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CIS 8590: Topics in Computer Science -- Text Mining and Language Processing

Instructor: Alexander Yates

Course Description:

This course will give a broad overview of problems and techniques in natural language processing, and then move on to cover the latest research in selected topics. The overview part of the course will cover:
  • Morphology and Syntax: Stemming, part-of-speech-tagging, parsing, Hidden Markov Models, Conditional Random Fields.
  • Information Retrieval: Building indexes, data compression, the vector space model, language modeling.
  • Semantics and Information Extraction: Coreference, semantic role labeling, word sense disambiguation, building hierarchies of knowledge (ontologies).
The in-depth part of the course will focus on the latest research in semantics and information extraction. This part of the course will cover such techniques as pointwise mutual information, pattern-matching, bootstrapping, TF-IDF, distributional representations, and others.

Prerequisites:

Familiarity and basic level of comfort with probability and statistics is essential and will be assumed. Any of the following courses, or specific permission of the instructor, should be enough: CIS 8525, 8526, 8527, 9603, 9664.

Textbook:

None. We will read extensively from the research literature, which will be handed out in class, or links to the material will be provided online.



Announcements:

  • 2/4: Updated slides for HMMs and CRFs are posted, along with slides for week 3.
  • 1/20: Welcome to CIS 8590!