CAJ | 학술논문

近年来，微博投诉成为用户维权的新途径。面对海量微博投诉，企业如何在有限资源下实现微博投诉自动诊断和处理，引发了学术和业界的高度关注。微博投诉句识别是微博投诉自动化处理的前提。本文针对微博投诉句识别问题，设计了微博投诉句识别框架，提出了投诉句识别的MCSI模型；应用人工神经网络方法，基于投诉信息特征、语句位置、句式、句长、词频5个属性，识别语句是否为投诉句。与多种基线模型相比，本文提出的模型可以提高投诉句识别性能。
근년래，미박투소성위용호유권적신도경。면대해량미박투소，기업여하재유한자원하실현미박투소자동진단화처리，인발료학술화업계적고도관주。미박투소구식별시미박투소자동화처리적전제。본문침대미박투소구식별문제，설계료미박투소구식별광가，제출료투소구식별적MCSI모형；응용인공신경망락방법，기우투소신식특정、어구위치、구식、구장、사빈5개속성，식별어구시부위투소구。여다충기선모형상비，본문제출적모형가이제고투소구식별성능。
Nowadays, microblogging complaints have become a new way for users to express their rights and dissatisfactions. How to achieve automatic diagnosis and treatment of microblogging complaints with limited resource is causing great concern in the academic and practice. Recognition of complaint sentences from microblogging complaint is a prerequisite for automated processing of microblogging complaints and this work designs a Microblogging Complaint Sentence Recognition (MCSR) model for the task. The model uses artificial neural network method, based on 5 features including the complaint information feature, sentence position, syntactical structure, sentence length, and word frequency to identify whether the sentence is a complaint sentence. In comparison with a variety of baseline models, the proposed model can improve the performance of microblogging complaint sentence recognition.