University of Naples Federico II, Italy
Title: Multimedia Recommender Systems: Approaches and Challenges
Abstract: Nowadays, multimedia data is surely one of the most popular and pervasive information and communication media that accompanies us in almost every walks of life. They allow fast and effective communication and sharing of information about peoples' lives, their behaviors, works, interests, and they are also the digital testimony of facts, objects, and locations and have become an essential component of Online Social Networks and represent the core element of Multimedia Streaming Platforms. One of the most challenging research topics concerning multimedia data is surely to provide users with recommendation facilities that are able to suggest content of interest within very large collections of data. Recently, traditional recommendation strategies have been extended to handle multimedia data and the related features giving rise to the so-called Multimedia Recommender Systems. In this presentation, we will discuss their foundations and the different types of approaches that characterize them, referring to some of the research works that have distinguished the main literature in the field over the past decade. Finally, future lines of research and main open challenges will be identified ,by looking at the problems associated with the ever-increasing volume and complex nature of multimedia data that must be analyzed.
Bio: Vincenzo Moscato is an Associate Professor at the Electrical Engineering and Information Technology Department of University of Naples Federico II, where he is the owner of "Database Systems" and "Big Data Engineering" teachings for the bachelor and master's degree programs in Computer Engineering, respectively. From 2009 to 2015, he was Assistant Professor at the Computer Science and Systems Department of the same University, where he was one of the leaders of PRIAMUS (Pattern Recognition, Image Analysis and Multimedia Systems), leading several research activities mainly concerning Multimedia Recommender Systems and Event Detection on multimedia streams, in collaboration with George Mason University and University of Maryland. Currently, he is one of the leaders of PICUS (Pattern and Intelligence Computation for mUltimedia Systems) departmental research group and the Scientific Coordinator of the University of Naples unit within the Big Data National Laboratory of CINI (National Research Consortium on Computer Science). His current research activities lay in the area of Big Data Analytics, Artificial Intelligence and Multimedia Social Network Analysis. In addition, he is the Co-founder of the Academic Spin-off Data JAM srl and an associate of DATALIFE srl startup and won an International Award by Oracle Corporation for the "Knowledge graphs for next-generation health science applications" project. He was in the Program Committee (PC) of a plethora of international and top-ranked conferences, and the PC chair of a dozen of IEEE international conferences. He served as reviewer in numerous international journals, including some of the most important journals concerning Multimedia, Knowledge and Data Engineering and Artificial Intelligence topics, and currently he is in the editorial boards of several international journals, including, among others, "Expert System and Applications" and "Intelligent Information Systems''. Finally, he was an author of more than 200 publications in international journals, conference proceedings and book chapters. About 70 of such publications are available on top-ranked journals (Q1 and Q2 from SCIMAGO ranking) or included in Proceedings of top-ranked conferences.
Technical University of Darmstadt, Germany
Title: MEX AND THE CITY – appropriating media and applications for city-scale use with mobile extended reality (MEX)
Abstract: Smartphones are our ubiquitous companions, and we often use them on the go, which for an increasingly large portion of the world's population means: when we're out and about in cities. But the way we interact with smartphones is not mobile-friendly in many ways. Augmented—and interestingly, also Virtual—Reality technologies promise to merge the physical and digital experience for our senses and to revolutionize the way we interact in and with the cities of the future, and with countless applications. Thereby, AR and VR will evolve from two distinct technologies to a continuum, which we shall denote as MEX.
Both MEX interaction and MEX immersion must be considerably improved in order to provide a better user experience along with the analog-digital convergence. Most interestingly, a new multimedia content type may play a key role in this development, characterized as "urban mobile 4D situated media" and simply coined as "4D City" during the talk.
The talk will place the vision of urban MEX interaction in the perspective of the evolution of human-computer interaction (HCI), describe the key development steps towards this vision and a number of contributions of the presenter's research lab to these steps. The novel content type "4D City" will be introduced and the necessary processing pipeline will be discussed along with insights into the state of mastery of the pipeline steps.
Bio: Max Mühlhäuser is a full professor at Technical University of Darmstadt and head of the Telecooperation Lab. He holds key positions in several large collaborative research centers and is leading the Doctoral School on Privacy and Trust for Mobile Users. He and his lab members conduct research on Human Computer Interaction, the future Internet, Intelligent Systems, and Cybersecurity including Privacy & Trust. Max founded and managed industrial research centers, and worked as either professor or visiting professor at universities in Germany, the US, Canada, Australia, France, and Austria. He published over 700 peer-reviewed articles and is a member of acatech, the German Academy of the Technical Sciences. Max was and is active in numerous conference program committees, as organizer of several annual conferences, and as a member of editorial boards or a Guest Editor for journals such as ACM IMWUT, ACM ToIT, Pervasive Computing, ACM Multimedia, and Pervasive and Mobile Computing.