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Natural Language Processing

文件类型 收录时间 最后活跃 资源热度 文件大小 文件数量
2015-12-20 18:34 2024-12-24 12:53 88 1.1 GB 102
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Natural Language Processing

文件列表
  1. 1 - 1 - Course Introduction (14_11).mp412.26MB
  2. 10 - 1 - What is Relation Extraction_ (9_47).mp410.19MB
  3. 10 - 2 - Using Patterns to Extract Relations (6_17).mp46.08MB
  4. 10 - 3 - Supervised Relation Extraction (10_51).mp410.31MB
  5. 10 - 4 - Semi-Supervised and Unsupervised Relation Extraction (9_53).mp410.06MB
  6. 11 - 1 - The Maximum Entropy Model Presentation (12_14).mp417.28MB
  7. 11 - 2 - Feature Overlap_Feature Interaction (12_51).mp412.63MB
  8. 11 - 3 - Conditional Maxent Models for Classification (4_11).mp44.79MB
  9. 11 - 4 - Smoothing_Regularization_Priors for Maxent Models (29_24).mp428.8MB
  10. 12 - 1 - An Intro to Parts of Speech and POS Tagging (13_19).mp411.88MB
  11. 12 - 2 - Some Methods and Results on Sequence Models for POS Tagging (13_04).mp412.82MB
  12. 13 - 1 - Syntactic Structure_ Constituency vs Dependency (8_46).mp48.96MB
  13. 13 - 2 - Empirical_Data-Driven Approach to Parsing (7_11).mp47.24MB
  14. 13 - 3 - The Exponential Problem in Parsing (14_30).mp414.87MB
  15. 14 - 1 - Instructor Chat (9_02).mp423.78MB
  16. 15 - 1 - CFGs and PCFGs (15_29).mp416.65MB
  17. 15 - 2 - Grammar Transforms (12_05).mp412.05MB
  18. 15 - 3 - CKY Parsing (23_25).mp426.18MB
  19. 15 - 4 - CKY Example (21_52).mp423.44MB
  20. 15 - 5 - Constituency Parser Evaluation (9_45).mp410.66MB
  21. 16 - 1 - Lexicalization of PCFGs (7_03).mp47.12MB
  22. 16 - 2 - Charniak_'s Model (18_23).mp418.96MB
  23. 16 - 3 - PCFG Independence Assumptions (9_44).mp49.83MB
  24. 16 - 4 - The Return of Unlexicalized PCFGs (20_53).mp421.22MB
  25. 16 - 5 - Latent Variable PCFGs (12_07).mp412.55MB
  26. 17 - 1 - Dependency Parsing Introduction (10_25).mp411.15MB
  27. 17 - 2 - Greedy Transition-Based Parsing (31_05).mp431.36MB
  28. 17 - 3 - Dependencies Encode Relational Structure (7_20).mp47.24MB
  29. 18 - 1 - Introduction to Information Retrieval (9_16).mp49.06MB
  30. 18 - 2 - Term-Document Incidence Matrices (8_59).mp49.02MB
  31. 18 - 3 - The Inverted Index (10_42).mp410.71MB
  32. 18 - 4 - Query Processing with the Inverted Index (6_43).mp46.74MB
  33. 18 - 5 - Phrase Queries and Positional Indexes (19_45).mp420.6MB
  34. 19 - 1 - Introducing Ranked Retrieval (4_27).mp44.58MB
  35. 19 - 2 - Scoring with the Jaccard Coefficient (5_06).mp45.39MB
  36. 19 - 3 - Term Frequency Weighting (5_59).mp46.36MB
  37. 19 - 4 - Inverse Document Frequency Weighting (10_16).mp411.12MB
  38. 19 - 5 - TF-IDF Weighting (3_42).mp44.1MB
  39. 19 - 6 - The Vector Space Model (16_22).mp416.93MB
  40. 19 - 7 - Calculating TF-IDF Cosine Scores (12_47).mp413.23MB
  41. 19 - 8 - Evaluating Search Engines (9_02).mp48.82MB
  42. 2 - 1 - Regular Expressions (11_25).mp410.85MB
  43. 2 - 2 - Regular Expressions in Practical NLP (6_04).mp47.96MB
  44. 2 - 3 - Word Tokenization (14_26).mp412.47MB
  45. 2 - 4 - Word Normalization and Stemming (11_47).mp410.08MB
  46. 2 - 5 - Sentence Segmentation (5_31).mp44.97MB
  47. 20 - 1 - Word Senses and Word Relations (11_50).mp414.89MB
  48. 20 - 2 - WordNet and Other Online Thesauri (6_23).mp48.75MB
  49. 20 - 3 - Word Similarity and Thesaurus Methods (16_17).mp420.24MB
  50. 20 - 4 - Word Similarity_ Distributional Similarity I (13_14).mp415.03MB
  51. 20 - 5 - Word Similarity_ Distributional Similarity II (8_15).mp49.46MB
  52. 21 - 1 - What is Question Answering_ (7_28).mp48.89MB
  53. 21 - 2 - Answer Types and Query Formulation (8_47).mp410.12MB
  54. 21 - 3 - Passage Retrieval and Answer Extraction (6_38).mp47.68MB
  55. 21 - 4 - Using Knowledge in QA (4_25).mp45.27MB
  56. 21 - 5 - Advanced_ Answering Complex Questions (4_52).mp46.17MB
  57. 22 - 1 - Introduction to Summarization.mp46.02MB
  58. 22 - 2 - Generating Snippets.mp49.61MB
  59. 22 - 3 - Evaluating Summaries_ ROUGE.mp46.53MB
  60. 22 - 4 - Summarizing Multiple Documents.mp413.4MB
  61. 23 - 1 - Instructor Chat II (5_23).mp418.63MB
  62. 3 - 1 - Defining Minimum Edit Distance (7_04).mp46.6MB
  63. 3 - 2 - Computing Minimum Edit Distance (5_54).mp45.38MB
  64. 3 - 3 - Backtrace for Computing Alignments (5_55).mp45.53MB
  65. 3 - 4 - Weighted Minimum Edit Distance (2_47).mp42.83MB
  66. 3 - 5 - Minimum Edit Distance in Computational Biology (9_29).mp48.95MB
  67. 4 - 1 - Introduction to N-grams (8_41).mp47.64MB
  68. 4 - 2 - Estimating N-gram Probabilities (9_38).mp49.48MB
  69. 4 - 3 - Evaluation and Perplexity (11_09).mp49.6MB
  70. 4 - 4 - Generalization and Zeros (5_15).mp44.67MB
  71. 4 - 5 - Smoothing_ Add-One (6_30).mp46.04MB
  72. 4 - 6 - Interpolation (10_25).mp49.38MB
  73. 4 - 7 - Good-Turing Smoothing (15_35).mp413.44MB
  74. 4 - 8 - Kneser-Ney Smoothing (8_59).mp48.44MB
  75. 5 - 1 - The Spelling Correction Task (5_39).mp44.84MB
  76. 5 - 2 - The Noisy Channel Model of Spelling (19_30).mp417.79MB
  77. 5 - 3 - Real-Word Spelling Correction (9_19).mp48.56MB
  78. 5 - 4 - State of the Art Systems (7_10).mp46.61MB
  79. 6 - 1 - What is Text Classification_ (8_12).mp47.7MB
  80. 6 - 2 - Naive Bayes (3_19).mp43.25MB
  81. 6 - 3 - Formalizing the Naive Bayes Classifier (9_28).mp48.19MB
  82. 6 - 4 - Naive Bayes_ Learning (5_22).mp46.18MB
  83. 6 - 5 - Naive Bayes_ Relationship to Language Modeling (4_35).mp44.09MB
  84. 6 - 6 - Multinomial Naive Bayes_ A Worked Example (8_58).mp411.38MB
  85. 6 - 7 - Precision, Recall, and the F measure (16_16).mp415.72MB
  86. 6 - 8 - Text Classification_ Evaluation (7_17).mp411.54MB
  87. 6 - 9 - Practical Issues in Text Classification (5_56).mp46.56MB
  88. 7 - 1 - What is Sentiment Analysis_ (7_17).mp49.56MB
  89. 7 - 2 - Sentiment Analysis_ A baseline algorithm (13_27).mp413.18MB
  90. 7 - 3 - Sentiment Lexicons (8_37).mp410.58MB
  91. 7 - 4 - Learning Sentiment Lexicons (14_45).mp418.65MB
  92. 7 - 5 - Other Sentiment Tasks (11_01).mp414.53MB
  93. 8 - 1 - Generative vs. Discriminative Models (7_49).mp47.92MB
  94. 8 - 2 - Making features from text for discriminative NLP models (18_11).mp416.66MB
  95. 8 - 3 - Feature-Based Linear Classifiers (13_34).mp413.46MB
  96. 8 - 4 - Building a Maxent Model_ The Nuts and Bolts (8_04).mp47.8MB
  97. 8 - 5 - Generative vs. Discriminative models_ The problem of overcounting evidence (12_15).mp412.22MB
  98. 8 - 6 - Maximizing the Likelihood (10_29).mp49.83MB
  99. 9 - 1 - Introduction to Information Extraction (9_18).mp49.39MB
  100. 9 - 2 - Evaluation of Named Entity Recognition (6_34).mp46.75MB
  101. 9 - 3 - Sequence Models for Named Entity Recognition (15_05).mp414.15MB
  102. 9 - 4 - Maximum Entropy Sequence Models (13_01).mp413.3MB
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