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Deep Learning for Named Entity Recognition

About a year ago I wrote a blog post about recent research in Deep Learning for Natural Language Processing covering several subareas. One of the areas I didn’t cover was Deep Learning for Named Entity Recognition – so here are some interesting recent (2015-2016) papers related to that:

  1. Capturing Semantic Similarity for Entity Linking with Convolutional Neural Networks – authors: M Francis
  2. Entity Attribute Extraction from Unstructured Text with Deep Belief Network – authors: B Zhong, L Kong, J Liu
  3. Learning Word Segmentation Representations to Improve Named Entity Recognition for Chinese Social Media – authors: N Peng, M Dredze
  4. Biomedical Named Entity Recognition based on Deep Neutral Network – authors: L Yao, H Liu, Y Liu, X Li, MW Anwar
  5. Shared tasks of the 2015 workshop on noisy user-generated text: Twitter lexical normalization and named entity recognition – authors: T Baldwin, MC de Marneffe, B Han, YB Kim, A Ritter…
  6. Semi-Supervised Approach to Named Entity Recognition in Spanish Applied to a Real-World Conversational System – authors: SS Bojórquez, VM González
  7. Boosting Named Entity Recognition with Neural Character Embeddings – authors: C dos Santos, V Guimaraes, RJ Niterói, R de Janeiro
  8. Exploring Recurrent Neural Networks to Detect Named Entities from Biomedical Text – authors: L Li, L Jin, D Huang
  9. Entity-centric search: querying by entities and for entities – authors: M Zhou
  10. Automatic Entity Recognition and Typing from Massive Text Corpora: A Phrase and Network Mining Approach – authors: X Ren, A El
  11. Boosting Named Entity Recognition with Neural Character Embeddings – authors: CN Santos, V Guimarães
  12. Named Entity Recognition in Chinese Clinical Text Using Deep Neural Network. – authors: Y Wu, M Jiang, J Lei, H Xu
  13. Context-aware Entity Morph Decoding – authors: B Zhang, H Huang, X Pan, S Li, CY Lin, H Ji, K Knight…
  14. Training word embeddings for deep learning in biomedical text mining tasks – authors: Z Jiang, L Li, D Huang, L Jin
  15. Entity Attribute Extraction from Unstructured Text with Deep Belief Network – authors: B Zhong, L Kong, J Liu
  16. Building Text-mining Framework for Gene-Phenotype Relation Extraction using Deep Leaning – authors: D Jang, J Lee, K Kim, D Lee
  17. Text Mining in Social Media for Security Threats – authors: D Inkpen
  18. Text Understanding from Scratch – authors: X Zhang, Y LeCun
  19. Syntax-based Deep Matching of Short Texts – authors: M Wang, Z Lu, H Li, Q Liu
  20. PTE: Predictive Text Embedding through Large-scale Heterogeneous Text Networks – authors: J Tang, M Qu, Q Mei
  21. Automatic Entity Recognition and Typing from Massive Text Corpora: A Phrase and Network Mining Approach – authors: X Ren, A El
  22. Domain-Specific Semantic Relatedness from Wikipedia Structure: A Case Study in Biomedical Text – authors: A Sajadi, EE Milios, V Kešelj, JCM Janssen
  23. Deep Unordered Composition Rivals Syntactic Methods for Text Classification – authors: M Iyyer, V Manjunatha, J Boyd
  24. Representing Text for Joint Embedding of Text and Knowledge Bases – authors: K Toutanova, D Chen, P Pantel, H Poon, P Choudhury…
  25. In Defense of Word Embedding for Generic Text Representation – authors: G Lev, B Klein, L Wolf

Best regards,

Amund Tveit ( @atveit )

btw: if you want to work (with me) as a Data Scientist on Deep Learning, check out this position

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