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University of California, Berkeley School of Information
     Management and Systems
SIMS > Academics > Courses > Course Catalog > INFOSYS 256
   

INFOSYS 256: Applied Natural Language Processing

 

Course Description

Students will receive no credit for 256 after receiving credit for 290 section 2. This course examines the state-of-the-art in applied Natural Language Processing (also known as content analysis and language engineering), with an emphasis on how well existing algorithms perform and how they can be used (or not) in applications. Topics include part-of-speech tagging, shallow parsing, text classification, information extraction, incorporation of lexicons and ontologies into text analysis, and question answering. Students will apply and extend existing software tools to text-processing problems.

Prerequisites

255, a computer science background, or equivalent