Università Roma Tre

The course will examine various methods for the design, implementation, and testing of adaptive systems on the Web, realized through Artificial Intelligence techniques. Particular attention will be paid to Information Retrieval systems, such as search engines, and to new and emerging technologies suitable for realizing the next generation of intelligent and personalized search tools. We will study classical retrieval models, such as the vector space model and probabilistic models, document ranking techniques, as well as the PageRank algorithm adopted by Google. Algorithms of Machine Learning in Information Retrieval will be addressed, including techniques for Sentiment Analysis, User Modeling methods needed for developing personalized research tools and recommender systems, identifying and analyzing online communities, and social networks (such as Facebook and Twitter). Finally, statistical methods for the experimental evaluation of the aforementioned systems will be described.

Lectures will cover topics dealt with in scientific papers and reference texts.
The teacher will make available the slides from the lectures through the course website. Those slides will be self-contained, that is, written in such a way as not to require the consultation of further texts for passing the exam.