Fall 2005

Department of Electronic Engineering, National Yunlin University of Science and Technology

Course : Natural Language Processing

Time : Tuesday 9:10-12:00

Location : ES 707

Instructor: 黃永廣

Office : ES 705 (Extension: 4330)

AI Lab : ES 715 (Extension: 4391) http://plum.yuntech.edu.tw

Email : wongwk@yuntech.edu.tw

Syllabus

Related Websites:

Textbook's website
Manning's course at Stanford University: Natural language processing
Stanford's website on resources of statistical natural language
Reinhard's course on Machine translation
MIT's opencourseware on Natural language & the computer representation of knowledge
Callan's course at Carnegie Mellon University: Text data mining
Japkowicz's course at the University of Ottawa: Natural language processing, a statistical approach
Poesio's course at the Essex University: Advanced natural language engineering
Poole's course at the University of British Columbia, Canada: CS322 Introduction to Artificial Intelligence
Park's course at Korean Advanced Institute of Science and Technology, CS370 Symbolic Programming
SWI-Prolog. A popular public domain Prolog from the Netherlands. http://www.swi-prolog.org/

Schedule:

Date	Content	Text and reference reading	Lecture notes	Comments
9/13	Introduction to artificial intelligence and natural language processing	Poole et al., Chapter 1	Poole: Chapter 1, Lectures 1, 2, 3
9/20	Propositional and predicate logic, semantics, interpretation, model, logical consequences	Poole et al., Chapter 2	Poole: Chapter 2, Lectures 1, 2, 3
9/27	Bottom-up proof procedures, soundness & completeness of this procedure	Poole et al., Chapter 2	Poole: Chapter 2, Lectures 4, 5, 6
10/4	Introduction to statistical NLP, linguistic essentials, text mining problems	Manning & Schutze Chapters 1, 3	Japkowicz: Lectures 2, 3 Callan: Lecture 1	Assignment 1 out: concordancer
10/11	Corpus-based works, collocations, statistical inference, n-gram models over sparse data	Manning & Schutze Chaps. 4, 5, 6	Japkowicz: Lectures 6, 7 Manning: fsnlp-statest-slides-6.ps Callan: Lecture 2
10/18	Introduction to word sense disambiguation 盛群半導體公司捐贈儀式	Manning & Schutze Chap. 7	Manning: fsnlp-wsd-slides-6.pdf	Assignment 1 due
10/25	Markov models, part of speech tagging	Manning & Schutze Chaps. 9, 10	Berwick: Lecture 4
11/1	Part of speech tagging, lexicon, lexical semantics, WordNet	Manning & Schutze Chaps. 9, 10, 7	Poesio: D3_POS.ppt, D4_lexicon.ppt
11/8	Machine translation	Manning & Schutze Chap. 13	Manning: Chris-Knight-mt-lecture2.pdf Reinhard: MT01, MT02	Assignment 2 out: sentence alignment of English-Chinese translation
11/15	Machine translation	Manning & Schutze Chap. 13	Reinhard: MT03, MT04, MT06
11/22	Machine translation	Manning & Schutze Chap. 13	Reinhard: MT06, MT07	Students presented initial implementation of Assignment 2
11/29	Text mining: Text representation	Manning & Schutze Chap. 15	Callan: Text representation	Assignment 2 due; Assignment 3 out
12/6	Text mining: Frequency and co-occurrence analysis	Manning & Schutze Chap. 15	Callan: FreqAndCooccur	Confirm students' choices of papers to review
12/13	Text mining: Frequency and co-occurrence analysis, clustering	Manning & Schutze Chap. 14	Callan: Clustering
12/20	Text mining: Ontologies, text classification	Manning & Schutze Chap. 16	Callan: Ontologies
12/27	Students' presentations: 黃文有,黃俊瑋,廖允在, 陳俊廷,童智楷			Each oral presentation takes 25 minutes
1/3	殷聖楷,賴孟緯, 李健豪,陳侑興,沈威龍
1/10	方柏文,陳漢鴻,詹家欣, 黃文有,張文獻