Methods of Collective Intelligence in Exploratory Data Analysis: A Research Survey

DOI

10.2991/cnct-16.2017.1How to use a DOI?

Keywords

Computational Intelligence, Collective Intelligence, Exploratory Data Analysis, Data Science, Classification, Clustering, Outlier Detection, Data and Dimensionality Reduction, Metaheuristics.

Abstract

This study contains a brief presentation of the basic tasks for Exploratory Data Analysis (EDA), namely: classification, clustering, reduction of data dimensionality and number of data instances as well as detection of outliers. Herein, solutions to the aforementioned problems incorporating a wide range of computational intelligence algorithms, in particular procedures based on collective intelligence, are under consideration. Furthermore, the combination of metaheuristic algorithms with basic EDA procedures applied and verified within many domains of science, technology and engineering are being presented.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Piotr A. KOWALSKI
AU  - Szymon Lukasik
AU  - Piotr KULCZYCKI
PY  - 2016/12
DA  - 2016/12
TI  - Methods of Collective Intelligence in Exploratory Data Analysis: A Research Survey
BT  - Proceedings of the International Conference on Computer Networks and Communication Technology (CNCT 2016)
PB  - Atlantis Press
SP  - 1
EP  - 7
SN  - 2352-538X
UR  - https://doi.org/10.2991/cnct-16.2017.1
DO  - 10.2991/cnct-16.2017.1
ID  - KOWALSKI2016/12
ER  -