INTRODUCTION TO TEXT MINING

LIS 768

Learn and apply introductory technology-related concepts and skills to plan, implement and assess data-driven projects in the humanities, social sciences and other fields. Topics include identifying relevant existing digitized materials, web scraping, text encoding, topic modeling, mapping, social network analysis and other approaches for collecting, analyzing and visualizing data.

INFOSYS 723

An introduction to text mining and natural language processing for business applications. Provides an overview of text data and steps to make it usable and approaches for making text data useful in descriptive and predictive analytics applications. Topics include representation approaches, topic modeling, and an overview of key applications of natural language processing, such as chatbots and recommender systems.

COMPSCI 769

Develop algorithms and mathematical models for natural language processing tasks, including text categorization, information retrieval, speech recognition, machine translation, and information extraction. Focus is on the state-of-the-art computational techniques as they are applied to natural language tasks. Students are strongly encouraged to have knowledge of introductory artificial intelligence (e.g.,COMP SCI 540).

CURRIC/EDPSYCH/LIS 803

Provides a broad overview of ways of formulating and investigating novel questions with tools from educational data mining and learning analytics including social network analysis, natural language processing, Markov modeling, Bayesian inference, and agent-based modeling.

GENBUS 891

An introduction to text mining and generation for business applications. Includes an overview of text data and approaches for making text data useful for descriptive and predictive analytics. Also, includes key applications of natural language processing, such as chatbots and recommender systems.