Natural Language Processing
Natural Language Processing is one of the oldest disciplines in Artificial Intelligence, since automatic language understanding was viewed from the beginning as a form of capturing the essence of human thinking and communication. Moreover, the theoretical field of linguistics has a hundred-year history as a scientific discipline, whereas computational linguistics has a forty-year history as a part of computer science. But it is only in the past five years that language understanding has emerged as an industry reaching millions of people, with information retrieval and machine translation available on the Internet, and speech processing becoming popular on desk computers. This industry has been enabled by theoretical advances in the representation and processing of language information. As a large percentage of the existing on-line data has textual form, the advent of new forms of processing textual and multimedial information is expected in the new century.
This course in natural language processing and computational linguistics. The course is concerned with concepts, models and algorithms to interpret, generate and learn natural languages, as well as applications of NLP. The goal of the course is for the students to be familiar with basic concepts in NLP, understand the algorithms and methods for NLP and acquire the skills for developing NLP tools/systems. Also this course will introduce students to several modern topics in Natural Language processing, ranging from Question-Answering on the Web to Summarization, Information Extraction, Machine Translation or Discourse Processing.
The course has four major parts:
It also serves three major goals:
Students are expected to have good knowledge of :
· Artificial Intelligence
· Theory of Automata and Languages
1-Introduction to Natural Language Processing
2. by Lucja M. Iwanska and Stuart C. Shapiro, Natural Language Processing and Knowledge Representation,Language for Knowledge and Knowledge for LanguageISBN : 0-262-59021-2.MIT Press