Integrative, Rapid, Data Analysis
Methods that bring together data from many sources and turn it into timely, usable insight.
-
Analysis of Morphology Based Horticultural Features through Clustering Methods
K Deb, A Hazra, S Kundu, P Hazra
-
A unified framework for reputation estimation in online rating systems
GS Ling, I King, MRT Lyu. Cited by 9
-
Shape Oriented Feature Selection for Tomato Plant Identification
A Hazra, K Deb, S Kundu, P Hazra. Cited by 17
-
Efficient online learning for multitask feature selection
H Yang, MRT Lyu, I King. Cited by 45
-
Solving clustering problems using bi-objective evolutionary optimisation and knee finding algorithms
G Recio, K Deb. Cited by 3
-
Introduction to Special section on Large-scale Data Mining
J Tang, L Chen, I King, J Wang
-
Change detection in remotely sensed images using semi-supervised clustering algorithms
M Roy, S Ghosh, AK Ghosh. Cited by 4
-
Data Management with Flexible and Extensible Data Schema in CLANS
S Wang, Y Man, T Zhang, TJ Wong, I King. Cited by 2
-
Preface: Computational Systems-Biology and Bioinformatics
S Cho, JH Chan, K Hwang
-
Self-adaptive differential evolution for feature selection in hyperspectral image data
AK Ghosh, A Datta, S Ghosh. Cited by 168
-
Search-based semi-supervised clustering algorithms for change detection in remotely sensed images
M Roy, S Ghosh, AK Ghosh. Cited by 4
-
Clustering based band selection for hyperspectral images
A Datta, S Ghosh, AK Ghosh. Cited by 14