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DATAMINE
1999
108views more  DATAMINE 1999»
13 years 7 months ago
A Survey of Methods for Scaling Up Inductive Algorithms
Abstract. One of the de ning challenges for the KDD research community is to enable inductive learning algorithms to mine very large databases. This paper summarizes, categorizes, ...
Foster J. Provost, Venkateswarlu Kolluri
AAI
2007
132views more  AAI 2007»
13 years 7 months ago
Incremental Extraction of Association Rules in Applicative Domains
In recent years, the KDD process has been advocated to be an iterative and interactive process. It is seldom the case that a user is able to answer immediately with a single query...
Arianna Gallo, Roberto Esposito, Rosa Meo, Marco B...
KDD
2005
ACM
163views Data Mining» more  KDD 2005»
14 years 1 months ago
Web mining from competitors' websites
This paper presents a framework for user-oriented text mining. It is then illustrated with an example of discovering knowledge from competitors’ websites. The knowledge to be di...
Xin Chen, Yi-fang Brook Wu
CIKM
2006
Springer
13 years 11 months ago
An integer programming approach for frequent itemset hiding
The rapid growth of transactional data brought, soon enough, into attention the need of its further exploitation. In this paper, we investigate the problem of securing sensitive k...
Aris Gkoulalas-Divanis, Vassilios S. Verykios
CORR
2010
Springer
279views Education» more  CORR 2010»
13 years 7 months ago
Mining Frequent Itemsets Using Genetic Algorithm
In general frequent itemsets are generated from large data sets by applying association rule mining algorithms like Apriori, Partition, Pincer-Search, Incremental, Border algorithm...
Soumadip Ghosh, Sushanta Biswas, Debasree Sarkar, ...