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» Using Data Mining in MURA Graphic Problems
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TMM
2002
104views more  TMM 2002»
15 years 3 months ago
Spatial contextual classification and prediction models for mining geospatial data
Modeling spatial context (e.g., autocorrelation) is a key challenge in classification problems that arise in geospatial domains. Markov random fields (MRF) is a popular model for i...
Shashi Shekhar, Paul R. Schrater, Ranga Raju Vatsa...
KDD
2006
ACM
164views Data Mining» more  KDD 2006»
16 years 3 months ago
Assessing data mining results via swap randomization
The problem of assessing the significance of data mining results on high-dimensional 0?1 data sets has been studied extensively in the literature. For problems such as mining freq...
Aristides Gionis, Heikki Mannila, Panayiotis Tsapa...
ICDM
2002
IEEE
114views Data Mining» more  ICDM 2002»
15 years 8 months ago
Online Algorithms for Mining Semi-structured Data Stream
In this paper, we study an online data mining problem from streams of semi-structured data such as XML data. Modeling semi-structured data and patterns as labeled ordered trees, w...
Tatsuya Asai, Hiroki Arimura, Kenji Abe, Shinji Ka...
ICDM
2009
IEEE
112views Data Mining» more  ICDM 2009»
15 years 10 months ago
Resolving Identity Uncertainty with Learned Random Walks
A pervasive problem in large relational databases is identity uncertainty which occurs when multiple entries in a database refer to the same underlying entity in the world. Relati...
Ted Sandler, Lyle H. Ungar, Koby Crammer
AUSDM
2007
Springer
93views Data Mining» more  AUSDM 2007»
15 years 9 months ago
Customer Analytics Projects: Addressing Existing Problems with a Process that Leads to Success
This article explicitly outlines an approach designed to allow optimal utilisation of Analytics in the industry setting. The paper focuses on the key stages of the Analytics proce...
Inna Kolyshkina, Simeon J. Simoff