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» Integrating Classification and Association Rule Mining
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CIKM
2006
Springer
15 years 1 months ago
Multi-evidence, multi-criteria, lazy associative document classification
We present a novel approach for classifying documents that combines different pieces of evidence (e.g., textual features of documents, links, and citations) transparently, through...
Adriano Veloso, Wagner Meira Jr., Marco Cristo, Ma...
PKDD
2001
Springer
185views Data Mining» more  PKDD 2001»
15 years 2 months ago
Temporal Rule Discovery for Time-Series Satellite Images and Integration with RDB
Feature extraction and knowledge discovery from a large amount of image data such as remote sensing images have become highly required recent years. In this study, a framework for ...
Rie Honda, Osamu Konishi
ADMA
2010
Springer
248views Data Mining» more  ADMA 2010»
14 years 7 months ago
Classification Inductive Rule Learning with Negated Features
This paper reports on an investigation to compare a number of strategies to include negated features within the process of Inductive Rule Learning (IRL). The emphasis is on generat...
Stephanie Chua, Frans Coenen, Grant Malcolm
SIGMOD
2005
ACM
161views Database» more  SIGMOD 2005»
15 years 9 months ago
Mining Top-k Covering Rule Groups for Gene Expression Data
In this paper, we propose a novel algorithm to discover the topk covering rule groups for each row of gene expression profiles. Several experiments on real bioinformatics datasets...
Gao Cong, Kian-Lee Tan, Anthony K. H. Tung, Xin Xu
KBS
2006
79views more  KBS 2006»
14 years 9 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