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文件列表
1 - 1 - Course Introduction (14:11).mp4
12.9 MB
1. Basic Text Processing/2 - 1 - Regular Expressions (11:25).mp4
11.4 MB
1. Basic Text Processing/2 - 2 - Regular Expressions in Practical NLP (6:04).mp4
8.4 MB
1. Basic Text Processing/2 - 3 - Word Tokenization (14:26).mp4
13.1 MB
1. Basic Text Processing/2 - 4 - Word Normalization and Stemming (11:47).mp4
10.6 MB
1. Basic Text Processing/2 - 5 - Sentence Segmentation (5:31).mp4
5.2 MB
10. Parsing Intro/13 - 1 - Syntactic Structure: Constituency vs Dependency (8:46).mp4
9.4 MB
10. Parsing Intro/13 - 2 - Empirical_Data-Driven Approach to Parsing (7:11).mp4
7.6 MB
10. Parsing Intro/13 - 3 - The Exponential Problem in Parsing (14:30).mp4
15.6 MB
11. Probablistic Parsing/15 - 1 - CFGs and PCFGs (15:29).mp4
17.5 MB
11. Probablistic Parsing/15 - 2 - Grammar Transforms (12:05).mp4
12.6 MB
11. Probablistic Parsing/15 - 3 - CKY Parsing (23:25).mp4
27.5 MB
11. Probablistic Parsing/15 - 4 - CKY Example (21:52).mp4
24.6 MB
11. Probablistic Parsing/15 - 5 - Constituency Parser Evaluation (9:45).mp4
11.2 MB
12. Lexicalized Parsing/16 - 1 - Lexicalization of PCFGs (7:03).mp4
7.5 MB
12. Lexicalized Parsing/16 - 2 - Charniak's Model (18:23).mp4
19.9 MB
12. Lexicalized Parsing/16 - 3 - PCFG Independence Assumptions (9:44).mp4
10.3 MB
12. Lexicalized Parsing/16 - 4 - The Return of Unlexicalized PCFGs (20:53).mp4
22.2 MB
12. Lexicalized Parsing/16 - 5 - Latent Variable PCFGs (12:07).mp4
13.2 MB
13. Dependency Parsing (Optional)/17 - 1 - Dependency Parsing Introduction (10:25).mp4
11.7 MB
13. Dependency Parsing (Optional)/17 - 2 - Greedy Transition-Based Parsing (31:05).mp4
32.9 MB
13. Dependency Parsing (Optional)/17 - 3 - Dependencies Encode Relational Structure (7:20).mp4
7.6 MB
14. Information Retrieval/18 - 1 - Introduction to Information Retrieval (9:16).mp4
9.5 MB
14. Information Retrieval/18 - 2 - Term-Document Incidence Matrices (8:59).mp4
9.5 MB
14. Information Retrieval/18 - 3 - The Inverted Index (10:42).mp4
11.2 MB
14. Information Retrieval/18 - 4 - Query Processing with the Inverted Index (6:43).mp4
7.1 MB
14. Information Retrieval/18 - 5 - Phrase Queries and Positional Indexes (19:45).mp4
21.6 MB
15. Ranked Information Retrieval/19 - 1 - Introducing Ranked Retrieval (4:27).mp4
4.8 MB
15. Ranked Information Retrieval/19 - 2 - Scoring with the Jaccard Coefficient (5:06).mp4
5.7 MB
15. Ranked Information Retrieval/19 - 3 - Term Frequency Weighting (5:59).mp4
6.7 MB
15. Ranked Information Retrieval/19 - 4 - Inverse Document Frequency Weighting (10:16).mp4
11.7 MB
15. Ranked Information Retrieval/19 - 5 - TF-IDF Weighting (3:42).mp4
4.3 MB
15. Ranked Information Retrieval/19 - 6 - The Vector Space Model (16:22).mp4
17.8 MB
15. Ranked Information Retrieval/19 - 7 - Calculating TF-IDF Cosine Scores (12:47).mp4
13.9 MB
15. Ranked Information Retrieval/19 - 8 - Evaluating Search Engines (9:02).mp4
9.2 MB
16. Semantics/20 - 1 - Word Senses and Word Relations (11:50).mp4
15.6 MB
16. Semantics/20 - 2 - WordNet and Other Online Thesauri (6:23).mp4
9.2 MB
16. Semantics/20 - 3 - Word Similarity and Thesaurus Methods (16:17).mp4
21.2 MB
16. Semantics/20 - 4 - Word Similarity: Distributional Similarity I (13:14).mp4
15.8 MB
16. Semantics/20 - 5 - Word Similarity: Distributional Similarity II (8:15).mp4
9.9 MB
17. Sentiment Analysis/7 - 1 - What is Sentiment Analysis? (7:17).mp4
10.0 MB
17. Sentiment Analysis/7 - 2 - Sentiment Analysis: A baseline algorithm (13:27).mp4
13.8 MB
17. Sentiment Analysis/7 - 3 - Sentiment Lexicons (8:37).mp4
11.1 MB
17. Sentiment Analysis/7 - 4 - Learning Sentiment Lexicons (14:45).mp4
19.6 MB
17. Sentiment Analysis/7 - 5 - Other Sentiment Tasks (11:01).mp4
15.2 MB
18. Question Answering/21 - 1 - What is Question Answering? (7:28).mp4
9.3 MB
18. Question Answering/21 - 2 - Answer Types and Query Formulation (8:47).mp4
10.6 MB
18. Question Answering/21 - 3 - Passage Retrieval and Answer Extraction (6:38).mp4
8.1 MB
18. Question Answering/21 - 4 - Using Knowledge in QA (4:25).mp4
5.5 MB
18. Question Answering/21 - 5 - Advanced: Answering Complex Questions (4:52).mp4
6.5 MB
19. Summarization/22 - 1 - Introduction to Summarization.mp4
6.3 MB
19. Summarization/22 - 2 - Generating Snippets.mp4
10.1 MB
19. Summarization/22 - 3 - Evaluating Summaries: ROUGE.mp4
6.8 MB
19. Summarization/22 - 4 - Summarizing Multiple Documents.mp4
14.1 MB
2. Edit Distance/3 - 1 - Defining Minimum Edit Distance (7:04).mp4
6.9 MB
2. Edit Distance/3 - 2 - Computing Minimum Edit Distance (5:54).mp4
5.6 MB
2. Edit Distance/3 - 3 - Backtrace for Computing Alignments (5:55).mp4
5.8 MB
2. Edit Distance/3 - 4 - Weighted Minimum Edit Distance (2:47).mp4
3.0 MB
2. Edit Distance/3 - 5 - Minimum Edit Distance in Computational Biology (9:29).mp4
9.4 MB
3. Language Modelling/4 - 1 - Introduction to N-grams (8:41).mp4
8.0 MB
3. Language Modelling/4 - 2 - Estimating N-gram Probabilities (9:38).mp4
9.9 MB
3. Language Modelling/4 - 3 - Evaluation and Perplexity (11:09).mp4
10.1 MB
3. Language Modelling/4 - 4 - Generalization and Zeros (5:15).mp4
4.9 MB
3. Language Modelling/4 - 5 - Smoothing: Add-One (6:30).mp4
6.3 MB
3. Language Modelling/4 - 6 - Interpolation (10:25).mp4
9.8 MB
3. Language Modelling/4 - 7 - Good-Turing Smoothing (15:35).mp4
14.1 MB
3. Language Modelling/4 - 8 - Kneser-Ney Smoothing (8:59).mp4
8.8 MB
4. Spelling Correction/5 - 1 - The Spelling Correction Task (5:39).mp4
5.1 MB
4. Spelling Correction/5 - 2 - The Noisy Channel Model of Spelling (19:30).mp4
18.7 MB
4. Spelling Correction/5 - 3 - Real-Word Spelling Correction (9:19).mp4
9.0 MB
4. Spelling Correction/5 - 4 - State of the Art Systems (7:10).mp4
6.9 MB
5. Text Classification/6 - 1 - What is Text Classification? (8:12).mp4
8.1 MB
5. Text Classification/6 - 2 - Naive Bayes (3:19).mp4
3.4 MB
5. Text Classification/6 - 3 - Formalizing the Naive Bayes Classifier (9:28).mp4
8.6 MB
5. Text Classification/6 - 4 - Naive Bayes: Learning (5:22).mp4
6.5 MB
5. Text Classification/6 - 5 - Naive Bayes: Relationship to Language Modeling (4:35).mp4
4.3 MB
5. Text Classification/6 - 6 - Multinomial Naive Bayes: A Worked Example (8:58).mp4
11.9 MB
5. Text Classification/6 - 7 - Precision, Recall, and the F measure (16:16).mp4
16.5 MB
5. Text Classification/6 - 8 - Text Classification: Evaluation (7:17).mp4
12.1 MB
5. Text Classification/6 - 9 - Practical Issues in Text Classification (5:56).mp4
6.9 MB
6. Discriminative Classifiers: Max Entropy Classifiers/8 - 1 - Generative vs. Discriminative Models (7:49).mp4
8.3 MB
6. Discriminative Classifiers: Max Entropy Classifiers/8 - 2 - Making features from text for discriminative NLP models (18:11).mp4
17.5 MB
6. Discriminative Classifiers: Max Entropy Classifiers/8 - 3 - Feature-Based Linear Classifiers (13:34).mp4
14.1 MB
6. Discriminative Classifiers: Max Entropy Classifiers/8 - 4 - Building a Maxent Model: The Nuts and Bolts (8:04).mp4
8.2 MB
6. Discriminative Classifiers: Max Entropy Classifiers/8 - 5 - Generative vs. Discriminative models: The problem of overcounting evidence (12:15).mp4
12.8 MB
6. Discriminative Classifiers: Max Entropy Classifiers/8 - 6 - Maximizing the Likelihood (10:29).mp4
10.3 MB
7. Named entity recognition and Maximum Entropy Sequence Models/9 - 1 - Introduction to Information Extraction (9:18).mp4
9.8 MB
7. Named entity recognition and Maximum Entropy Sequence Models/9 - 2 - Evaluation of Named Entity Recognition (6:34).mp4
7.1 MB
7. Named entity recognition and Maximum Entropy Sequence Models/9 - 3 - Sequence Models for Named Entity Recognition (15:05).mp4
14.8 MB
7. Named entity recognition and Maximum Entropy Sequence Models/9 - 4 - Maximum Entropy Sequence Models (13:01).mp4
13.9 MB
8. Relation Extraction/10 - 1 - What is Relation Extraction? (9:47).mp4
10.7 MB
8. Relation Extraction/10 - 2 - Using Patterns to Extract Relations (6:17).mp4
6.4 MB
8. Relation Extraction/10 - 3 - Supervised Relation Extraction (10:51).mp4
10.8 MB
8. Relation Extraction/10 - 4 - Semi-Supervised and Unsupervised Relation Extraction (9:53).mp4
10.6 MB
9. Advanced Entropy Max Models/11 - 1 - The Maximum Entropy Model Presentation (12:14).mp4
18.1 MB
9. Advanced Entropy Max Models/11 - 2 - Feature Overlap_Feature Interaction (12:51).mp4
13.2 MB
9. Advanced Entropy Max Models/11 - 3 - Conditional Maxent Models for Classification (4:11).mp4
5.0 MB
9. Advanced Entropy Max Models/11 - 4 - Smoothing_Regularization_Priors for Maxent Models (29:24).mp4
30.2 MB
9. POS Tagging/12 - 1 - An Intro to Parts of Speech and POS Tagging (13:19).mp4
12.5 MB
9. POS Tagging/12 - 2 - Some Methods and Results on Sequence Models for POS Tagging (13:04).mp4
13.4 MB
Lecture Slides/0.pdf
2.8 MB
Lecture Slides/1.pdf
896.4 kB
Lecture Slides/10.pdf
911.3 kB
Lecture Slides/11.pdf
1.2 MB
Lecture Slides/12.pdf
1.5 MB
Lecture Slides/13.pdf
900.2 kB
Lecture Slides/14.pdf
2.5 MB
Lecture Slides/15.pdf
2.3 MB
Lecture Slides/16.pdf
2.5 MB
Lecture Slides/17.pdf
1.9 MB
Lecture Slides/18.pdf
1.6 MB
Lecture Slides/19.pdf
1.5 MB
Lecture Slides/2.pdf
1.3 MB
Lecture Slides/3.pdf
2.2 MB
Lecture Slides/4.pdf
1.5 MB
Lecture Slides/5.pdf
1.8 MB
Lecture Slides/6.pdf
1.9 MB
Lecture Slides/7.pdf
1.0 MB
Lecture Slides/8.pdf
1.6 MB
Lecture Slides/9.pdf
717.0 kB
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