Tina Eliassi-Rad's Publications

  • MetricForensics: A Multi-Level Approach for Mining Volatile Graphs (with K. Henderson, C. Faloutsos, L. Akoglu, L. Li, K. Maruhashi, B.A. Prakash, and H. Tong), Proceedings of the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'10), Washington, DC, July 2010.

  • Basset: Scalable Gateway Finder in Large Graphs (with H. Tong, S. Papadimitriou, C. Faloutsos, and P. Yu), Proceedings of the 14th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD'10), Hyderabad, India, June 2010.

  • HCDF: A Hybrid Community Discovery Framework (with K. Henderson, S. Papadimitriou, and C. Faloutsos), Proceedings of the 2010 SIAM Conference on Data Mining (SDM'10), Columbus, OH, April 2010.

  • Literature Search through Mixed-Membership Community Discovery (with K. Henderson), Proceedings of the 2010 International Conference on Social Computing, Behavioral Modeling, and Prediction (SBP10), Bethesda, MD, March 2010. (An extended version of the 2009 WIN Workshop presentation)

  • Homophily in Application Layer and its Usage in Traffic Classification (with B. Gallagher, M. Iliofotou, and M. Faloutsos), Proceedings of the 29th IEEE Conference on Computer Communications (INFOCOM'10) Miniconference, San Diego, CA, March 2010. (Long version)

  • Continuous Time Group Discovery in Dynamic Graphs (with K. Miller), NIPS 2009 Workshop on Analyzing Networks and Learning with Graphs, Whistler, BC, Canada, December 2009.

  • Evaluating Statistical Tests for Within-Network Classifiers of Relational Data (with J. Neville and B. Gallagher), Proceedings of the 9th IEEE International Conference on Data Mining (ICDM'09), Miami, FL, December 2009. (Best Paper Award Runner-up)

  • Literature Search through Mixed-Membership Community Discovery (with K. Henderson), Notes of the 1st Workshop on Information in Networks (WIN), New York, NY, September 2009.

  • DAPA-V10: Discovery and Analysis of Patterns and Anomalies in Volatile Time-Evolving Networks (with B. Thompson), Notes of the 1st Workshop on Information in Networks (WIN), New York, NY, September 2009.

  • Leveraging Label-Independent Features for Classification in Sparsely Labeled Networks: An Empirical Study (with B. Gallagher), Lecture Notes in Computer Science: Advances in Social Network Mining and Analysis, Springer, 2009 (forthcoming).

  • Classification of HTTP Attacks: A Study on the ECML/PKDD 2007 Discovery Challenge (with B. Gallagher), Technical Report LLNL-TR-414570, Lawrence Livermore National Laboratory, Livermore, CA, July 2009.

  • PaCK: Scalable Parameter-Free Clustering on K-Partite Graphs (with J. He, H. Tong, S. Papadimitriou, C. Faloutsos, J. Carbonell), Proceedings of the 2009 SIAM SDM Workshop on Link Analysis, Counterterrorism and Security, Reno, NV, May 2009.

  • Applying Latent Dirichlet Allocation to Group Discovery in Large Graphs (with K. Henderson), Proceedings of the 24th Annual ACM Symposium on Applied Computing (ACM-SAC'09), Honolulu, HI, March 2009.

  • Solving the Top-K Problem with Fixed-Memory Heuristic Search (with K. Henderson), Technical Report LLNL-TR-410187, Lawrence Livermore National Laboratory, Livermore, CA, January 2009. (Updated 2010 version)

  • GRAPHITE: A Visual Query System for Large Graphs (with D. H. Chau, C. Faloutsos, H. Tong, J. Hong, and B. Gallagher), Proceedings of the 8th IEEE International Conference on Data Mining (ICDM'08), Pisa, Italy, December 2008.

  • Fast Mining of Complex Time-Stamped Events (with H. Tong, Y. Sakurai, and C. Faloutsos), Proceedings of the 17th ACM Conference on Information and Knowledge Management (CIKM'08), Napa Valley, CA, October 2008.

  • Two Heads Better than One: Pattern Discovery in Time-evolving Multi-Aspect Data (with J. Sun, C. Tsourakakis, E. Hoke, and C. Faloutsos), Proceedings of the 2008 European Conference on Machine Learning & Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD'08), Antwerp, Belgium, September 2008. Also appears in Data Mining and Knowledge Discovery Journal, 17(1):111-128, 2008.

  • Collective Classification in Network Data (with P. Sen, G. Namata, M. Bilgic, L. Getoor, and B. Gallagher), AI Magazine, Special Issue on AI and Networks, 29(3):93-106, 2008.

  • Using Ghost Edges for Classification in Sparsely Labeled Networks (with B. Gallagher, H. Tong, and C. Faloutsos), Proceedings of the Fourteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'08), Las Vegas, NV, August 2008.

  • Leveraging Label-Independent Features for Classification in Sparsely Labeled Networks: An Empirical Study (with B. Gallagher), Proceedings of the Second ACM SIGKDD Workshop on Social Network Mining and Analysis (SNA-KDD'08), Las Vegas, NV, August 2008.

  • Finding Mixed-Memberships in Social Networks (with P.S. Koutsourelakis), Papers from the 2008 AAAI Spring Symposium on Social Information Processing (AAAI-SS'08), Stanford, CA, March 2008.

  • An Evaluation of Experimental Methodology for Classifiers of Relational Data (with B. Gallagher), 2007 IEEE International Conference on Data Mining, Workshop on Mining Graphs and Complex Structures (MGCS'07), Omaha, NE, October 2007.

  • Fast Best-Effort Pattern Matching in Large Attributed Graphs (with H. Tong, B. Gallagher, and C. Faloutsos), Proceedings of the Thirteenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'07), San Jose, CA, 2007, pp. 737-746.

  • A Position Paper: Value of Information for Evidence Detection. (with D.L. Roberts), Papers from the 2006 AAAI Fall Symposium on Capturing and Using Patterns for Evidence Detection (AAAI-FS'06), AAAI Press, Washington, D.C., October, 2006.

  • Visual Analysis of Large Heterogeneous Social Networks by Semantic and Structural Abstraction (with Z. Shen and K.-L. Ma), IEEE Transactions on Visualization and Computer Graphics, Special Issue on Visual Analytics, 12(6): 1427-1439, 2006

  • Similarity in Computational Sciences (with T. Critchlow), Abstracts from the 2005 Learning Workshop (invited contribution), Snowbird, UT, April 5-8, 2005.

  • Knowledge Representation Issues in Semantic Graphs for Relationship Detection (with M. Barthelemy and E. Chow), Papers from the 2005 AAAI Spring Symposium on AI Technologies for Homeland Security (AAAI-SS'05), AAAI Press, Stanford, CA, 2005, pp. 91-98.

  • A Hybrid Approach to Multiresolution Modeling of Large-Scale Scientific Data (with T. Critchlow), Proceedings of the Twentieth Annual ACM Symposium on Applied Computing (ACM SAC'05), Santa Fe, NM, 2005, pp. 511-518.

  • Statistical Modeling of Large-Scale Scientific Simulation Data (with C. Baldwin, G. Abdulla, and T. Critchlow), New Generation of Data Mining Applications, Eds: J. Zurada and M. Kantardzic, IEEE Press/Wiley Publishers, February 2005.

  • Using Ontological Information to Accelerate Path-Finding in Large Semantic Graphs: A Probabilistic Approach (with E. Chow), Technical Report UCRL-CONF-202002, Lawrence Livermore National Laboratory, Livermore, CA, 2005.

  • Multivariate Clustering of Large-Scale Scientific Simulation Data (with T. Critchlow), Technical Report UCRL-JC-151860-REV-1, Lawrence Livermore National Laboratory, Livermore, CA, 2003.

  • A System for Building Intelligent Agents that Learn to Retrieve and Extract Information (with J. Shavlik), International Journal on User Modeling and User-Adapted Interaction, Special Issue on User Modeling and Intelligent Agents, 13, 2003, pp. 35-88.

  • The Evolution of a Hierarchical Partitioning Algorithm for Large-Scale Scientific Data: Three Steps of Increasing Complexity (with C. Baldwin, G. Abdulla, and T. Critchlow), Proceedings of the Fifteenth International Conference on Scientific and Statistical Data Base Management (SSDBM'03), Cambridge, MA, 2003.

  • Intelligent Web Agents that Learn to Retrieve and Extract Information (with J. Shavlik), Intelligent Exploration of the Web, Eds: P.S. Szczepaniak, F. Segovia, J. Kacprzyk, and L.A. Zadeh, Springer-Verlag Publishers, 2003.

  • Statistical Modeling of Large-Scale Simulation Data (with T. Critchlow and G. Abdulla), Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD'02), Edmonton, Alberta, Canada, 2002.

  • Building Intelligent Agents that Learn to Retrieve and Extract Information. PhD Thesis. Computer Sciences Department. University of Wisconsin, Madison, WI, 2001.

  • A Theory-Refinement Approach to Information Extraction (with J. Shavlik), Proceedings of the Eighteenth International Conference on Machine Learning (ICML'01), Williamstown, MA, 2001.

  • An Instructable, Adaptive Interface for Discovering and Monitoring Information on the World Wide Web (with J. Shavlik, S. Calcari, and J. Solock), Proceedings of the 1999 International Conference on Intelligent User Interfaces (IUI'99), Redondo Beach, CA, 1999.

  • Using a Trained Text Classifier to Extract Information (with J. Shavlik), Technical Report, July 1999.

  • Intelligent Agents for Web-Based Tasks: An Advice-Taking Approach (with J. Shavlik), Working Notes of the AAAI/ICML'98 Workshop on Learning for Text Categorization, Madison, WI, 1998.

  • Building Intelligent Agents for Web-Based Tasks: A Theory-Refinement Approach (with J. Shavlik), Presented at the Conf on Automated Learning and Discovery Workshop on Learning from Text and the Web (CONALD'98), Pittsburgh, PA, 1998.

  • Visual Support for the ISLE Simulation Environment. Master's Thesis. Department of Computer Science. University of Illinois, Urbana, IL, 1995.