MATEC Web Conf.
Volume 210, 201822nd International Conference on Circuits, Systems, Communications and Computers (CSCC 2018)
|Number of page(s)||6|
|Published online||05 October 2018|
Distributed data mining systems: techniques, approaches and algorithms
Faculty of Applied Informatics, Tomas Bata University in Zlin, Czech Republic
2 Pomorska Academia in Slupsk, Poland
* Corresponding author: firstname.lastname@example.org
Nowadays, we are living in the midst of a data explosion and seeing a massive growth in databases so with the wide availability of huge amounts of data; necessarily we are become in need for turning this data into useful information and knowledge, where Data mining uncovers interesting patterns and relationships hidden in a large volume of raw data and big data is a new term used to identify the datasets that are of large size and have grater complexity. The knowledge gained from data can be used for applications such as market analysis, customer retention and production control. Data mining is a massive computing task that deals with huge amount of stored data in a centralized or distributed system to extract useful information or knowledge. In this paper, we will discuss Distributed Data Mining systems, approaches, Techniques and algorithms to deal with distributed data to discover knowledge from distributed data in an effective and efficient way.
© The Authors, published by EDP Sciences, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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