Recommendation techniques for Web search and social media

Recommenders aim to solve the information and interaction overload. A recommender system is a tool that identifies highly relevant items of interest for a user. In this thesis we aim to harness the information available through Web to build recommender systems. In particularwe study on a number of different recommendation problems: "correct tag recommendation", "query recommendation", "tweet recommendation", and "tourist points of interest recommendation". For each problem, we describe and evaluate effective solutions using novel efficient techniques.