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APPINF
2003
13 years 9 months ago
Fast Frequent Itemset Mining using Compressed Data Representation
Discovering association rules by identifying relationships among sets of items in a transaction database is an important problem in Data Mining. Finding frequent itemsets is compu...
Raj P. Gopalan, Yudho Giri Sucahyo
ICDE
2007
IEEE
129views Database» more  ICDE 2007»
14 years 2 months ago
Ontology-driven Rule Generalization and Categorization for Market Data
—Radio Frequency Identification (RFID) is an emerging technique that can significantly enhance supply chain processes and deliver customer service improvements. RFID provides use...
Dongwoo Won, Dennis McLeod
PKDD
2004
Springer
141views Data Mining» more  PKDD 2004»
14 years 1 months ago
Spatial Associative Classification at Different Levels of Granularity: A Probabilistic Approach
In this paper we propose a novel spatial associative classifier method based on a multi-relational approach that takes spatial relations into account. Classification is driven by s...
Michelangelo Ceci, Annalisa Appice, Donato Malerba
KBS
2006
79views more  KBS 2006»
13 years 7 months ago
Using multiple and negative target rules to make classifiers more understandable
One major goal for data mining is to understand data. Rule based methods are better than other methods in making mining results comprehensible. However, the current rule based cla...
Jiuyong Li, Jason Jones
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