Methods of Collective Intelligence in Exploratory Data Analysis: A Research Survey
Piotr A. KOWALSKI, Szymon Lukasik, Piotr KULCZYCKI
Piotr A. KOWALSKI
Available Online December 2016.
- https://doi.org/10.2991/cnct-16.2017.1How to use a DOI?
- Computational Intelligence, Collective Intelligence, Exploratory Data Analysis, Data Science, Classification, Clustering, Outlier Detection, Data and Dimensionality Reduction, Metaheuristics.
- 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.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
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 - https://doi.org/10.2991/cnct-16.2017.1 ID - KOWALSKI2016/12 ER -