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C SC 620
Advanced Topics in Natural Language Processing
Spring '04

Natural language processing (NLP) is a broad and exciting field at the intersection of computer science, formal linguistics and cognitive science. Areas include machine translation, information retrieval, document processing and summarization, machine learning, grammar formalisms and parsing algorithms. This course will survey selected topics in NLP highlighting both the use of large-scale lexical resources and techniques in the implementation of linguistic theories.

Instructor: Sandiway Fong
Office (temporary): RM 309 Douglass


Location Gould-Simpson 701
Time Tuesday-Thursdays 12:30 pm - 1:45 pm

Pre-requisites and Requirements

Students should have some background in computational linguistics, formal linguistics, logic or formal grammars or artificial intelligence. Otherwise, permission of the instructor is required.

Lectures will follow a seminar format. We will discuss both general techniques and assigned papers.

Formal requirements for registered students:

Lecture Notes

Available in Adobe PDF and PowerPoint formats.


Date Lecture Notes and Papers Topic
PDF Powerpoint
1/15 lecture1.pdf lecture1.ppt Background and organizational meeting.

For next time: WordNet. Read Introduction to WordNet: An On-line Lexical Database
(pages 1-9 in the 5 papers package below)

1/20 lecture2.pdf lecture2.ppt 6 slides. Introduction to WordNet.
5papers.pdf   Reading: WordNet 5 core papers.

Available locally or download directly from Princeton

1/22 lecture3.pdf lecture3.ppt WordNet software: browsers and wnconnect.
Example puzzles and possible software projects:
(1) What do the following have in common?
(2) Autoantonyms or antagonyms.
1/27 lecture4.pdf lecture4.ppt WordNet organization. Case study: verbs.

Paper: English Verbs as a Semantic Net, Fellbaum, C.
(pp. 40-61 from the core papers download.)

1/29     No lecture today


Date Lecture Notes and Papers Topic
PDF Powerpoint
2/03 lecture5.pdf lecture5.ppt Instructions for class presentation starting 2/17.
Paper selection from conference proceedings.
icos3.pdf   Semantic Opposition and WordNet
2/05 lecture6.pdf lecture6.ppt Paper assignments
bleaching.pdf   Semantic Bleaching and WordNet
2/10 telicroles.pdf Telic Roles and WordNet
2/12 lecture8.pdf lecture8.ppt WordNet and Canonical Color
kael.pdf kael.ppt Student Presentation: Kael Dai.
Paper: Automated Discovery of Telic Relations for Wordnet by De Boni and Manandhar
2/17 lecture9.pdf lecture9.ppt Student Presentations
he.pdf he.ppt Hai-Feng He. Paper: Using WordNet to Improve User Modelling in a Web Document Recommender System by Magnini, B. and C. Strapparava
baker.pdf baker.ppt Patrick Baker. Paper: Chinese Characters and Top Ontology in EuroWordNet by Wong, S. and K. Pala
rabee.pdf rabee.ppt Rabee Ali Alshemali. Paper: Comparing Ontology-based and Corpus-based Domain Annotations in WordNet by Magnini, B. et al.
chow.pdf chow.ppt Sandy Chow. Paper: Creating a Bilingual Ontology: A Corpus-Based Approach for Aligning WordNet and HowNet by Carpuat, M. et al.
2/19 lecture10.pdf lecture10.ppt Reading list for Machine Translation
Student Presentations
schlecht.pdf schlecht.ppt Joseph Schlecht. Paper: Using Lexical Knowledge to Evaluate the Novelty of Rules Mined from Text by Basu, S. et al.
alcock.pdf alcock.ppt Keith Alcock. Paper: Semantic distance in WordNet: An experimental, application-oriented evaluation of five measures. by Budanitsky, A. and G. Hirst
eggers.pdf eggers.ppt Shauna Eggers. Paper: The Informative Role of WordNet in Open-Domain Question Answering by Pasca, M. & S. Harabagiu
swaminathan.pdf swaminathan.ppt Ranjini Swaminathan. Paper: Word Sense Disambiguation Using Semantic Graph by Unny, N. & P. Bhattacharyya
2/24 lecture11.pdf lecture11.ppt Speech-to-speech Machine Translation (MT) system demo
Student Presentation
landis.pdf landis.ppt Matt Landis. Paper: Words with Attitude by Kamps, J. and M. Marx
2/26     No lecture today


Date Lecture Notes and Papers Topic
PDF Powerpoint
3/2 lecture12.pdf lecture12.ppt Paper 1: Translation. Weaver, W.
Student Presentation
wing.pdf wing.ppt Ben Wing. Paper: Cross-Linguistic Discovery of Semantic Regularity. Peters, W. et al.
3/4 lecture13.pdf lecture13.ppt Paper 3: The Mechanical Determination of Meaning. Reifler, E.
3/9 lecture14.pdf lecture14.ppt Paper 5: A Framework for Syntactic Translation. Yngve, V.
3/11 lecture15.pdf lecture15.ppt New reading list for Machine Translation
Paper 6: The Present Status of Automatic Translation of Languages. Bar-Hillel, Y.
3/16     Spring break: no lecture
3/18     Spring break: no lecture
3/23 lecture16.pdf lecture16.ppt Paper 12: Correlational Analysis and Mechanical Translation. Ceccato, S.
3/25 lecture17.pdf lecture17.ppt Paper 13: Automatic Translation: Some Theoretical Aspects and the Design of a Translation System. Kulagina, O. and I. Mel'cuk
3/30 lecture18.pdf lecture18.ppt (43 slides)
Paper 16: Automatic Translation and the Concept of Sublanguage. Lehrberger, J.


Date Lecture Notes and Papers Topic
PDF Powerpoint
4/1 lecture18.pdf lecture18.ppt Continued.
Paper 16: Automatic Translation and the Concept of Sublanguage. Lehrberger, J.
4/6 lecture19.pdf lecture19.ppt Paper 17: The Proper Place and Men and Machies in Language Translation. Kay, M.

New readings

4/8 lecture20.pdf lecture20.ppt EU News
Paper 19: Montague Grammar and Machine Translation. Landsbergen, J.
4/13 lecture21.pdf lecture21.ppt Phraselator
Paper 20: Dialogue Translation vs. Text Translation. Tsujii, J,-I. and M. Nagao.
Paper 21: Translation by Structural Correspondences. Kaplan, R. et al.
4/15 lecture22.pdf lecture22.ppt Papero/E-Navi
Ectaco UT-103
Online translation tools story
Paper 22: Pros and Cons of the Pivot and Transfer Approaches in Multilingual Machine Translation. Boitet, C.
4/20 lecture23.pdf lecture23.ppt Vocera
Paper 31: A Framework of a Mechanical Translation between Japanese and English by Analogy Principle. Nagao, M.
4/24 lecture24.pdf lecture24.ppt Language Weaver
Paper 33: A Statistical Approach to Machine Translation. Brown, P.F. et al.
4/27     No lecture
4/29     No lecture


Date Lecture Notes and Papers Topic
PDF Powerpoint
5/4 lecture25.pdf lecture25.ppt MT Summit IX
Panel: Have we found the Holy Grail?
Paper: Hutchins, J. Has Machine Translation Improved?

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