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ICDM
2009
IEEE
109views Data Mining» more  ICDM 2009»
14 years 3 months ago
Knowledge Discovery from Citation Networks
—Knowledge discovery from scientific articles has received increasing attentions recently since huge repositories are made available by the development of the Internet and digit...
Zhen Guo, Zhongfei Zhang, Shenghuo Zhu, Yun Chi, Y...
KDD
2007
ACM
137views Data Mining» more  KDD 2007»
14 years 9 months ago
Characterising the difference
Characterising the differences between two databases is an often occurring problem in Data Mining. Detection of change over time is a prime example, comparing databases from two b...
Jilles Vreeken, Matthijs van Leeuwen, Arno Siebes
CINQ
2004
Springer
151views Database» more  CINQ 2004»
14 years 10 days ago
Query Languages Supporting Descriptive Rule Mining: A Comparative Study
Recently, inductive databases (IDBs) have been proposed to tackle the problem of knowledge discovery from huge databases. With an IDB, the user/analyst performs a set of very diffe...
Marco Botta, Jean-François Boulicaut, Cyril...
TSD
2010
Springer
13 years 6 months ago
Comparison of Different Lemmatization Approaches through the Means of Information Retrieval Performance
This paper presents a quantitative performance analysis of two different approaches to the lemmatization of the Czech text data. The first one is based on manually prepared diction...
Jakub Kanis, Lucie Skorkovská
KDD
2001
ACM
253views Data Mining» more  KDD 2001»
14 years 9 months ago
GESS: a scalable similarity-join algorithm for mining large data sets in high dimensional spaces
The similarity join is an important operation for mining high-dimensional feature spaces. Given two data sets, the similarity join computes all tuples (x, y) that are within a dis...
Jens-Peter Dittrich, Bernhard Seeger