This course focuses on cutting-edge research topics in information retrieval and related applications. It covers recent research on subjects such as retrieval models for unstructured text data and semi-structured data, information filtering, personalized information retrieval, federated search, multimedia information retrieval, private-preserved information retrieval, information extraction, cross-lingual text processing, biomedical literature mining, etc. These applications involve a combination of techniques of information retrieval, machine learning, natural language processing and data mining. For more information, please see http://www.cs.purdue.edu/homes/lsi/CS690I_Course_Description.pdf

Homepage	http://www.cs.purdue.edu/homes/lsi/CS690I_Course_Description.pdf
Usually Offered:	Spring
Credit:	3 hours (class)
Prerequisite:	CS 590I is preferred or a reasonable knowledge of basic models/algorithms in information retrieval
University Catalog:	CS 690I
Schedule:	Spring 2007 Instructor: Luo Si