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    邵俊明

    • 教授 博士生导师
    • 性别:男
    • 毕业院校:慕尼黑大学
    • 学历:博士研究生毕业
    • 学位:理学博士学位
    • 在职信息:在岗
    • 所在单位:计算机科学与工程学院(网络空间安全学院)
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    参考资料

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    Outlier/Noisy object Detection

    Related references:

    ●    Shao, J., He, X., Boehm, C., Yang, Q. and Plant, C.:Synchronization-inspired Partitioning and Hierarchical Clustering, IEEE Transactions on Knowledge and Data Engineering, 25(4): 893-905. 2013. [Code]    

    ●    Shao, J., He, X., Yang, Q., Plant, C. and Boehm, C.:Robust Synchronization-Based Graph Clustering, 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining, 249-260, 2013. [Code]    

    ●    Shao, J:Synchronization on Data Mining, LAP LAMBERT Academic Publishing, 2012.    

    ●    Shao, J., Yang, Q., Boehm, C. and Plant, C.:Detection of Arbitrarily Oriented Synchronized Clusters in High-dimensional Data, IEEE International Conference on Data Mining (ICDM), pp. 607-616, 2011. [Code]    

    ●    Boehm, C., Plant, C., Shao, J.* and Yang, Q.:Clustering by synchronization, Proceedings of the 16th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2010), 583-592, 2010. [Code]    

    ●    Shao, J., Boehm, C., Yang, Q. and Plant, C.:Synchronization Based Outlier Detection, Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD 2010), 245-260, 2010. [Code]    

    Data Mining on Brain Data

    1. Fiber Clustering

    Chanllenges –  Effective Fiber Similarity Measure (Dynamic Time Wraping),   Clustering on Multiple Scales (Hierarchical clustering) –  Noisy Fibers Handling (Outlier robustness)


          

    Hierarchical Fiber Clustering [IJDB 2010] [Best Paper Award]

    Related Papers:

    ●    Shao, J., Hahn, K., Yang, Q., Wohlschlaeger, A., Boehm, C., Myers, N. and Plant, C.:Hierarchical Density-based Clustering of White Matter Tracts in the Human Brain, International Journal of Knowledge Discovery in Bioinformatics 1(4), 1-26, 2010. [Code]    

    ●    Shao, J., Hahn, K., Yang, Q., Boehm, C., Wohlschlaeger, A., Myers, N. and Plant, C.:Combining Time Series Similarity with Density-Based Clustering to Identify Fiber Bundles in the Human Brain, Proceedings of International Conference on Data Mining (ICDM), Workshop on Biological Data Mining and its Applications in Healthcare, 747-754, 2010.    

    ●    Shao, J, Wohlschläger, A, Hahn, C, Boehm, C, and Plant, C.:Density-based Clustering of White Matter Tracts in the Human Brain with Dynamic Time Warping, European Workshop on Mining Massive Data Sets (EMMDS ), pp. 1101-1108,2009.    

    2. Disease Diagnosis

     

    ISCN-based AD prediction. [Shao et. al., Neurobiology of Aging, 2012]

    Related Papers:

    ●    Shao, J., Myers, N., Yang, Q., Feng, J., Plant, C., Böhm, C., Förstl, H., Kurz, A., Zimmer, C., Meng, C., Riedl, V., Wohlschläger, A. and Sorg, C.:Prediction of Alzheimer’s disease using individual structural connectivity networks, Neurobiology of Aging, 33(12):2756-2765, 2012.    

    ●    Meng, C., Brandl, F., Tahmasian, M., Shao, J., Manoliu, A., Scherr, M., … & Sorg, C.:Aberrant topology of striatum’s connectivity is associated with the number of episodes in depression, Brain 2014: 137; 598–609.    

    ●    Shao, J., Hahn, K., Yang, Q., Wohlschlaeger, A., Boehm, C., Myers, N. and Plant, C.:Hierarchical Density-based Clustering of White Matter Tracts in the Human Brain, International Journal of Knowledge Discovery in Bioinformatics 1(4), 1-26, 2010.    


    ●    Shao, J, Yang, Q, Wohlschlaeger, A, and Sorg, C.:Insight into Disrupted Spatial Patterns of Human Connectome in Alzheimer’s Disease via Subgraph Mining, International Journal of Knowledge Discovery in Bioinformatics, 3(1):14-29, 2013.    

    ●    Tahmasian, M., Knight, D. C., Manoliu, A., Schwerthöffer, D., Scherr, M., Meng, C., … & Sorg, C.:Aberrant intrinsic connectivity of hippocampus and amygdala overlap in the fronto-insular and dorsomedial-prefrontal cortex in major depressive disorder, Frontiers in human neuroscience, 7, 2013.    

    ●    Shao J., Yang Q., Wohlschlaeger A. and Sorg C.:Discovering Aberrant Patterns of Human Connectome in Alzheimer’s Disease via Subgraph Mining, IEEE International Conference on Data Mining (ICDM), Workshop on Biological Data Mining and its Applications in Healthcare (BioDM), pp. 86-93,