Conceptualization of Social Big Data
Nowadays, much of the social interaction is mediated by the various forms of the social online services. This has led to emergence of extensive amounts of human-generated data with the rich semantics and large potential for diverse personal, commercial and societal applications. In this presentation, we will provide the conceptualization of Social Big Data from three perspectives: at first we will define taxonomy of data types for Social Media as the main source of data. In the second perspective, we will conceptualize Data Analysis methods gaining and analysing knowledge from the source data. The third perspective will incorporate Big Data research area as a main processing paradigm.
Peter Bednár, PhD, is a senior researcher at the Faculty of Electrical Engineering and Informatics, Technical University of Kosice, Slovakia. He was awarded a PhD in Artificial Intelligence at the Faculty of Electrical Engineering and Informatics of the Technical University of Kosice in 2010. His experiences are tightly connected with research in knowledge management, text and data mining, natural language processing and distributed software architectures for Big Data processing. He has participated in several EU R&D projects, e.g. H2020 Monsoon, Picaso, FP7 Urban Sensing, Adapt4EE, SPIKE, FP6 Access e-Gov, KP-Lab, FP5 Webocracy.
SMAP & UMAP Shared talk
Paul De Bra
After twenty-five years of user modeling and adaptation…what makes us UMAP?
ACM UMAP 2017 is the 25th conference on User Modeling, on Adaptive Hypermedia, or on both together (since 2009). The research has actually been going on for more than 25 years as initially there was a conference only every two years. This keynote offers both reflection on the past and outlook into the future, with the burning question: What makes us UMAP? We perform research on modeling users (individuals as well as groups), not just for fun but to use these models for recommendations and for adaptation. That’s not unique to us. In recommender systems analyzing user behavior is needed in order to give better and better recommendations, and likewise an area like educational data mining analyzes how learners study in order to best guide them to new learning material or followup courses. With analysis of social networks and website adaptation we step into the same research area that is covered by the hypertext community. If all of this is “us” but “not just us”, where is our identity?
One key characteristic of User Modeling is our quest to come up with understandable user models, or scrutable as Judy Kay coins them. The same is true for the adaptation: we strive to understand why certain adaptation happens or why a certain recommendation is given. UMAP research is not complete if we cannot understand the chain that leads from user action to (a perhaps much later) system reaction. As we move from expert-driven adaptation towards data-driven adaptation the problem of understanding the user-modeling-to-adaptation process is becoming harder and harder. But we need this understanding to ensure that adaptation continues to adapt in the right way under continuously changing circumstances (both in what we adapt and in the users and context we adapt to). We need the understanding also to prevent continuous adaptation from creating lter bubbles and to avoid creating the illusion that the recommendations will always be “right” because of the “wisdom of the crowd” principle.
One key element has always been missing from UMAP, and this keynote will that void: we need to practice what we preach. Therefore, the conference proceedings will only contain this abstract, but there will be a real paper to go with this abstract. That paper cannot be printed because it is adaptive.
Prof. dr. Paul De Bra was is Professor in the Department of Computer Science at the Eindhoven University of Technology (TU/e) and chair of the Web Engineering group.
Paul De Bra started his university life at the University of Antwerp, Belgium, where he first obtained a master degree in Mathematics, as well as a teaching qualification, in 1981. He continued his study towards a doctorate under the guidance of prof. dr. Jan Paredaens and graduated in 1987, with a thesis on “Horizontal Decomposition in the Relational Database Model”.
During 1988 and 1989 he was a post-doctoral researcher at AT&T Bell Laboratories in Murray Hill, New Jersey, studying principles and technology for WYSIYWYG interfaces for document processing. He also learned about the then upcoming research field of hypertext.
He joined the TU/e in December 1989, first as an associate professor in databases, and since August 1996 as a full professor and chair of the Information Systems group, out of which the Web Engineering group emerged.
Paul De Bra is especially known for research on adaptive hypermedia and adaptive Web-based systems. He initiated both theoretical research and practical development, the theory leading to the most cited reference models in adaptive hypermedia, AHAM and GAF, and the development leading to the most cited and used adaptive hypermedia systems AHA! and GALE. His largest project was GRAPPLE, an EU FP7 Technology-Enhanced Learning project to support life-long learning through the use of a user-modeling and adaptation platform that allows users to be helped by adaptation even when moving between different learning systems and providers. He also initiated the CHIP project on personalization in cultural heritage, and contributed to many other studies and development, most recently also on adaptation for autistic students moving from high-school to the university, in the Autism&Uni project.
Besides his teaching, research and grant acquisition tasks at the TU/e he served in a number of additional functions. He was a part-time professor at the University of Antwerp from 1987 to 2007, is scientific director of the dutch research school SIKS on Information and Knowledge Systems, President of User Modeling Inc., and at the TU/e he is Graduate Program Director of Computer Science and representatitive of the TU/e in the World Wide Web Consortium.