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» Mining association rules from imprecise ordinal data
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ICDE
2007
IEEE
129views Database» more  ICDE 2007»
16 years 14 days 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
DATAMINE
2006
131views more  DATAMINE 2006»
15 years 6 months ago
A systematic approach to the assessment of fuzzy association rules
In order to allow for the analysis of data sets including numerical attributes, several generalizations of association rule mining based on fuzzy sets have been proposed in the li...
Didier Dubois, Eyke Hüllermeier, Henri Prade
PAKDD
1999
ACM
129views Data Mining» more  PAKDD 1999»
15 years 10 months ago
Visually Aided Exploration of Interesting Association Rules
Association rules are a class of important regularities in databases. They are found to be very useful in practical applications. However, the number of association rules discovere...
Bing Liu, Wynne Hsu, Ke Wang, Shu Chen
DGO
2007
192views Education» more  DGO 2007»
15 years 7 months ago
D-HOTM: distributed higher order text mining
We present D-HOTM, a framework for Distributed Higher Order Text Mining based on named entities extracted from textual data that are stored in distributed relational databases. Unl...
William M. Pottenger
SAC
2005
ACM
15 years 11 months ago
Mining concept associations for knowledge discovery in large textual databases
In this paper, we describe a new approach for mining concept associations from large text collections. The concepts are short sequences of words that occur frequently together acr...
Xiaowei Xu, Mutlu Mete, Nurcan Yuruk