1.A Scalable Data Chunk Similarity based Compression Approach for Efficient Big Sensing Data Processing on Cloud.
2.A Systematic Approach Toward Description and Classification of Cybercrime Incidents.
3.Achieving Efficient and Privacy-Preserving Cross-Domain Big Data Deduplication in Cloud.
4.aHDFS: An Erasure-Coded Data Archival System for Hadoop Clusters.
5.Big Data Privacy in Biomedical Research.
6.Cost-Aware Big Data Processing across Geo-distributed Datacenters.
7.Disease Prediction by Machine Learning over Big Data from Healthcare Communities.
8.DyScale: a MapReduce Job Scheduler for Heterogeneous Multicore Processors.
9.Efficient Processing of Skyline Queries Using MapReduce.
10.FiDoop-DP: Data Partitioning in Frequent Itemset Mining on Hadoop Clusters.
11.Hadoop MapReduce for Mobile Clouds.
12.Mining Human Activity Patterns from Smart Home Big Data for Healthcare Applications.
13.PPHOPCM: Privacy-preserving High-order Possibilistic c-Means Algorithm for Big Data Clustering with Cloud Computing.
14.Practical Privacy-Preserving MapReduce Based K-means Clustering over Large-scale Dataset.
15.Public Interest Analysis Based on Implicit Feedback of IPTV Users.
16.Ring: Real-Time Emerging Anomaly Monitoring System over Text Streams.
17.Robust Big Data Analytics for Electricity Price Forecasting in the Smart Grid.
18.Scalable Uncertainty-Aware Truth Discovery in Big Data Social Sensing Applications for Cyber-Physical Systems.
19.Self-Adjusting Slot Configurations for Homogeneous and Heterogeneous Hadoop Clusters.
20.Service Rating Prediction by Exploring Social Mobile Users’ Geographical Locations.