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KDD
2007
ACM
170views Data Mining» more  KDD 2007»
11 years 7 days 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
CVPR
2007
IEEE
11 years 1 months ago
Discovery of Collocation Patterns: from Visual Words to Visual Phrases
A visual word lexicon can be constructed by clustering primitive visual features, and a visual object can be described by a set of visual words. Such a "bag-of-words" re...
Junsong Yuan, Ying Wu, Ming Yang
PODS
2009
ACM
134views Database» more  PODS 2009»
11 years 11 days ago
An efficient rigorous approach for identifying statistically significant frequent itemsets
As advances in technology allow for the collection, storage, and analysis of vast amounts of data, the task of screening and assessing the significance of discovered patterns is b...
Adam Kirsch, Michael Mitzenmacher, Andrea Pietraca...
ICDM
2006
IEEE
138views Data Mining» more  ICDM 2006»
10 years 5 months ago
Adding Semantics to Email Clustering
This paper presents a novel algorithm to cluster emails according to their contents and the sentence styles of their subject lines. In our algorithm, natural language processing t...
Hua Li, Dou Shen, Benyu Zhang, Zheng Chen, Qiang Y...
ICMCS
2006
IEEE
344views Multimedia» more  ICMCS 2006»
10 years 5 months ago
Pattern Mining in Visual Concept Streams
Pattern mining algorithms are often much easier applied than quantitatively assessed. In this paper we address the pattern evaluation problem by looking at both the capability of ...
Lexing Xie, Shih-Fu Chang
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