CS674: Natural Language Processing
Spring 2002
Reaction Essay Readings


The primary readings in this list were chosen with a variety of criteria in mind, including impact, accessibility to the non-expert, recency, brevity, and on-line availability. Also, since these papers are meant to serve as subjects for reaction essays, "provocativeness" was an additional consideration. It was not always easy to balance all these conditions, and in some cases potentially unorthodox choices were made. Hence, this collection should not be regarded as a compilation of major papers, but rather as a set of starting points for becoming acquainted with some issues and ideas in natural language processing.

In this vein, the related references are meant simply to give some idea of the range of work on the same topic. I've omitted papers covered in lecture.

Instructions: Reaction essays are due on the following Mondays: February 4, 11, 18, and 25, and March 4. The intent is threefold: to acquaint you with some important recent papers and subjects in the field, to help you find a project topic, and to train you in how to read a research paper both quickly and effectively. Of course, it is expected that you will look at papers that aren't on the list as well!

Your reaction essay is just that: a short (one or two pages) critical reading of one of the primary papers (in red and marked with a filled-in bullet) from the list below. Briefly (1-2 paragraphs) describe the problem attacked and the solution proposed, but do not merely summarize the paper. Then, address such questions as, is the evaluation fair and informative? Are the underlying assumptions valid? When are the proposed methods applicable? On the other hand, don't spend an inordinate amount of time on these essays -- they are meant to be brief, and will be graded on a check-plus/check/check-minus scale.

A note about proper citation: it is not acceptable to copy out sentences or phrases from papers without citation. If you have not placed quotation marks around a passage, then you are claiming that these words are your own. Violating the Code of Academic Integrity may result and has resulted in failing the course. When in doubt, credit your source!

Topic index:

Language modeling
Machine translation


TAG's  (back to topic listing)

Semantics (back to topic listing)

Discourse  (back to topic listing)

Language Modeling  (back to topic listing)

Clustering (back to topic listing)

Machine Translation (back to topic listing)

Learning  (back to topic listing)

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CS674, Spring '02
Lillian Lee