CSSE 490: Natural Language Processing and Textual Entailment

CSSE 490: Natural Language Processing and Textual Entailment
Rose-Hulman Institute of Technology
Computer Science and Software Engineering Department
Syllabus
Spring 2020

Natural Language Processing is a key field in Artificial Intelligence and Robotics. The use of NLP enables seamless interaction with computers, in particular, robots. In this course, we will study modern (statistical) NLP techniques to get an overview of current problems and potential solutions to them. NLP is a fairly large field, part of the course will focus on NLP in the context of textual entailment. Textual entailment is concerned about information that can be inferred from a given text, however, in a light-weight approach, i.e. without the use of FOL reasoners.

This is a research course in which students take an active part in shaping the direction of the course as well as in presenting course materials. As such, this course is conducted very much like a graduate seminar. If you are interested in attending graduate school, this course would be a good way to find out whether you are interested in this sort of endaeavor and if you are, to develop your research tool inventory, which includes studying, evaluating and presenting other people's work, as well as researching and working on a research project which advances the field.

Prerequisites

CSSE 230

Instructor

Michael Wollowski

Course Objectives

There are three main objectives for the course. They are:

To evaluate the power and limitation of key NLP and TE solutions.
To advance the state of the art in NLP or TE
To develop students' research skills.

Book

In addition to research papers, we will be studying select chapters from the following books which are freely available on the author's website:

Speech and Language Processing (3rd ed. draft) by Dan Jurafsky and James H. Martin
Recognizing Textual Entailment: Models and Applications by Ido Dagan, Dan Roth, Mark Sammons and Fabio Massimo Zanzotto

Grading

Participation (such as participation and preparedness for in-class discussions, participation in newsgroup discussions, willingness to scour for information, effort you put into the course, as evidenced by your journal and reading summaries)	10%
Presentations (about 6, together with a partner)	25%
Project/Experiments	60%
Final Exam	5%

Citizenship

The success of this course depends on your active participation in class. Please come to class prepared and do things that contribute to your learning and that of others.