BUZZ SESSION 3: DATA MINING by

BUZZ SESSION 3: DATA MINING by https://padlet.com/nilamnur/21bshxee24s9 MANB1143 FT01&FT02 en-us 2017-04-24 23:32:16 UTC 2026-01-18 11:26:11 UTC hello@padlet.com QUESTION nilamnur https://padlet.com/nilamnur/21bshxee24s9/wish/167985101 •Group Discussion

•Identify what are the privacy issues in data mining?

•How do you think the discussion between privacy and data mining will progress? Why?

•What are the most common myths about data mining?

]]> 2017-04-24 23:33:45 UTC https://padlet.com/nilamnur/21bshxee24s9/wish/167985101 Sharida & Yee Fang https://padlet.com/nilamnur/21bshxee24s9/wish/169066126
1. Privacy issues in data mining involve concerns about privacy focus both on actual projects proposed, as well as concerns about the potential for data mining applications to be expanded beyond their original purposes.

2. Both privacy and security are politically popular areas of concern, with growing public awareness and activism in the U.S., Europe, and in many other countries. The privacy issues will continuously being debate due to its strong affiliation with data mining, both are coexisted. However, the usefulness of information and knowledge gained via data mining is undeniable. Therefore, the temptation to legislate and regulate to protect the public may outweigh the consequences of restricting both online and offline commerce. On the other hand, the burden is on business to show where federal legislation is necessary to enhance electronic commerce, with clear benefits and consumer protections. Finally, elected and public officials should be informed of the costs and consequences to consumers, businesses, and the economy of leg

3. Myths and misconceptions about data mining are as follows:

i. Data mining is all about algorithms
ii. Data mining is all about predictive accuracy
iii. Data mining requires a data warehouse
iv. Data mining is all about vast quantities of data
v. Data mining should be done by a technology expert
vi. Neural networks are opaque and consequently useless – an over-simplistic view of data mining

Ref: https://www.witpress.com/Secure/elibrary/papers/DATA02/DATA02002FU.pdf

http://faculty.ksu.edu.sa/sfatima/ksu/Shared%20Documents/MIS%20350/BOOK/sharda_dss10_im_05.pdf

http://ijcttjournal.org/Volume4/issue-2/IJCTT-V4I2P129.pdf

]]> 2017-04-30 16:41:24 UTC https://padlet.com/nilamnur/21bshxee24s9/wish/169066126 Wan | Rijal onezisone https://padlet.com/nilamnur/21bshxee24s9/wish/169836300 2017-05-04 03:12:55 UTC https://padlet.com/nilamnur/21bshxee24s9/wish/169836300 Data Mining Buzz #3 https://padlet.com/nilamnur/21bshxee24s9/wish/176934516 Yassin MY and Sakib]]> 2017-06-20 04:18:21 UTC https://padlet.com/nilamnur/21bshxee24s9/wish/176934516