Document Analysis COMP4650

Course overview

Course description

Processing of semi-structured documents such as internet pages, RSS feeds and their accompanying news items, and PDF brochures is considered from the perspective of interpreting the content. This course considers the document" and its various genres as a fundamental object for business, government and community. For this, the course covers four broad areas: (A) information retrieval, (B) natural language processing, (C) machine learning for documents, and (D) relevant tools for the Web. Basic tasks here are covered including content collection and extraction, formal and informal natural language processing, information extraction, information retrieval, classification and analysis. Fundamental probabilistic techniques for performing these tasks, and some common software systems will be covered, though no area will be covered in any depth.

Textbooks

The following reference books will be used.

• Introduction to Information Retrieval, C.D. Manning, P. Raghavan and H. Scutze, Cambridge University Press, 2008.
• Foundations of Statistical Natural Language Processing, C.D. Manning and H. Scutze, MIT Press, 1999.

Workload

Thirty one-hour lectures and six two hour tutorial/laboratory sessions.