CS 685: Recommended papers for presentation

Data Mining based Classification

1. ( Presenter: Mary E. Biddle) Discriminative Frequent Pattern Analysis for Effective Classification - Hong Cheng, Xifeng Yan, Jiawei Han and Chih-Wei Hsu

2. ( Presenter: Venkata Ramana Banda) Co-clustering based Classification for Out-of-domain Documents - Wenyuan Dai, Gui-Rong Xue, Qiang Yang, and Yong Yu

3. (Presenter: Casey Lengacher) Mining Optimal Decision Trees from Itemset Lattices - Siegfried Nijssen and Elisa Fromont

4. (Presenter: Arunava Bhattacharya) Show me the money! Deriving the Pricing Power of Product Features by Mining Consumer Reviews - Nikolay Archak, Anindya Ghose, and Panagiotis Ipeirotis

5. (Presenter: Satya Bulusu) Distributed Classification in Peer-to-Peer Networks. -Ping Luo, Hui Xiong

Graph Mining

1. (Presenter: Wenbin Li) A Framework For Community Identification in Dynamic Social Networks - Chayant Tantipathananandh, Tanya Y. Berger-Wolf, and David Kempe

2. (Presenter: Yinfang Zhuang) Cost-effective Outbreak Detection in Networks - Jure Leskovec, Andreas Krause, Carlos Guestrin, Christos Faloutsos, Jeanne VanBriesen, and Natalie Glance

3. (Presenter: Phani Yarlagadda) Correlation Search in Graph Databases - Yiping Ke, James Cheng, and Wilfred Ng

4. (Presenter: Nick Mattei) Finding Tribes: Identifying Close-Knit Individuals from Employment Patterns - Lisa Friedland and David Jensen

Joint Learning

1. A Spectral Clustering Approach to Optimally Combining Numerical Vectors with a Modular Network - Motoki Shiga, Ichigaku Takigawa, and Hiroshi Mamitsuka

2. Association Analysis-based Transformations for Protein Interaction Networks: A Function Prediction Case Study - Gaurav Pandey, Michael Steinbach, Rohit Gupta, Tushar Garg, and Vipin Kuma

3. (Presenter: Tim Meyers) Detecting research topics via the correlation between graphs and texts - Yookyung Jo, Carl Lagoze, and C. Lee Giles

4. (Presenter: Cindy Burklow) Dynamic hybrid clustering of bioinformatics by incorporating text mining and citation analysis - Frizo Janssens, Wolfgang Glnzel, and Bart De Moor

5. Enhancing Semi-Supervised Clustering: A Feature Projection Perspective - Wei Tang, Hui Xiong, Shi Zhong, and Jie Wu

6. (Presenter: Sandeep Gajjala) Corroborate and Learn Facts from the Web -Shubin Zhao, Jonathan Betz

Privacy preserving data mining

1. (Presenter: Lian Liu) Time Series Compressibility and Privacy - Spiros Papadimitriou, Feifei Li, George Kollios, Philip Yu

2. Privacy-Preservation for Gradient Descent Methods - Li Wan, Wee Keong Ng, Shuguo Han, and Vincent Lee

Bioinformatics

1. (Presenter: Elissaveta Arnaoudova) Automatic genome-wide reconstruction of phylogenetic gene trees -- Ilan Wapinski, Avi Pfeffer, Nir Friedman and Aviv Regev

2. (Presenter: Arthur Hall III) Annotating Gene Function by Combining Expression Data with a Modular Gene Network -- Motoki Shiga, Ichigaku Takigawa and Hiroshi Mamitsuka

3. A graph-based approach to systematically reconstruct human transcriptional regulatory modules -- Xifeng Yan, Michael Mehan, Yu Huang, Michael Waterman, Philip Yu and Jasmine Zhou

Paper recommended by students

1. (Presenter: Awasthi, Apurv) Mining Approximate frequent itemset in the presence of noise: algorithm and analysis - Jinze Liu, Susan Paulsen, Xing Sun, Wei Wang, Andrew Nobel, and Jan Prins

2. (Presenter: Wang XianWang) Local Fisher Discriminant Analysis for Supervised Dimensionality Reduction - Masashi Sugiyama

3. (Presenter: Song Yuan) Data Mining for  Network Intrusion Detection - Dokas, P., Ertoz, L., Kumar, V., Lazarevic, A., Srivastava, J., Tan, P\

4. (Presenter: Onur) Analysis of Firewall Policy Rules Using Data Mining Techniques

5. (Presenter: Jizhou Gao) Weighted Substructure Mining for Image Analysis, - Sebastian Nowozin, Koji Tsuda, Takeaki Uno, Taku Kudo, and Gokhan BakIr