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Big Data Mining and Its Application Team

Set up Time: 2013

Leader: Genlin Ji

Members: Yudong Zhang, Jiaquan Gao, Bin Zhao, Peiming Bao, Chao Tan, Shuihua Wang



The group of “Big Data Mining and Its Application” mainly concentrates the research of big data mining algorithm, technology and application. This study includes Correlation analysis, clustering analysis, classification, anomaly detection, etc. This group consists of 3 professors, 2 associate professors, and 2 lecturers. This group published more than 100 papers and 6 NSFC and province projects have been granted.


Research Content

Correlation analysis

clustering analysis


anomaly detection


Representative Achievements


[1]  Mitochondrial Dysfunction as a Neurobiological Subtype of Autism Spectrum Disorder: Evidence from Brain Imaging. JAMA Psychiatry. 2014, 71(6): 665-671 (IF: 12.008, ESI Highly Cited Papers)

[2] Binary PSO with Mutation Operator for Feature Selection using Decision Tree applied to Spam Detection . Knowledge-Based Systems. 2014, 64: 22-31 (IF: 2.947, ESI Highly Cited Papers)

[3]  Exponential Wavelet Iterative Shrinkage Thresholding Algorithm for Compressed Sensing Magnetic Resonance Imaging. Information Sciences. 2015, doi: 10.1016/j.ins.2015.06.017 (IF: 4.038)

 [4]  A Support-Based Reconstruction for SENSE MRI. Sensors. 13(4), 4029-4040. 2013. (IF: 2.245)

[5] Detection of subjects and brain regions related to Alzheimer’s disease using 3D MRI scans based on eigenbrain and machine learning. Frontiers in Computational Neuroscience. 2015, 9(66): 1-15, doi: 10.3389/fncom.2015.00066 (IF: 2.201)

[6] Effect of Spider web plot in MR brain image classification. Pattern Recognition Letters. 2015, 62: 14-16 (IF: 1.551)

[7] Fruit Classification by Wavelet-Entropy and Feedforward Neural Network trained by Fitness-scaled Chaotic ABC and Biogeography-based Optimization. Entropy. 2015, 17(8): 5711-5728 (IF: 1.502)

[8] Preclinical Diagnosis of Magnetic Resonance (MR) Brain Images via Discrete Wavelet Packet Transform with Tsallis Entropy and Generalized Eigenvalue Proximate Support Vector Machine (GEPSVM) . Entropy. 2015, 17, 1795-1813 (IF: 1.502)

[9] Feed-forward Neural Network Optimized by Hybridization of PSO and ABC for Abnormal Brain Detection. International Journal of Imaging Systems and Technology. 2015, 25(2): 153-164  (IF: 1.301)

[10]  Pathological Brain Detection in Magnetic Resonance Imaging Scanning by Wavelet Entropy and Hybridization of Biogeography-based Optimization and Particle Swarm Optimization. Progress in Electromagnetics Research – PIER. 2015, 152: 41-58 (IF: 1.229)
[11] Pathological Brain Detection based on wavelet entropy and Hu moment invariants. Bio-Medical Materials and Engineering, 2015, 26: 1283-1290 (IF: 1.091)

[12] Classification of Alzheimer Disease Based on Structural Magnetic Resonance Imaging by Kernel Support Vector Machine Decision Tree. Progress in Electromagnetics Research-PIER. 2014, 144, 185-191 (IF: 1.229)