Keynote 1 - Francesco Ricci, Free University of Bozen-Bolzano, Italy

Computing Effective Recommendations for Tourists

Recommender systems have been introduced as information search and filtering tools for providing suggestions for items to be of use to a user. State of the art recommender systems mostly focus on the usage of data mining and information retrieval techniques to predict to what extent an item fits user needs and wants. But often they end up in making uninteresting suggestions especially in complex domains, such as tourism. In this talk, classical recommender systems ideas will be introduced and critically scrutinised in the attempt to better understand the role of observed and predicted choices and preferences. We will discuss some of the key ingredients necessary to build a useful recommender system. Hence, we will point out some limitations and open challenges for recommender systems research. We will also present a novel recommendation technique that leverages data collected from observation of tourists behaviour to generate more useful individual and group recommendations.

Francesco Ricci is full professor at the Faculty of Computer Science, Free University of Bozen-Bolzano. F. Ricci has established in Bolzano a reference point for the research on Recommender Systems. He has co-edited the Recommender Systems Handbook (Springer 2015), and has been actively working in this community as President of the Steering Committee of the ACM conference on Recommender Systems (2007-2010). He was previously (from 2000 to 2006) senior researcher and the technical director of the eCommerce and Tourism Research Lab (eCTRL) at ITC-irst (Trento, Italy). F. Ricci's research interests cover: machine learning, user modelling, recommender systems and ICT applications to travel and tourism. Francesco Ricci is author of approximately two hundred refereed publications and, according to Google Scholar, has H-index 57 and around 20,000 citations.

Keynote 2 - Brennan Lake, Cuebiq, USA

Location Intelligence for COVID-19 Response - building data collaboratives for COVID-19 research and public policy

What do public health agencies, big-box retailers, and complex-systems researchers have in common? They all use precise location-based data to gain insights into how COVID-19 is shaping human mobility, and how mobility data can reveal the impacts of response efforts on society. In this presentation, Cuebiq's Senior Director of Data for Good, Brennan Lake, will show how key decision makers across private, public and research sectors are using Cuebiq data to inform decision-making and drive positive outcomes in the fight against the COVID-19 pandemic.

Brennan Lake is the Senior Director of Research Partnerships & Data For Good at Cuebiq, where he is responsible for developing partnerships with research and humanitarian organizations to drive positive social impact through the novel use of location data. Prior to Cuebiq, Brennan was the Co-Director of The Technology Exchange Lab (TEL), a nonprofit organization that enables innovative technology solutions to problems of poverty. Prior to his work with TEL, Brennan spent four years living in Buenos Aires, Argentina, where he co-founded a SaaS platform that democratizes eCommerce for small businesses in Latin America. Outside of the office, Brennan is a social entrepreneurship mentor and board member of the Technology Exchange Lab, Inc. He holds a bachelor’s degree in Diplomacy and World Affairs from Occidental College and an MBA from Cornell University