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A comprehensive review on privacy preserving data mining

Overview of attention for article published in SpringerPlus, November 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (88th percentile)
  • High Attention Score compared to outputs of the same age and source (90th percentile)

Mentioned by

policy
1 policy source
twitter
1 X user
patent
2 patents
facebook
1 Facebook page
wikipedia
1 Wikipedia page
googleplus
1 Google+ user

Citations

dimensions_citation
79 Dimensions

Readers on

mendeley
206 Mendeley
Title
A comprehensive review on privacy preserving data mining
Published in
SpringerPlus, November 2015
DOI 10.1186/s40064-015-1481-x
Pubmed ID
Authors

Yousra Abdul Alsahib S. Aldeen, Mazleena Salleh, Mohammad Abdur Razzaque

Abstract

Preservation of privacy in data mining has emerged as an absolute prerequisite for exchanging confidential information in terms of data analysis, validation, and publishing. Ever-escalating internet phishing posed severe threat on widespread propagation of sensitive information over the web. Conversely, the dubious feelings and contentions mediated unwillingness of various information providers towards the reliability protection of data from disclosure often results utter rejection in data sharing or incorrect information sharing. This article provides a panoramic overview on new perspective and systematic interpretation of a list published literatures via their meticulous organization in subcategories. The fundamental notions of the existing privacy preserving data mining methods, their merits, and shortcomings are presented. The current privacy preserving data mining techniques are classified based on distortion, association rule, hide association rule, taxonomy, clustering, associative classification, outsourced data mining, distributed, and k-anonymity, where their notable advantages and disadvantages are emphasized. This careful scrutiny reveals the past development, present research challenges, future trends, the gaps and weaknesses. Further significant enhancements for more robust privacy protection and preservation are affirmed to be mandatory.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 206 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Colombia 1 <1%
Unknown 205 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 45 22%
Student > Master 23 11%
Student > Bachelor 14 7%
Researcher 11 5%
Lecturer 10 5%
Other 29 14%
Unknown 74 36%
Readers by discipline Count As %
Computer Science 86 42%
Engineering 11 5%
Business, Management and Accounting 4 2%
Mathematics 4 2%
Social Sciences 4 2%
Other 14 7%
Unknown 83 40%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 14. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 October 2023.
All research outputs
#2,440,388
of 24,657,405 outputs
Outputs from SpringerPlus
#142
of 1,864 outputs
Outputs of similar age
#34,106
of 288,174 outputs
Outputs of similar age from SpringerPlus
#13
of 120 outputs
Altmetric has tracked 24,657,405 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,864 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one has done particularly well, scoring higher than 92% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 288,174 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 88% of its contemporaries.
We're also able to compare this research output to 120 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 90% of its contemporaries.