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企業における自然言語処理技術利用の最先端

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2015/06/20 統計数理研究所オープンハウスでの招待講演のスライドです

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企業における自然言語処理技術利用の最先端

  1. 1. 1 Preferred Infrastructure 2015/06/19
  2. 2. !  -2008 !  !  2008-2011 t 1 !  t !  2011- 1 t !  t !  !  Jubatus NLP 12014- t 12015,
  3. 3. NLP 1YANS !  YANS 19 !  !  -‐‑‒19/3 9/5 !  YANS 13 !  !  "
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  18. 18. 24 http://www.soumu.go.jp/johotsusintokei/whitepaper/ja/h24/html/nc122310.html
  19. 19. !  ! 
  20. 20. t t : Siri https://www.apple.com/jp/ios/siri/ http://v-assist.yahoo.co.jp/ https://www.nttdocomo.co.jp/service/information/shabette_concier/
  21. 21. Gunosy, SmartNews http://gunosy.com https://www.smartnews.be/
  22. 22. 11/2 !  !  1970 t PC !  !  !  2000 !  t
  23. 23. 12/2 !  !  RSS 2000 !  !  1 !  2000 ! 
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  30. 30. t !  t !  !  t !  t !  !  t
  31. 31. 3.
  32. 32. !  !  1993: [Brown+93] !  1996: [Berger+96] !  2001: [Lafferty+01] !  t !  2003: Latent Dirichlet Allocation [Blei+03] !  2006: Pitman-Yor language model [Teh06] !  !  2006: [Clarke+06][Riedel+06] !  2010: [Koo+10][Rush+10] !  !  2003: Neural language model [Bengio+03] !  2010: Recurrent Neural Network [Mikolov+10] !  2013: Skipgram Model (word2vec) [Mikolov+13]
  33. 33. !  !  90 2010 ! 
  34. 34. !  ! 
  35. 35. 1. !  2011: 30% # 20% !  2012: 26% # 16% http://image-net.org/challenges/LSVRC/2012/ilsvrc2012.pdf
  36. 36. 2. !  2012/3: Google Hinton DNNresearch !  2012/4: Baidu Institute of Deep Learning !  2012/8, 10: Yahoo! IQ Engines LookFlow !  2012/12: Facebook AI Lab LeCun !  2014/1: Google DeepMind !  2014/5: Andrew Ng Baidu !  2014/8: IBM SyNAPSE
  37. 37. 3. !  2014/1 !  2014/10 -‐‑‒ !  2015/06
  38. 38. 4. t !  !  Sequence-to-sequence (2014, Google) !  !  Deep Q-Networks (2013, DeepMind) !  !  Variational Auto-Encoder (2014, UvA) !  Stochastic Backprop (2014, DeepMind) !  !  Neural Turing Machines (2014, DeepMind) !  !  Memory Networks (2014, Facebook) !  !  Show and Tell (2015, Google)
  39. 39. !  !  !  !  !  !  ! 
  40. 40. !  t !  !  !  1 !  ! 
  41. 41. Neural Network Language Model (NNLM) [Bengio +03] !  N NN !  N-1
  42. 42. Recurrent Neural Network Language Model (RNNLM) [Mikolov+10] !  t-1 t !  NNLM N !  !  http://rnnlm.org
  43. 43. Skip-gram (word2vec) [Mikolov+13] !  !  1CBOW !  Analogical reasoning !  1word2vec
  44. 44. (MV-RNN) [Socher +12] !  !  f !  Root
  45. 45. Sequence-to-sequence learning [Sutskever+14] !  ! 
  46. 46. Show and Tell [Vinyals+15] !  !  CNN RNN CNN CNN RNN
  47. 47. Memory networks [Weston+15][Sukhbaatar+15] !  ! 
  48. 48. !  !  !  1 !  End-to-end !  !  ! 
  49. 49. !  libsvm, liblinear !  !  JUMAN, Chasen, MeCab !  !  Moses (GIZA++) !  !  Stanford CoreNLP !  !  word2vec !  Skipgram !  Theano, Caffe, Torch !  t ! 
  50. 50. Chainer v1.0.0 2015/06/09 Powerful Flexible Intuitive
  51. 51. Chainer !  Chainer !  Python h(f(x) + g(x)) x f g h+
  52. 52. !  !  1 !  !  !  !  !  Chainer
  53. 53. t
  54. 54. PFI 2010 Xappy12012 !  2012 Gunosy !  !  !  t
  55. 55. Xappy t !  !  Blog !  Twitter Facebook SNS !  !  4G !  t !  !  etc. !  GUI t
  56. 56. !  !  !  !  t !  PC t !  !  !  !  10 ! 
  57. 57. (1/5) !  [Brown+93] Peter F. Brown, Vincent J. Della Pietra, Stephen A. Della Pietra, Robert L. Mercer. The mathematics of statistical machine translation: parameter estimation. Computational Linguistics Vol. 19 (2), 1993. !  [Berger+96] Adam L. Berger, Vincent J. Della Pietra, Stephen A. Della Pietra. A Maximum Entropy Approach to Natural Language Processing. Computational Linguistics, Vol. 22 (1), 1996. !  [Lafferty+01] John Lafferty, Andrew McCallum, Fernando C. N. Pereira. Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data. ICML2001.
  58. 58. (2/5) !  [Blei+03] David M. Blei, Andrew Y. Ng, Michael I. Jordan. Latent Dirichlet Allocation. JMLR Vol. 3, 2003. !  [Teh06] Yee Whye Teh. A Hierarchical Bayesian Language Model based on Pitman-Yor Processes. ACL 2006. !  [Clarke+06] James Clarke, Mirella Lapata. Constraint-Based Sentence Compression: An Integer Programming Approach. COLING/ACL 2006. !  [Riedel+06] Sebastian Riedel, James Clarke. Incremental Integer Linear Programming for Non-projective Dependency Parsing. COLING/ACL 2006.
  59. 59. (3/5) !  [Koo+10] Terry Koo, Alexander M. Rush, Michael Collins, Tommi Jaakkola, David Sontag. Dual Decomposition for Parsing with Non-Projective Head Automata. EMNLP 2010. !  [Rush+10] Alexander M. Rush, David Sontag, Michael Collins, Tommi Jaakkola. On Dual Decomposition and Linear Programming Relaxations for Natural Language Processing. EMNLP 2010. !  [Bengio+03] Yoshua Bengio, Réjean Ducharme, Pascal Vincent, Christian Jauvin. A Neural Probabilistic Language Model. JMLR, 2003.
  60. 60. (4/5) !  [Mikolov+10] Tomas Mikolov, Martin Karafiat, Lukas Burget, Jan "Honza" Cernocky, Sanjeev Khudanpur. Recurrent neural network based language model. Interspeech, 2010. !  [Mikolov+13] Tomas Mikolov, Kai Chen, Greg Corrado, Jeffrey Dean. Efficient Estimation of Word Representations in Vector Space. CoRR, 2013. !  [Socher+12] Richard Socher, Brody Huval, Christopher D. Manning, Andrew Y. Ng. Semantic Compositionality through Recursive Matrix-Vector Spaces. EMNLP2012. !  [Sutskever+14] I. Sutskever, O. Vinyals, Q. V. Le. Sequence to Sequence Learning with Neural Networks. NIPS 2014.
  61. 61. (5/5) !  [Vinyals+15] O. Vinyals, A. Toshev, S. Bengio, D. Erhan. Show and Tell: A Neural Image Caption Generator. arXiv:1411.4555, 2014. !  [Weston+15] J. Weston, S. Chopra, A. Bordes. Memory Networks. ICLR 2015 !  [Sukhbaatar+15] S. Sukhbaatar, A. Szlam, J. Weston, R. Fergus. End-To-End Memory Networks. arXiv:1503.08895, 2015.

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