Dr. Munindar Singh
CSC 791 603 Natural Language Processing
3 Credit Hours
This course is self-contained, and provides the essential foundation in natural language processing. It identifies the key concepts underlying NLP applications as well as the main NLP paradigms and techniques.
This course combines the core ideas developed in linguistics and in artificial intelligence to show how to understand language. Key topics include regular expressions, unigrams, and n-grams; word embeddings; syntactic (phrase-structure) and dependency parsing; semantic role labeling; language modeling; sentiment and affect analysis; question answering; text-based dialogue; discourse processing; and applications of machine learning to language processing.
The course provides the necessary background in linguistics and artificial intelligence. This course is suitable for high-performing students who are willing and able to learn abstract concepts, complete programming assignments, develop a student-selected project, and produce a term paper.
Ordinarily, the term paper would describe a research topic based on the project. The term paper could instead be a substantial review of the literature on some specific aspect of NLP or be an original contribution.
Please discuss (with me and any concerned faculty member) any potential overlap of your project and term paper with your other work; also report any overlap within your project report and term paper. Such overlap is acceptable as long as there is an assurance that the work performed for uniquely for this course is substantial.