Файл:Deep Learning for Natural Language Processing - Theory and Practice CIKM14 tutorial HeGaoDeng.pdf

Xiaodong He, Jianfeng Gao, Li Deng Deep Learning Technology Center Microsoft Research, Redmond, WA

Tutorial Outline

• Part I: Background

• Part II: Deep learning in spoken language understanding
  • Domain & intent detection using DNN
  • Slot filling using RNN

• Part III: Learning semantic embedding
  • Semantic embedding^ from words to sentences
  • The Deep Structured Semantic Model (DSSM)
  • DSSM in practice: Word Embedding, Information Retrieval, Question Answering

• Part IV: Deep semantic similarity model for text processing
  • Overview of Semantic Similarity Model
  • DSSM for Web Search
  • DSSM for recommendation
  • DSSM for semantic translation models

• Part V: Conclusion