"深度学习与语义分析:方法与应用"
The workshop on "Deep Learning and Lexical, Syntactic, and Semantic Analysis" was held on July 27, 2018, at the Research Center for Social Computing and Information Retrieval at Harbin Institute of Technology. The event was organized by Wanxiang Che and featured a comprehensive overview of various methods and applications related to the topic. The workshop began with an introduction to the tasks involved in lexical, syntactic, and semantic analysis. It then delved into graph-based methods, which offer a structured way to represent linguistic information. Transition-based methods were also discussed, which focus on predicting the next step in a parsing process. Following a break, the workshop moved on to neural graph-based methods, which leverage neural networks to improve the performance of graph-based approaches. Neural transition-based methods were also covered, highlighting the use of neural networks in transition-based parsing models. The workshop concluded with a session on the practical applications of these methods in real-world scenarios. Participants gained insights into how deep learning techniques can be employed for analyzing and understanding language at different levels of abstraction. Overall, the workshop provided a comprehensive overview of the latest advancements in deep learning for lexical, syntactic, and semantic analysis. Participants left with a better understanding of the theoretical foundations and practical applications of these methods, setting the stage for further research and development in this rapidly evolving field. Reference Book: - G. 1 0 5 1 2
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