CURRENT RESEARCH TOPICS SEMINARS by IIT Members

Recommender Systems: From classical to Point-of-Interest recommendation

By Pablo Sánchez Pérez

Since the emergence of the Internet and the spread of digital communications throughout the world, the amount of data stored on the Web has been growing exponentially. In this new digital era, a large number of companies have emerged with the purpose of filtering the information available on the web and provide users with interesting items. The algorithms and models used to recommend these items are called Recommender Systems. These systems are applied to a large number of domains, from music, books, or movies to dating or Point-of-Interest (POI), which is an increasingly popular domain where users receive recommendations of different places when they arrive to a city.

This seminar will provide an introduction to both the traditional and the POI recommendation problem, emphasising the importance of contextual information (temporal, sequential, geographical, etc.) in making recommendations to users. Besides, the seminar will also introduce to some of the algorithms that are frequently used in the recommender systems domain and explain some of the metrics that are applied in the field to measure the quality of the recommendations produced to users.