Document Analysis

Note: Non-DADAN/MADAN students wanting to enrol in the non-standard session offerings are required to seek approval from their Program Convener. Processing of semi-structured documents such as internet pages, Really Simple Syndication (RSS) feeds and their accompanying news items, and Portable Document Format (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: 1. Information Retrieval (IR), 2. Natural Language Processing (NLP), 3. Machine/Deep Learning (M/DL) for documents, and 4. relevant tools for the Web. Basic tasks here are covered, including content collection and extraction, formal and informal NLP, Information Extraction (IE), IR, 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. (The older version: This course considers the “document” and its various genres as a fundamental object for business, government and community, such as web pages, social media feeds, news items, and PDF brochures. The goal is to introduce concepts and hands-on tools for automated understanding of large amounts of text. 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. Tasks include 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 great depth.)