Recommender systems 2016
This course is focused on data mining approaches for analysis and modeling of user behavior online. The course touches upon three main topics including modeling user preferences and recommender systems, analysis of social media discourse and data mining for location-based social networks. The material of the course is based on a variety of the recent research results in the analysis of online datasets (e.g., Twitter, Foursquare, BBC iPlayer, Pinterest, etc.) and the state-of-the-art data mining techniques in the field are discussed. The basic knowledge of statistical analysis and supervised machine learning is recommended but not required to comprehend this course.
Dr. Dmytro Karamshuk
A data scientist at King’s College London
Affiliation: King’s College London, United Kingdom
Data Scientist at King’s College London focused on machine learning approaches to modeling behavior of online users. Previously worked on studying watching patterns of TV-streaming users (e.g., BBC iPlayer), mining geo-location social networks (e.g., Foursquare) and predicting user behavior in Pinterest and Twitter.
Fields of interests: urban data mining, video networks, social media analysis, recommender systems.