Limitations, Effectiveness and Misuse of Data Mining

DATA MINING
Data mining
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DATA MINING
Table of Contents
Introduction......................................................................................................................................2
Review of papers on data mining....................................................................................................2
Effectiveness of data mining approaches........................................................................................6
Misuse of data mining.....................................................................................................................6
Conclusion.......................................................................................................................................7
Reference.........................................................................................................................................8
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DATA MINING
Introduction
The foremost determination of this unit of the paper is to focus on the limitations of data
mining, the effectiveness of data mining and the misuse of data mining. The paper includes six
scholarly journals; each journal is described on the basis of its strength, weakness and its
relevance to the topic. The paper also focuses on the effectiveness of the data mining approaches.
Review of papers on data mining
Buczak, A. L., & Guven, E. (2016). A survey of data mining and machine learning methods
for cyber security intrusion detection. IEEE Communications Surveys &
Tutorials, 18(2), 1153-1176.
Recent studies indicated that lots of emerging methodologies used in the data mining
process. The writer of this journal highlighted the different kinds of data sets considering data
mining such as the packet level data and net flow data and public set data. The main strength of
this document is that it guides the readers to know about all the potential risks associated with
data mining but the one the limitations of this journal is that it does not discusses the issue
related to the emerging methodologies which may have an impact of the overall process. This
resource gives in-depth knowledge about artificial neutral networks, fuzzy association rules,
clustering and Bayesian networks.
Wu, X., Zhu, X., Wu, G. Q., & Ding, W. (2014). Data mining with big data. IEEE
transactions on knowledge and data engineering, 26(1), 97-107.
A recent study conducted on data mining stated the problems related to data mining such
as the networking problems, data storage problems and data collection challenges. The journal
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