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» Mining Rare Association Rules from e-Learning Data
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ADC
2003
Springer
182views Database» more  ADC 2003»
14 years 22 days ago
CT-ITL : Efficient Frequent Item Set Mining Using a Compressed Prefix Tree with Pattern Growth
Discovering association rules that identify relationships among sets of items is an important problem in data mining. Finding frequent item sets is computationally the most expens...
Yudho Giri Sucahyo, Raj P. Gopalan
SIGMOD
1999
ACM
112views Database» more  SIGMOD 1999»
13 years 11 months ago
A New Method for Similarity Indexing of Market Basket Data
In recent years, many data mining methods have been proposed for finding useful and structured information from market basket data. The association rule model was recently propos...
Charu C. Aggarwal, Joel L. Wolf, Philip S. Yu
DKE
2008
124views more  DKE 2008»
13 years 7 months ago
A MaxMin approach for hiding frequent itemsets
In this paper, we are proposing a new algorithmic approach for sanitizing raw data from sensitive knowledge in the context of mining of association rules. The new approach (a) rel...
George V. Moustakides, Vassilios S. Verykios
CORR
2010
Springer
208views Education» more  CORR 2010»
13 years 7 months ago
Discovering potential user browsing behaviors using custom-built apriori algorithm
Most of the organizations put information on the web because they want it to be seen by the world. Their goal is to have visitors come to the site, feel comfortable and stay a whi...
Sandeep Singh Rawat, Lakshmi Rajamani
HICSS
2006
IEEE
138views Biometrics» more  HICSS 2006»
14 years 1 months ago
An Efficient Algorithm for Real-Time Frequent Pattern Mining for Real-Time Business Intelligence Analytics
Finding frequent patterns from databases has been the most time consuming process in data mining tasks, like association rule mining. Frequent pattern mining in real-time is of in...
Rajanish Dass, Ambuj Mahanti