Titlebook: Machine Learning and Knowledge Extraction; First IFIP TC 5, WG Andreas Holzinger,Peter Kieseberg,Edgar Weippl Conference proceedings 2017

冒號(hào)

DEAWL

Complement

On the Challenges and Opportunities in Visualization for Machine Learning and Knowledge Extraction: professional and personal experience. The unprecedented increase in the amount, variety and the value of data has been significantly transforming the way that scientific research is carried out and businesses operate. Within data science, which has emerged as a practice to enable this data-intensiv

秘密會(huì)議

Quantitative Externalization of Visual Data Analysis Results Using Local Regression Modelsccessfully combine the benefits of both methodologies. In interactive data exploration and analysis workflows, we need successful means to quantitatively externalize results from data studies, amounting to a particular challenge for the usually qualitative visual data analysis. In this paper, we pro

FLACK

Analysis of Online User Behaviour for Art and Culture Eventsave exploited this as a source for understanding the user behaviour and profile in various settings. In this paper, we address the specific problem of user behavioural profiling in the context of cultural and artistic events. We propose a specific analysis pipeline that aims at examining the profile

Panacea

吞噬

mucous-membrane

insomnia

Analysis of Online User Behaviour for Art and Culture Events modeling, user clustering, and prediction of interest. We show our approach at work for the monitoring of participation to a large-scale artistic installation that collected more than 1.5 million visitors in just two weeks (namely ., by .). We report our findings and discuss the pros and cons of the work.

踉蹌

Managing Complexity: Towards Intelligent Error-Handling Assistance Trough Interactive Alarm Flood Rethe implementation of a first vertical prototype for such a system. We consider this prototype as a first artifact to be discussed by the research community and aim towards an incremental further development of the system in order to support humans in complex error situations.