There were around 150 participants from worldwide. Regarding submissions, there were 226 abstracts which resulted in 171 final submissions in total. 539 reviews were submitted for those papers and 42 out of 142 research papers have been accepted. Based on further quality assessment, the organizers also divided 42 papers into long presentations (17.3%) and short presentations for presentations during the conference.
Keynotes:
The first keynote was given by Chris Welty from Google research. He talked about how current AI systems are losing information with one label ground truth for training themselves (e.g, a song might be in different genres or not in the options you provided for getting ground truth data with a survey). He pointed out current simplified world for AI, which consists of black and white, while the reality is much complex. To achieve better ground truth labeling, he also introduced solutions such as using the wise crowd with diversity-enabled labeling for training AI systems.
The second keynote was given by Francesca Rossi from IBM research. She talked about AI has the capabilities to make sense of the huge volume of data (text, images, videos, etc.) that surrounds us in our everyday private and professional life, and to transform it into knowledge to be exploited to make better and more informed decisions that could help solving global societal problems such as those in healthcare, transportation, and climate. To achieve these goals, and in order to fully exploit the potential of AI, we need to build intelligent machines that behave ethically and create symbiotic partnerships with humans. So rather than considering/making AI for Decision Making Systems, we need to consider/make it as Decision Support Systems.
The conference sessions are very diverse, from data management to NLP as well as Entity Recognition, Crowdsourcing, ontology related topics etc.
My presentation:
I presented a User Modeling work considering different dimensions studied in the literature for investigating their synergetic effect on User Modeling.
EKAW2016 - Interest Representation, Enrichment, Dynamics, and Propagation: A Study of the Synergetic Effect of Different User Modeling Dimensions for Personalized Recommendations on Twitter from GUANGYUAN PIAO
The organizers also did a good job on proceedings, which were available before the conference:
The organizers also did a good job on proceedings, which were available before the conference: