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With continued advances in communication network technology and sensing technology
Keke Chen, Ling Liu. iVIBRATE: Interactive Visualization Based Framework for Clustering Large Datasets. 2006 ;.  (0 bytes)
which offers visualization-guided disk-labeling solutions that are effective in dealing with outliers
Keke Chen, Ling Liu. iVIBRATE: Interactive Visualization Based Framework for Clustering Large Datasets. 2006 ;.  (0 bytes)
which invites human into the large-scale iterative clustering process through interactive visualization
Keke Chen, Ling Liu. iVIBRATE: Interactive Visualization Based Framework for Clustering Large Datasets. 2006 ;.  (0 bytes)
which demand effective solutions. The first problem is how to effectively define and validate irregularly shaped clusters
Keke Chen, Ling Liu. iVIBRATE: Interactive Visualization Based Framework for Clustering Large Datasets. 2006 ;.  (0 bytes)
web search ranking
Keke Chen, Jing Bai, Zhaohui Zheng. Ranking Function Adaptation With Boosting Trees. ACM Transactions on Information Systems. 2011 ;.  (437.8 KB)
we study the entropy property between the clustering results of categorical data with different K number of clusters
Ling Liu, Keke Chen. Best K: the Critical Clustering Structures in Categorical Data. 2008 ;.  (0 bytes)
we propose Transactional-cluster-modes Dissimilarity based on the concept of coverage density as an intuitive transactional inter-cluster dissimilarity measure. Based on the above measure
Hua Yan, Keke Chen, Ling Liu. Determining the Best K for Clustering Transactional Datasets: A Coverage Density-based Approach. 2008 ;.  (536 KB)
we propose a novel method to find a set of candidate optimal number Ks of clusters in transactional datasets. Concretely
Hua Yan, Keke Chen, Ling Liu. Determining the Best K for Clustering Transactional Datasets: A Coverage Density-based Approach. 2008 ;.  (536 KB)
we describe iVIBRATE &#161 an interactive-visualization based three-phase framework for clustering large datasets. The two main components of iVIBRATE are its VISTA visual cluster rendering subsystem
Keke Chen, Ling Liu. iVIBRATE: Interactive Visualization Based Framework for Clustering Large Datasets. 2006 ;.  (0 bytes)
visualization technique
Zohreh Alavi, Sagar Sharma, Lu Zhou, Keke Chen. Scalable Euclidean Embedding for Big Data. 2015 IEEE 8th International Conference on Cloud Computing. New York City, NY: IEEE; 2015. p. 773 - 780.
visual cluster exploartion
Keke Chen, Huiqi Xu, Fengguang Tian, Shumin Guo. CloudVista: Visual Cluster Exploration for Extreme Scale Data in the Cloud. In Scientific and Statistical Database Management Conference. Portland OR; 2011.  (557.52 KB)
user feedback
Keke Chen, Jing Bai, Zhaohui Zheng. Ranking Function Adaptation With Boosting Trees. ACM Transactions on Information Systems. 2011 ;.  (437.8 KB)
traditional cluster validation techniques based on geometric shapes and density distributions are not appropriate for categorical data. In this paper
Ling Liu, Keke Chen. Best K: the Critical Clustering Structures in Categorical Data. 2008 ;.  (0 bytes)
those articles selected by the Surgical Oncology Society. <br /><b>Results</b>: Our results showed that CCPY outperforms CC and JIF
Ling Liu, Keke Chen. Document Clustering and Ranking System for Exploring MEDLINE Citations. 2007 ;.  (0 bytes)
this study developed an approach that retrieved and organized MEDLINE citations into different topical groups and prioritized important citations in each group. <br /> <b>Design</b>: A text mining system framework for automatic document clustering and ra
Ling Liu, Keke Chen. Document Clustering and Ranking System for Exploring MEDLINE Citations. 2007 ;.  (0 bytes)
there is an astounding growth in the amount of data produced and made available through the cyberspace. Efficient and high quality clustering of large datasets continues to be one of the most important problems in largescale data analysis. A commonly use
Keke Chen, Ling Liu. iVIBRATE: Interactive Visualization Based Framework for Clustering Large Datasets. 2006 ;.  (0 bytes)
The problem of determining the optimal number of clusters is important but mysterious in cluster analysis. In this paper
Hua Yan, Keke Chen, Ling Liu. Determining the Best K for Clustering Transactional Datasets: A Coverage Density-based Approach. 2008 ;.  (536 KB)
The demand on cluster analysis for categorical data continues to grow over the last decade. A well-known problem in categorical clustering is to determine the best K number of clusters. Although several categorical clustering algorithms have been develope
Ling Liu, Keke Chen. Best K: the Critical Clustering Structures in Categorical Data. 2008 ;.  (0 bytes)
Space Situational Awareness
Keke Chen, Bharath Avusherla, Sarah Allison, Vincent Schmidt. SPIN: Cleaning, Monitoring, and Querying Image Streams Generated by Ground-Based Telescopes for Space Situational Awareness. 2017 ;. Citation Keke Chen, Bharath Avusherla, Sarah Allison ,Vincent Schmidt Data Intensive Analysis and Computing Lab Department of Computer Science and Engineering Wright State University, OH, USA E-mail: {keke.chen, avusherla.2, allison.24}@wright.edu
Citation Keke Chen, Bharath Avusherla, Sarah Allison ,Vincent Schmidt Data Intensive Analysis and Computing Lab Department of Computer Science and Engineering Wright State University, OH, USA E-mail: {keke.chen, avusherla.2, allison.24}@wright.edu
 (2.5 MB)
social media analysis
Shreyansh Bhatt, Swati Padhee, Amit Sheth, Keke Chen, Valerie Shalin, Derek Doran, Brandon Minnery. Knowledge Graph Enhanced Community Detection and Characterization. In Twelfth ACM International Conference on Web Search and Data Mining. Melbourne, Australia: ACM; 2019. p. 51-59.  (1.47 MB)
simply showing them as a long list often provides poor overview. With a goal of presenting users with reduced sets of relevant citations
Ling Liu, Keke Chen. Document Clustering and Ranking System for Exploring MEDLINE Citations. 2007 ;.  (0 bytes)
Security services
Sagar Sharma, James Powers, Keke Chen. Privacy-Preserving Spectral Analysis of Large Graphs in Public Clouds. Asia Conference on Computer and Communications Security 2016. Xi'an, China: ACM; 2016. p. 71-82.
search engine ranking
Jing Bai, Fernando Diaz, Yi Chang, Zhaohui Zheng, Keke Chen. Cross-Market Model Adaptation with Pairwise Preference Data for Web Search Ranking. In International Conference on Computational Linguistics. 2010.  (267.85 KB)
scalable Euclidean embedding algorithm
Zohreh Alavi, Sagar Sharma, Lu Zhou, Keke Chen. Scalable Euclidean Embedding for Big Data. 2015 IEEE 8th International Conference on Cloud Computing. New York City, NY: IEEE; 2015. p. 773 - 780.
Scalability
Zohreh Alavi, Sagar Sharma, Lu Zhou, Keke Chen. Scalable Euclidean Embedding for Big Data. 2015 IEEE 8th International Conference on Cloud Computing. New York City, NY: IEEE; 2015. p. 773 - 780.
sampling/summarization &#161 iterative cluster analysis &#161 disk-labeling&#39
Keke Chen, Ling Liu. iVIBRATE: Interactive Visualization Based Framework for Clustering Large Datasets. 2006 ;.  (0 bytes)
Random Space Encryption
Keke Chen, Ramakanth Kavuluru, Shumin Guo. RASP: Efficient Multidimensional Range Query on Attack-Resilient Encrypted Databases. In ACM Conference on Data and Application Security and Privacy (CODASPY) 2011. San Antonio, TX; 2011.  (316.57 KB)
Privacy-preserving protocols
Sagar Sharma, James Powers, Keke Chen. Privacy-Preserving Spectral Analysis of Large Graphs in Public Clouds. Asia Conference on Computer and Communications Security 2016. Xi'an, China: ACM; 2016. p. 71-82.
Privacy-preserving data mining
Keke Chen, Ling Liu. Geometric Data Perturbation for Privacy Preserving Outsourced Data Mining. Journal of Knowledge and Information Systems (KAIS). 2010 ;.  (1.21 MB)
Keke Chen, Ling Liu. Geometric Data Perturbation for Privacy Preserving Outsourced Data Mining. Journal of Knowledge and Information Systems (KAIS). 2011 ;.  (1.21 MB)
Privacy-preserving
Sagar Sharma, Keke Chen. Privacy-Preserving Boosting with Random Linear Classifiers. ACM Conference on Computer and Communications Security (CCS) 2018; 2018.  (724.46 KB)
Sagar Sharma, Keke Chen. Poster: Image Disguising for Privacy-preserving Deep Learning. ACM Conference on Computer and Communications Security (CCS) 2018; 2018.  (1.04 MB)
Privacy evaluation
Keke Chen, Ling Liu. Geometric Data Perturbation for Privacy Preserving Outsourced Data Mining. Journal of Knowledge and Information Systems (KAIS). 2010 ;.  (1.21 MB)
Keke Chen, Ling Liu. Geometric Data Perturbation for Privacy Preserving Outsourced Data Mining. Journal of Knowledge and Information Systems (KAIS). 2011 ;.  (1.21 MB)
parallel processing
Zohreh Alavi, Sagar Sharma, Lu Zhou, Keke Chen. Scalable Euclidean Embedding for Big Data. 2015 IEEE 8th International Conference on Cloud Computing. New York City, NY: IEEE; 2015. p. 773 - 780.
parallel algorithms
Zohreh Alavi, Sagar Sharma, Lu Zhou, Keke Chen. Scalable Euclidean Embedding for Big Data. 2015 IEEE 8th International Conference on Cloud Computing. New York City, NY: IEEE; 2015. p. 773 - 780.
Outsourced Database
Keke Chen, Ramakanth Kavuluru, Shumin Guo. RASP: Efficient Multidimensional Range Query on Attack-Resilient Encrypted Databases. In ACM Conference on Data and Application Security and Privacy (CODASPY) 2011. San Antonio, TX; 2011.  (316.57 KB)
our text clustering and knowledge extraction strategy grouped the retrieval results into informative clusters as revealed by the keywords and MeSH terms extracted from the documents in each cluster. <br /> <b>Conclusions</b>: The text mining system studi
Ling Liu, Keke Chen. Document Clustering and Ranking System for Exploring MEDLINE Citations. 2007 ;.  (0 bytes)
none has satisfactorily addressed the problem of Best K for categorical clustering. Since categorical data does not have an inherent distance function as the similarity measure
Ling Liu, Keke Chen. Best K: the Critical Clustering Structures in Categorical Data. 2008 ;.  (0 bytes)

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