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KDD
2000
ACM
77views Data Mining» more  KDD 2000»
13 years 9 months ago
Small is beautiful: discovering the minimal set of unexpected patterns
A drawback of most traditional data mining methods is that they do not leverage prior knowledge of users. In many business settings, managers and analysts have significant intuiti...
Balaji Padmanabhan, Alexander Tuzhilin
AUSDM
2006
Springer
122views Data Mining» more  AUSDM 2006»
13 years 9 months ago
Analysis of Breast Feeding Data Using Data Mining Methods
The purpose of this study is to demonstrate the benefit of using common data mining techniques on survey data where statistical analysis is routinely applied. The statistical surv...
Hongxing He, Huidong Jin, Jie Chen, Damien McAulla...
IDA
1999
Springer
13 years 9 months ago
Knowledge-Based Visualization to Support Spatial Data Mining
Data mining methods are designed for revealing significant relationships and regularities in data collections. Regarding spatially referenced data, analysis by means of data minin...
Gennady L. Andrienko, Natalia V. Andrienko
DEXAW
1999
IEEE
97views Database» more  DEXAW 1999»
13 years 9 months ago
Mining Several Data Bases with an Ensemble of Classifiers
The results of knowledge discovery in databases could vary depending on the data mining method. There are several ways to select the most appropriate data mining method dynamicall...
Seppo Puuronen, Vagan Y. Terziyan, Alexander Logvi...
PAKDD
2005
ACM
160views Data Mining» more  PAKDD 2005»
13 years 11 months ago
Improving Mining Quality by Exploiting Data Dependency
The usefulness of the results produced by data mining methods can be critically impaired by several factors such as (1) low quality of data, including errors due to contamination, ...
Fang Chu, Yizhou Wang, Carlo Zaniolo, Douglas Stot...
ICDM
2005
IEEE
148views Data Mining» more  ICDM 2005»
13 years 11 months ago
Online Hierarchical Clustering in a Data Warehouse Environment
Many important industrial applications rely on data mining methods to uncover patterns and trends in large data warehouse environments. Since a data warehouse is typically updated...
Elke Achtert, Christian Böhm, Hans-Peter Krie...
ICDM
2006
IEEE
86views Data Mining» more  ICDM 2006»
13 years 11 months ago
Turning Clusters into Patterns: Rectangle-Based Discriminative Data Description
The ultimate goal of data mining is to extract knowledge from massive data. Knowledge is ideally represented as human-comprehensible patterns from which end-users can gain intuiti...
Byron J. Gao, Martin Ester
SEMWEB
2007
Springer
13 years 11 months ago
OntoDNA: Ontology Alignment Results for OAEI 2007
OntoDNA is an automated ontology mapping and merging system that utilizes unsupervised data mining methods, comprising of Formal Concept analysis (FCA), Self-Organizing map (SOM) a...
Ching-Chieh Kiu, Chien-Sing Lee
PREMI
2007
Springer
13 years 11 months ago
Discovery of Process Models from Data and Domain Knowledge: A Rough-Granular Approach
The rapid expansion of the Internet has resulted not only in the ever-growing amount of data stored therein, but also in the burgeoning complexity of the concepts and phenomena per...
Andrzej Skowron
VL
2007
IEEE
120views Visual Languages» more  VL 2007»
13 years 11 months ago
Finding Gender Differences in End-User Debugging: A Data Mining Approach
We are currently investigating what types of end user personas (or homogeneous groups in the population) exist and what works for or hinders each in end-user debugging. These pers...
Valentina Grigoreanu