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Andreas Holzinger <[log in to unmask]>
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Andreas Holzinger <[log in to unmask]>
Tue, 9 Apr 2013 08:57:02 +0200
text/plain (105 lines)
Call for Papers
Special session Human-Computer Interaction and Knowledge Discovery
at CD-ARES 2013, September 2-6, Regensburg, Germany

One of the grand challenges in our networked world are the large, 
complex, and often weakly structured data sets. These increasingly 
monstrous amounts of data require new, efficient and user-friendly 
solutions for knowledge discovery. This challenge is most evident in the 
biomedical domain: the trend towards personalized medicine has resulted 
in an explosion in the amount of generated biomedical data.

The ultimate goal of the task force HCI-KDD is to combine the best of 
two worlds: Human–Computer Interaction (HCI), with emphasis on human 
intelligence, and Knowledge Discovery from Data (KDD), dealing with 
computational intelligence.

The cross-domain integration and appraisal of different fields provide 
an atmosphere to foster different perspectives and opinions; it will 
offer a platform for novel ideas and a fresh look on the methodologies 
to put these ideas into practice.

This special session is organized in the context of the CD-ARES 2013, 
September, 2-6, 2013, Regensburg, Germany. CD stands for Cross-Domain. 
The mission is to bring together researchers from diverse areas in an 
highly inter-disciplinary manner, to stimulate fresh ideas and encourage 
multi-disciplinary work.

Accepted papers will be published in the conference proceedings by 
Springer as a volume of the series of Lecture Notes in Computer Science 
(LNCS). It is planned to select best papers and to invite to expand 
their contributions integrating the comments during the session in BMC 

Some hot topics include but are not limited to …

* … Graph-based Knowledge Discovery (e.g. Knowledge Discovery with graph 
entropy, biological networks, etc.)
* … Structural Graph Analysis (e.g. in Biology, Systems Biology, 
Medicine and Image Analysis, etc.)
* … Methods for Structural Network Analysis (e.g. graph measures and 
properties thereof, information-theoretic techniques such as entropy, etc.)
* … Knowledge Discovery from complex networks (e.g. large social 
networks, large biomedical data, protein-protein networks, epigenetics 
data etc.)
* … Interactive Content Analytics from “unstructured” text data (e.g. 
computational topology in text mining, text analytics, NLP, linguistics 
* … Big Data Analytics methodologies, methods, approaches and tools 
(e.g. Hadoop, R, RStudio, Rapid Miner, KNIME, ELKI, etc.  )
* … Multimedia Data Mining & Knowledge Discovery from multimedia data 
(e.g from the biomedical informatics domain etc.)
* … Swarm Intelligence (collective intelligence) and collaborative 
Knowledge Discovery/Data Mining/Decision Making
* … Intelligent, interactive, semi-automatic, multivariate Information 
Visualization and Visual Analytics (e.g. in the life sciences etc.)
* … Interactive multimedia Data Exploration and Sensemaking
* … Time-Oriented Data and Information (e.g. longitudinal data, complex 
noisy time series, entropy methods, …)
* … Novel Search User Interaction Techniques (supporting human 
intelligence with computational intelligence)
* … Future Knowledge Discovery Techniques (Note: science fiction of 
today is science fact of tomorrow)
* … Modeling of Human Discovery and exploration Behavior and 
Understanding Human Information Needs
* … Knowledge Discovery methods and methodologies (e.g. Support Vector 
Machines, Boltzmann machines, Evolutionary computing …)
* … Topological Data Analyis (e.g. in images, biomed data, medical 
diagnostics, clinical assessment, …)
* … Special HCI-KDD solutions in the biomedical domain (e.g. 
bioinformatics, genome analysis, genetics, epigentics, evolution, …)
* … Practical HCI-KDD solutions in the hospital (e.g. content analytics 
in business enterprise hospital data, …)

We are looking forward to your submission,
best regards
Andreas Holzinger & Matthias Dehmer

Science is to test ideas -
Engineering is to bring these ideas into Business
Assoc.Prof.Dr.Andreas HOLZINGER, PhD, MSc, MPh, BEng, CEng, DipEd, MBCS
Head Research Unit Human-Computer Interaction for Medicine and Health
Institute for Medical Informatics, Statistics and Documentation (IMI)
Medical University Graz (MUG)
Auenbruggerplatz 2/V, A-8036 Graz (Austria)
Phone: ++43 316 385 13883, Fax: ++43 316 385 13590
Enjoy Thinking. Taming Information. Support Knowledge.

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