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» A rough set approach to multiple dataset analysis
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PREMI
2007
Springer
15 years 3 months ago
Discovery of Process Models from Data and Domain Knowledge: A Rough-Granular Approach
The rapid expansion of the Internet has resulted not only in the ever-growing amount of data stored therein, but also in the burgeoning complexity of the concepts and phenomena per...
Andrzej Skowron
CIKM
2010
Springer
14 years 8 months ago
CiteData: a new multi-faceted dataset for evaluating personalized search performance
Personalized search systems have evolved to utilize heterogeneous features including document hyperlinks, category labels in various taxonomies and social tags in addition to free...
Abhay Harpale, Yiming Yang, Siddharth Gopal, Daqin...
95
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ICDCS
2006
IEEE
15 years 3 months ago
ParRescue: Scalable Parallel Algorithm and Implementation for Biclustering over Large Distributed Datasets
Biclustering refers to simultaneously capturing correlations present among subsets of attributes (columns) and records (rows). It is widely used in data mining applications includ...
Jianhong Zhou, Ashfaq A. Khokhar
TRS
2008
14 years 9 months ago
Generalized Indiscernibility Relations: Applications for Missing Values and Analysis of Structural Objects
In this paper, we discuss an approach to structural objects based on a generalisation of indiscernibility relation used in rough set theory. The existing results in rough set theor...
Wojciech Jaworski
GIS
2008
ACM
15 years 10 months ago
Finding regional co-location patterns for sets of continuous variables in spatial datasets
This paper proposes a novel framework for mining regional colocation patterns with respect to sets of continuous variables in spatial datasets. The goal is to identify regions in ...
Christoph F. Eick, Jean-Philippe Nicot, Rachana Pa...