Special Session Proposal for IDEAL2017

Learning from Big Data, Streaming Data and Heterogeneous Multi-Source Data: Algorithms, Models and Applications

Prof. Ming Yang, Nanjing Normal University, China. Email: myang@njnu.edu.cn

Prof. Yang Gao, Nanjing University, China. Email: gaoy@nju.edu.cn

Prof. Wensheng Zhang, Institute of Automation of Chinese Academy of Sciences, China. Email: wensheng.zhang@ia.ac.cn

Dr. Wanqi Yang, Nanjing Normal University, China. Email: yangwq@njnu.edu.cn

In our real life, big data are usually continuously collected from various sources (e.g., websites, devices, databases, etc). Thus, they are in form of streaming and heterogeneous multi-source data. The learning and mining techniques to obtain the valuable information from such big data, are becoming more and more significant, which can help improve our life. However, the state-of-the-art techniques are undesirable to deal with the issue. Recently, related learning theories and techniques of big data analysis have attracted much attention from both academic and industrial communities. Several existing methods have been successfully presented in many applications, e.g., social network, e-business, information retrieve, multimedia analysis, etc. The special session on “learning from big data, streaming data and heterogeneous multi-source data: algorithms, models and applications” will focus on the latest developments about learning theories and techniques to deal with streaming data and heterogeneous multi-source data. Specifically, it is welcome to discuss about several novel methods to address (1) efficient learning algorithms for heterogeneous multi-source data, (2) fast online learning algorithms for streaming data and (3) their applications in computer vision (e.g., medical image analysis, face recognition, person re-identification, etc).

Finance and Data Mining

Peter Mitic, Banco Santander UK and University College London, UK (peter.mitic@virgin.net)

Ángel Arcos-Vargas, University of Seville, Spain (aarcos@us.es)

Fernando Núñez Hernández , University of Seville, Spain (fnunezh@us.es)

Antonio J. Tallón-Ballesteros, University of Seville, Spain (atallon@us.es)

The topics of interest for this session include, but are not limited to:
- Finance
- Data mining
- Economical prediction
- Stock-market analysis
- Reputation on finance
- Economist intelligence
- Money laundering avoidance
- Early detection of tax evasion
- Technological issues affecting the economy of a company
- Big numbers in the economy of a country
- Business intelligence

Metaheuristics for data engineering

Milan Tuba, John Naisbitt University, Belgrade, Serbia and State University of Novi Pazar, Novi Pazar, Serbia (tuba@ieee.org)

Antonio J. Tallon-Ballesteros, University of Seville, Spain (atallon@us.es)

This special session goals to collect contemporary approaches in the context of metaheuristics focusing on applications in real problems or simulated scenarios as a first step. It is very common in science and engineering the necessity of reaching an approximated solution in a reasonable amount of time. As soon as the scale of some problems is slightly increased exact solutions are no longer possible.
    The topics of interest for this session include, but are not limited to:
- Metaheuristics: theory and foundations
- Bio-Inspired computation
- Memetic algorithms
- Evolutionary computing
- Genetic algorithms
- Evolutionary programming
- Evolutionary strategies
- Swarm intelligence
- Particle swarm optimization
- Ant colony optimization
- Stochastic diffusion search
- Artificial immune systems
- Bird flocking
- Cuckoo Search
- Cultural algorithms
- Artificial bee colony optimization
- Fireworks algorithm
- Harmony search

Crisp and fuzzy intelligent systems

Antonio J. Tallón-Ballesteros, University of Seville (Spain). email: atallon@us.es

Luís Correia, University of Lisbon (Portugal)

Juan Rada-Vilela, FuzzyLite Limited, Wellington (New Zealand)

Hujun Yin, The University of Manchester (UK)

This special focuses on the application/research of intelligent approaches to any kind of scenerario. Currently, the artificial intelligence is tied to our daily life. Thus, the presentation of works facing theoretical issues and/or applications is welcomed. The topics of interest include, but are not limited to:
- Agents
- Applications
- Artificial vision
- Business intelligence
- Business to business
- Computational models
- Contemporary technologies for modern intelligent systems
- Crisp intelligent systems
- Crisp logic systems
- Databases and data centers
- Distributed artificial intelligence
- Expert systems
- Fuzzy logic systems
- Granular computing
- Grey systems
- Hybrid systems
- Intelligent systems
- Internet of things
- Innovative arquitectures of Intelligent systems
- Joint technologies (classical, fuzzy, neural, soft matters)
- Knowledge-based systems
- [L]arge-scale systems
- Machine learning
- Meta-learning
- Natural language processing
- Neural systems
- Optical computing
- Parallel approaches
- Pattern recognition
- Probabilistic reasoning
- Quantum computing
- Remote systems
- Resolution enhacement
- Robust face and image recognition
- Secure systems
- Smart cities
- Soft computing
- Time series modelling
- Virtual reality
- Web intelligence