DATA 565 Web Data Science
Data scientific methods and techniques for uncovering information from web user behavior. Topics may include web log cleaning and filtering, server identification, feature derivation, bot identification, de-spidering, user identification, heuristic methods, error handling, session identification, path completion, explaining why users leave the website, identifying anomalous user behavior, basket transformations, estimating last-page duration, exploratory data analysis and modeling for web analytics, including clustering, association, and classification.
Credits
4
Prerequisite
DATA 511 or permission of department chair.