is based on maximum entropy model is proposed in this paper. Evaluations on our corpus give a final F-score of 82.82％ and 75.79％ for type recognition and argument recognition.%事件抽取是信息抽取领域一个重要的研究方向.该文从音乐领域的事件抽取出发,通过领域事件词聚类的方法自动发现音乐领域具有代表性的事件,然后采用基于关键词与触发词相结合的过滤方法简化了事件类型的识别过程.在事件元素识别中,该文采用了基于最大熵的事件元素识别方法.在该文构建的语料库下,最终事件类型识别的平均F值达到82.82%,事件元素识别的平均F值达到75.79%.