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» Practical Preference Relations for Large Data Sets
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TKDE
2012
253views Formal Methods» more  TKDE 2012»
11 years 10 months ago
Horizontal Aggregations in SQL to Prepare Data Sets for Data Mining Analysis
—Preparing a data set for analysis is generally the most time consuming task in a data mining project, requiring many complex SQL queries, joining tables and aggregating columns....
Carlos Ordonez, Zhibo Chen 0002
ICDM
2006
IEEE
193views Data Mining» more  ICDM 2006»
14 years 2 months ago
Feature Subset Selection on Multivariate Time Series with Extremely Large Spatial Features
Several spatio-temporal data collected in many applications, such as fMRI data in medical applications, can be represented as a Multivariate Time Series (MTS) matrix with m rows (...
Hyunjin Yoon, Cyrus Shahabi
IPMI
2003
Springer
14 years 9 months ago
Analysis of Event-Related fMRI Data Using Best Clustering Bases
We explore a new paradigm for the analysis of event-related functional magnetic resonance images (fMRI) of brain activity. We regard the fMRI data as a very large set of time serie...
François G. Meyer, Jatuporn Chinrungrueng
AI
2010
Springer
13 years 8 months ago
Elicitation strategies for soft constraint problems with missing preferences: Properties, algorithms and experimental studies
We consider soft constraint problems where some of the preferences may be unspecified. This models, for example, settings where agents are distributed and have privacy issues, or ...
Mirco Gelain, Maria Silvia Pini, Francesca Rossi, ...
ICCBR
2003
Springer
14 years 1 months ago
Case-Based Ranking for Decision Support Systems
Abstract. Very often a planning problem can be formulated as a ranking problem: i.e. to find an order relation over a set of alternatives. The ranking of a finite set of alternat...
Paolo Avesani, Sara Ferrari, Angelo Susi