CSC 350 - Computational Linguistics
I. COURSE NUMBER AND CREDIT:
CSC/ISC 350 - 3 S.H.
II. COURSE TITLE:
Computational Linguistics
III. COURSE DESCRIPTION:
Computational approach to the study of language.
Problems in understanding and producing natural (or
natural-like) language by computer and humans.
Theories of parsing, meaning, knowledge
representation, and communication, along with their
mechanical embodiments.
IV. PREREQUISITES:
CSC/ISC 221 and CSC 241
V. JUSTIFICATION:
VI. COURSE OBJECTIVES:
As a result of this course, students will be able to:
1. Understand the concepts of meaning, language and
understanding from an artificial intelligence
perspective.
2. Use logic as a descriptive tool in formulating
various grammars.
3. Understand fundamental concepts of representing
English for various computational purposes, and
to present several different grammar types.
4. Outline the fundamental role of semantics in
disambiguating syntax driven parsing.
5. Paraphrase information once a phrase has been
parsed.
6. Examine properties of existing systems in a case-
study manner, comparing differing approaches.
VII. COURSE OUTLINE:
A. Introduction
1. Symbolizing Concepts
2. Semantic Processing and Semantic Networks
3. The Role of Syntax
B. The Place of Logic
1. Propositional Logic
2. Predicate Logic
3. Procedural Logic
4. Definite Clause Grammars
C. Word Patterns
1. Context-free Grammars and Parsing
2. Transformational Grammar
3. Augmented Transition Network Grammars
4. Case and Functional Grammars
D. Translation to Semantic Relations
1. Generative Semantics
2. Semantic Nets and Memory Models
3. Context and Scripts
E. Questing and Summarizing
1. Analysis of English Questions
2. Retrieving Answers with Fuzzy Matching
3. Generating English Answers
4. Computing Summaries
5. Paraphrase
F. Case Studies
VIII. METHODS OF INSTRUCTION:
The primary mode of instruction will be lectures with
emphasis on basic concepts and applications of these
concepts. Textbook readings will be supplemented by
primary source material. Assignments which require
students to apply specific concepts will be regularly
given. These assignments will include small
programming projects.
IX. COURSE REQUIREMENTS:
X. MEANS OF EVALUATION:
Examinations and homework assignments.
XI. RESOURCES:
XII. BIBLIOGRAPHY:
Barr, A. & Feigenbaum, E. A. (Eds.). The Handbook of
Artifical Intelligence (volumes 1-3). Kaufmann:
Los Altos, CA, 1981.
Brady, M. & Berwick. R. C. (Eds.). Computational
Models of Discourse. Cambridge, MA: MIT Press,
1982.
Charniak, E. & Wilks, Y. (Eds.). Computational
Semantics: An Introduction to Artificial
Intelligence and Natural Language Comprehension.
New York: North-Holland, 1976.
King, M. (Ed.). Parsing Natural Language. Orlando:
Academic Press, 1983.
O'Shea, T. & Eisenstadt, M. Artificial Intelligence:
Tools, Techniques, and Applications. New York:
Harper & Row, 1984.
Sager, N. Natural Language Information Processing: A
Computer Grammar of English and Its Applications.
Reading, MA: Addison-Wesley, 1981.
Schank, R. C. & Colby, K. M. (Eds.). Computer Models
of Thought and Language. San Francisco, Freeman,
1973.
Simmons, R. F. Computations From the English.
Englewood Cliffs, NJ: Prentice-Hall, 1984.
Winograd, T. Language as a Cognitive Process
- Volume I: Syntax. Reading, MA: Addison-Wesley,
1983.