Much of the most valuable information available online today resides in textual
form, but natural language is notoriously difficult to process
automatically. Applied natural language processing -- also known as automated
content analysis and language engineering -- can provide partial solutions.
course will examine the state-of-the-art in applied NLP, with an emphasis on
how well the algorithms work and how they can be used (or not) in
applications. Topics will include text summarization, text mining, question
answering, information extraction, text categorization, author and genre
recognition, word sense disambiguation, and lexical and ontological acquisition,
and text analysis for social applications such as Blogs and social networks.
NOTE: Dan Klein's CS 294-5
is also being offered this term. Both courses
deal with statistical, corpus-based NLP. CS 294-5 will emphasize NLP models and
algorithms, while SIMS 290-2 will emphasize the applications of NLP