Weimao Ke, Ph.D.


Contact Information

Education

Ph.D. - Information Science
University of North Carolina at Chapel Hill (2010)

M.A. - Information Science
Indiana University (2006)

B.E. - Chemical Engineering
East China University of Science & Technology (1998)

Biography

Dr. Ke’s research is centered on information retrieval (IR), particularly the investigation of intelligent systems that support better connection and interaction between people and information. His recent focus is on decentralized IR functions that can adapt and scale in continuously growing and increasingly interconnected information spaces. His broad interests also include complex networks/systems, text mining, information visualization, bibliometrics, machine learning, multi-agent systems, and the notion of information. Dr. Ke’s major teaching interests include IR, databases, data mining, software/web development, and complex systems.

Publications

Yongping Du, Jingxuan Liu, Weimao Ke, Xuemei Gong. Hierarchy construction and text classification based on the relaxation strategy and least information model. Expert Systems with Applications (2018).

Ke, Weimao. “Text Retrieval based on Least Information Measurement.” In ICTIR 2017: the 3rd ACM International Conference on the Theory of Information Retrieval, 1-10., 2017.

Gao, J., B. Song, W. Ke, and X. Hu. “BalanceAli: Multiple PPI Network Alignment with Balanced High Coverage and Consistency.” IEEE Transactions on NanoBioscience PP (2017), 16(5): 333 – 340.

Gao, Jianliang, Bo Song, Weimao Ke, Wanying Ding, and Xiaohua Hu. “Counter Deanonymization Query: H-index Based k-Anonymization Privacy Protection for Social Networks.” In ACM SIGIR 2017., 2017.

Ke, Weimao. “Distributed Search Efficiency and Robustness in Service-oriented Multi-agent Systems.” In International Conference on Management Engineering, Software Engineering and Service Sciences, 1-10. Wuhan, China: ACM ICPS, 2017.

Song, Bo, Jianliang Gao, Weimao Ke, and Xiaohua Hu. “Achieving High k-Coverage and k-Consistency in Global Alignment of Multiple PPI Networks.” In IEEE International Conference on Bioinformatics and Biomedicine (BIBM’16). Shenzhen, China: IEEE, 2016.

Gao, Jianliang, Bo Song, Ping Liu, Weimao Ke, Jianxin Wang, and Xiaohua Hu. Parallel Top-k Subgraph Query in Massive Graphs: Computing from the Perspective of Single Vertex In IEEE International Conference on Big Data. Washington, DC, 2016.

Ke, Weimao, and Javed Mostafa. Scalability Analysis of Distributed Search in Large Peer-to-peer Networks In IEEE International Conference on Big Data. Washington, DC, 2016.

Ke, Weimao. “Information-theoretic term weighting schemes for document clustering and classification.” International Journal on Digital Libraries 16, no. 2 (2015): 145-159.

Ke, Weimao, Xiaoli Song, Sheik Hassan, and Xuemei Gong. “Scalable Text Clustering with Partial Affinity Propagation on MapReduce.” In ACM WSDM 2015 Workshop on Scalable Data Analytics: Theory and Applications (SDATA’15), 1-9. Shanghai, China, 2015.

Gong, Xuemei, and Weimao Ke. “Term Weighting for Interactive Cluster Labeling based on Least Information Gain.” In ACM WSDM 2015 Workshop on Heterogeneous Information Access (HIA’15), 1-6. Shanghai, China, 2015.