Welcome to Data Mining Laboratory in Department of Computer Science at KAIST. The main theme of our lab is Large-scale Data Mining, and research interests include but are not limited to devising scalable algorithms for big graph (tensor) mining, and developing large-scale graph mining platforms.
3 regular papers are accepted to CIKM 2014, one of the top data mining conferences.
Ph.D. student Ha-Myung Park won the HumanTech award (bronze) from Samsung. His paper is titled "An Efficient MapReduce Algorithm for Triangulation in a Very Large Graph" and it proposed an efficient MapReduce algorithm for finding triangles in large graphs.
Ph.D. student Yongsub Lim won the grant award from the "Venture Research Program for Graduate and PhD Students" from KAIST, for his proposal on distributed real time graph stream mining. The grant is highly selective (10 students in KAIST this year), and aimed for providing active support for creative and influential ideas that entail high risk.
MS student Inah Jeon won the 2013 Qualcomm Innovation Award. The award is a fellowship given to high quality papers. Her paper is titled "GigaTensor: Scaling Tensor Analysis Up By 100 Times - Algorithms and Discoveries" and it focused on the tensor analysis for finding patterns and anomalies in billion-scale real-world tensor using Hadoop.
Prof. U Kang won Honorable Mention for the 2013 KDD Dissertation Award, which is the highest honor for a data mining thesis. His dissertation is titled "Mining Tera-Scale Graphs: Theory, Engineering and Discoveries" and it focused on the award winning PEGASUS system for finding patterns and anomalies in billion-node graphs using thousands of machines. U received a certificate of recognition during the opening ceremonies at the upcoming KDD Conference in Chicago.