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Instructor Class Description

Time Schedule:

Fei Xia
LING 570
Seattle Campus

Shallow Processing Techniques for Natural Language Processing

Techniques and algorithms for associating relatively surface-level structures and information with natural language corpora, including POS tagging, morphological analysis, preprocessing/segmentation named-entity recognition, chunk parsing, and word-sense disambiguation. Examines linguistic resources that can be leveraged for these tasks (e.g., WordNet). Prerequisite: a minimum grade of 2.7 in each of CSE 326 or equivalent, STAT 391 or equivalent, and LING 473 or passing score on the placement exam. Offered: A.

Class description

Student learning goals

General method of instruction

Recommended preparation

Prerequisites: (1) if you are a CLMA student, you need to pass either the CLMA placement test or LING473 first, and you should register for Section C. (2) if you are a NLT (Natural Language Technology Certificate) student, you need to take and pass LING473 first, and you should register for Section A. (3) for everyone else, before taking the course, you need to know the following: programming (C/C++, Java, Perl, or Python), unix, a college-level course on statistics and probability, finite-state automaton, regular expression, regular grammar, and context-free grammar. You should register for Section B.

If you believe you meet the prerequisites, please email Joyce at phoneme@u.washington.edu for the add code. In your email, please specify the following: - Which section are you registering for?

- explain how you meet the prerequisites: e.g., including your grades for the placement test and/or LING 473 for CLMA/NLT students, and an unofficial transcripts for non-CLMA/NLT students.

Thanks.

-Fei

Class assignments and grading


The information above is intended to be helpful in choosing courses. Because the instructor may further develop his/her plans for this course, its characteristics are subject to change without notice. In most cases, the official course syllabus will be distributed on the first day of class.
Last Update by Fei Xia
Date: 06/25/2009