“Call for
papers” del congreso IWINAC que se celebrará el 2019 en Almería, España.
Los proceeedings (memorias) del congreso se publican en “Lecture Notes in Computer Science” de la editorial Springer-Verlag.
"We would like to cordially invite you to submit a paper for IWINAC 2019 Special Session on Machine Learning Methods applied to Big Data Analysis, Processing and Visualization
Almeria, Spain - 3-7 June, 2019 http://www.iwinac.org/iwinac2019/
Aims:
The amount of data available every day is
not only enormous, but growing at an exponential rate. Over the last years
there has been an increasing interest in using machine learning methods to
analyse and visualize massive data generated from very different sources and
with many different features: social networks, surveillance systems, smart
cities, medical diagnosis, business, cyberphysical systems or media digital
data. This special session is designed to serve researchers and developers to
publish original, innovative and state-of-the art machine learning algorithms
and architectures to analyse and visualize large amounts of data.
This special session provides a platform
for academics, developers, and industry-related researchers belonging to the
vast communities of *Big Data*, *Machine Learning*, *Pattern Recognition*,
*Visualization*,*Media Digital Data*, and many others, to discuss, share
experience and explore traditional and new areas of Data analysis, processing
or visualization and machine learning combined to solve a range of problems.
The objective of the workshop is to integrate the growing international
community of researchers working on the application of Machine Learning applied
to Big Data analysis, processing and visualization to a fruitful discussion on
the evolution and the benefits of this technology to the society.
The topics of interest are those related
with big data, but we are particularly interested in candidates who have
conducted research in the theoretical or practical aspects of big data –
algorithms, machine learning, deep learning, statistical learning methods
applied to one or more domains – software engineering, media digital data,
bio-informatics, health care, imaging and video, social networks, natural
language processing and others. It can be identified by, but are not limited
to, the following subjects:
Healthcare and medical diagnosis
Social network modelling
Financial risk assessment
Marketing and E-commerce
Multimedia data mining
Visual surveillance
Application Systems for Big Visual Data
Understanding
Education data mining
Location big data mining
Intelligent transportation system
Web mining
Text mining
Sentiment analysis for social media
Network security
Smart cities
Smart government
Smart and cyberphysical devices
Approximate and randomized methods for
subspace learning, classification and clustering on Big Data
Nonlinear learning techniques
Distributed solutions for nonlinear big
data processing and analysis
Deep methods for representation learning,
clustering and classification on Big Data
Unsupervised and semi-supervised methods
for Big Data
Data-driven techniques for representation
learning, clustering and classification on Big Data
Big media data on the web and social
networks
Big multimedia data (signal, 2D/3D image,
video) analysis in medicine, science and engineering
Semantic visual analysis: human activity
recognition, face/facial expression recognition, scene understanding, object
detection and tracking, saliency detection
Big Media Data applications, including
media data summarization, post-processing, search and retrieval, video
surveillance, robotics
Big Media Data description, visualization
and analytics
Big cross-media analytics
Important dates:
Paper Submission Deadline:
January 31, 2019
Paper acceptance notification date:
April 30, 2019
Conference:
June 3-7, 2019
Chairs:
José García-Rodríguez -University of
Alicante (Spain)
Enrique Domínguez – University of Malaga
(Spain)
Jaime Oswaldo Salvador Meneses - Universidad Central del Ecuador (Ecuador)
Zoila Ruiz - Universidad Central del
Ecuador (Ecuador)
Contact:
Email: jgarcia@dtic.ua.es
Main Conference webpage: http://www.iwinac.org/iwinac2019/
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