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KDD
2007
ACM
170views Data Mining» more  KDD 2007»
16 years 6 months ago
From frequent itemsets to semantically meaningful visual patterns
Data mining techniques that are successful in transaction and text data may not be simply applied to image data that contain high-dimensional features and have spatial structures....
Junsong Yuan, Ying Wu, Ming Yang
KDD
2007
ACM
182views Data Mining» more  KDD 2007»
16 years 6 months ago
A fast algorithm for finding frequent episodes in event streams
Frequent episode discovery is a popular framework for mining data available as a long sequence of events. An episode is essentially a short ordered sequence of event types and the...
Srivatsan Laxman, P. S. Sastry, K. P. Unnikrishnan
157
Voted
KDD
2004
ACM
163views Data Mining» more  KDD 2004»
16 years 6 months ago
Exploiting dictionaries in named entity extraction: combining semi-Markov extraction processes and data integration methods
We consider the problem of improving named entity recognition (NER) systems by using external dictionaries--more specifically, the problem of extending state-of-the-art NER system...
William W. Cohen, Sunita Sarawagi
182
Voted
KDD
2004
ACM
135views Data Mining» more  KDD 2004»
16 years 6 months ago
Discovering additive structure in black box functions
Many automated learning procedures lack interpretability, operating effectively as a black box: providing a prediction tool but no explanation of the underlying dynamics that driv...
Giles Hooker
KDD
2001
ACM
150views Data Mining» more  KDD 2001»
16 years 6 months ago
Empirical bayes screening for multi-item associations
This paper considers the framework of the so-called "market basket problem", in which a database of transactions is mined for the occurrence of unusually frequent item s...
William DuMouchel, Daryl Pregibon