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Courses: [NLP]

Natural Language Processing (#215021)

Text Books & References

(*) The textbook is to be decided since [1] has many minor but noisy errors as found in my last year's course -- (*) I am thinking of using [2] or [3] plus some of my own handouts as the replacement. [1] Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition, by Daniel Jurafsky & James H. Martin, Prentice Hall, 2000. Website: Errata: (Local copy) Errata: (Local copy) - Probabilistic CYK Algorithm [*] Slides & Addons: Preface Chapter 1: Introduction, Historical Review Chapter 2: Words, Regular Expression, Fast Matching (04/09) Chapter 2+: Chinese Words, Word Segmentation (03/27) Chapter 3: Morphology & Finite State Tranducers (04/10) Chapter 6: N-Gram (Model, Parameter Estimation & Smoothing) (04/17) Good-Tuning Smoothing & Backoff (04/17) Chapter 7: HMM (Hidden Markov Model) (slides: courtesy of Prof. Sheng-Wen Shih) Chapter 9: Context-Free Grammars (and a Simple Grammar for English) (06/05) Chapter 10: Parsing Algorithms -- (todo ...) Generic Chart Parsing (todo ...) CYK (todo ...) Earley (todo ...) Left-Corner Parsing (todo ...) LR Parser with Augmentation (todo ...) Chapter 12: PCFG, Trainable Grammars, and Lexicalization [I] Trainable Grammars: 1. Inside/Outside Probabilities 2. Estimation of Rule Probabilities 3. Finding Best Parse [IIa] GPSM: PCFG enhanced with Context Sensitivity, Lexicalization and Normalization [IIb] Lexicalized PCFG (todo) Todo ... [*] Figures of the book: Figs: (Local copy) Other Figs: (Local copy) [2] Foundations of Statistical Natural Language Processing, by Christopher D. Manning and Hinrich Schutze, MIT Press, 1999. [3] Spoken Language Processing: A Guide to Theory, Algorithm, and System Development, by XueDong Huang, Alex Acero and Hsiao-Wen Hon, Prentice Hall PTR, Upper Saddle River, NJ 07458, USA, 2001. (Ch. 1, Sec. 2.3-2.5, Ch. 3, Ch. 4, Sec. 5.8, Ch. 8, Ch. 11, Ch. 12, Ch. 13, Ch. 14, Sec. 17.3-17.5 will be particularly interesting for Statistical NLP.) [4] Advanced NLP Issues ... (beyond algorithmic/application points of view ...) [1] Modeling Problems [1.1] Features [1.2] Dependency [2] Estimation Problems [2.1] Performance Metrics [2.2] Dicrimination [2.3] Robustness [2.4] Adaptive Training [2.5] Supervised vs. Unsupervised Training - Why and When

Conference Papers

[11] Chang, J.-S. , Y.-F. Luo and K.-Y. Su, "GPSM: A Generalized Probabilistic Semantic Model for Ambiguity Resolution," Proceedings of ACL-92, pp. 177--184, 30th Annual Meeting of the Association for Computational Linguistics, University of Delaware, Newark, DE, USA, 28 June--2 July, 1992. [13] Tung-Hui Chiang, Jing-Shin Chang, Ming-Yu Lin and Keh-Yih Su, "Statistical Models for Word Segmentation and Unknown Word Resolution," Proceedings of ROCLING-V, ROC Computational Linguistics Conference V, pp. 123--146, National Taiwan University, Taipei, Taiwan, ROC, Sep. 18--20, 1992. (PDF version)

Journals and Books

[6] Tung-Hui Chiang, Jing-Shin Chang, Ming-Yu Lin and Keh-Yih Su, "Statistical Word Segmentation," in C.-R. Huang, K.-J. Chen and Benjamin K. T'sou (eds.): Journal of Chinese Linguistics, Monograph Series Number 9, Readings in Chinese Natural Language Processing, pp. 147-173. University of California, Berkeley. 1996. [7] K.-Y. Su, Tung-Hui Chiang, and Jing-Shin Chang, "An Overview of Corpus-Based Statistics-Oriented (CBSO) Techniques for Natural Language Processing," International Journal of Computational Linguistics & Chinese Language Processing (CLCLP), vol. 1 no. 1, pp. 101--157, August 1996. [8] Yu-Ling Una Hsu, Jing-Shin Chang, and Keh-Yih Su, "Computational Tools and Resources for Linguistics Studies," International Journal of Computational Linguistics & Chinese Language Processing (CLCLP), vol. 2, no. 1, pp. 1-39, 1997.


Su, K.-Y., T.-H. Chiang and J.-S. Chang, "Introduction to Corpus-based Statistics-oriented (CBSO) Techniques," Pre-Conference Workshop on Corpus-based NLP, ROC Computational Linguistics Conference VII, National Tsing-Hua Univ., Taiwan, ROC., Aug. 1994. Part I: Introduction (PDF/4) (PS/4) (PDF) (PS) Part II: Basic Concepts (PDF/4) (PS/4) (PDF) (PS) Part III: Techniques (PDF/4) (PS/4) (PDF) (PS) Errata: Corrections to Part I-III TXT "RFC 1922: Chinese Character Encoding for Internet Messages," (2nd Rev.) was invited as a co-author of this RFC document for my technical revisions on the ROC part of the ISO-2022 conformant encoding standard, aka ISO-2022-CN, (originated from the Chinese Character Subworking Group of the I18N/L10N Working Group of the Asian Pacific Networking Group, APNG-CC), March, 1995. Reports related to RFC1922

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