基于中文字形的ELMo在电商事件识别上的应用

挖掘电商评论文本中的电商事件对分析用户购物行为和商品场景分类有重要帮助.该文给出电商事件的定义,将电商事件识别问题转换为序列标注问题,构建了一个基于电商评论文本的电商事件标注数据.该文首先在基于字符的BiLSTM-CRF神经网络模型上进行扩展,加入语言模型词向量(Embeddings from Language Mod...

E-commerce Event Detection with Chinese Character Glyph Based ELMo

Mining events in E-commerce reviews is of great help to analyze customer shopping behavior and commodity scene classification. This paper presents the definition of E-commerce event and treats the event detectionas a sequence labeling issue. Besides, It constructs an event detection corpus based on E-commerce comments. Firstly, this paper extends the character based BiLSTM-CRF model with the Embeddings from Language Models (ELMo) to improve the performance. Then, it considers the characteristics of Chinese characters, including five-strokes(Wubi) and common strokes. Two novel models are proposed to add glyph features into ELMo by using the glyph information of events. Experimental results show that the proposed models can improve performance on a newly built dataset. Finally, this paper uses two large text corpus from news and E-commerce domains to train language models. The results show that the E-commerce corpus is more helpful to the system.