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ECML
2007
Springer
16 years 26 days ago
Discovering Word Meanings Based on Frequent Termsets
Word meaning ambiguity has always been an important problem in information retrieval and extraction, as well as, text mining (documents clustering and classification). Knowledge di...
Henryk Rybinski, Marzena Kryszkiewicz, Grzegorz Pr...
193
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SAC
2006
ACM
16 years 20 days ago
A probability analysis for candidate-based frequent itemset algorithms
This paper explores the generation of candidates, which is an important step in frequent itemset mining algorithms, from a theoretical point of view. Important notions in our prob...
Nele Dexters, Paul W. Purdom, Dirk Van Gucht
ICANN
2005
Springer
16 years 6 days ago
Principles of Employing a Self-organizing Map as a Frequent Itemset Miner
This work proposes a theoretical guideline in the specific area of Frequent Itemset Mining (FIM). It supports the hypothesis that the use of neural network technology for the prob...
Vicente O. Baez-Monroy, Simon O'Keefe
WIDM
2004
ACM
16 years 3 days ago
Web personalization based on static information and dynamic user behavior
The explosive growth of the web is at the basis of the great interest into web usage mining techniques in both commercial and research areas. In this paper, a web personalization ...
Massimiliano Albanese, Antonio Picariello, Carlo S...
DMIN
2006
132views Data Mining» more  DMIN 2006»
15 years 8 months ago
An Overview of Associative Classifiers
Abstract-- Associative classification is a new classification approach integrating association mining and classification. It becomes a significant tool for knowledge discovery and ...
Yanmin Sun, Andrew K. C. Wong, Yang Wang 0007