Software

Copyright: the software tools listed in this page are free for non-commercial use. The authors of these tools have no responsibility or
legal obligation for any consequence caused by using them. If you want to use them in your publications, please cite them appropriately.
Please contact Keke Chen (keke.chen at wright.edu) for any further question. Some programs are not ready yet, but they are in our schedule.

· CRESP optimizer for MapReduce programs in public clouds (to appear)

Please cite: Fengguang Tian, Keke Chen, " Towards Optimal Resource Provisioning for Running MapReduce Programs in Public Clouds",
IEEE Conference on Cloud Computing, Washington DC, 2011

· Secure and privacy-preserving range query service with RASP perturbation (attack evaluation and parameter optimization, demo)

Please cite: Keke Chen, Ramakanth Kavuluru, Shumin Guo " RASP: Efficient Multidimensional Range Query on Attack-Resilient Encrypted Databases ",
ACM Conference on Data and Application Security and Privacy (CODASPY), 2011

· CloudVista demo system (client side UI demo (download, online), the full client-cloud demo on Amazon)

Please cite:  Keke Chen, Huiqi Xu, Fengguang Tian, Shumin Guo, " CloudVista: visual cluster exploration for extreme scale data in the cloud ",
Scientific and Statistical Database Management Conference, Portland OR, 2011

· Geometric data perturbation – attack evaluation and parameter optimization

Please cite:  Keke Chen and Ling Liu, " Geometric Data Perturbation for Privacy Preserving Outsourced Data Mining ",
Journal of Knowledge and Information Systems (KAIS), 2011

· WCD transactional data clustering – python reference implementation (no optimization, python code)

Please cite:  Hua Yan, Keke Chen and Ling Liu, "SCALE: a Scalable Framework for Efficiently Clustering Large Transactional Data ",
Journal of Data Mining and Knowledge Discovery (DMKD), 2010

· BKPlot – finding the best K for categorical data clustering (binary download)

Please cite: Keke Chen and Ling Liu: " Best K: the Critical Clustering Structures in Categorical Data ",
Knowedge and Information Systems, 2008

· VISTA - interactive visual cluster exploration system: homepage and download

Please cite: Keke Chen and Ling Liu: "VISTA: Validating and Refining Clusters via Visualization."
Journal of Information Visualization, Sept. 2004

Other implementations:

· RA-SVM ranking adaptation (Geng et al. CIKM 2009) with SVM (our implementation based on liblinear SVM) that was used in our ACM TOIS paper