##
__Tina Eliassi-Rad's Publications__

The Why, How, and When of Representations for Complex Systems (with L. Torres, A. Sizemore Blevins, and D.S. Bassett), *SIAM Review* (SIREV), 2021 (in press)

Nonbacktracking Eigenvalues under Node Removal: X-Centrality and Targeted Immunization (with L. Torres, K.S. Chan, and H. Tong), *SIAM Journal on Mathematics of Data Science* (SIMODS), 2021 (in press)

Selective Network Discovery via Deep Reinforcement Learning on Embedded Spaces (with P. Morales and R. Caceres), *Applied Network Science*, Volume 6, Article 24, 2021.

RAWLSNET: Altering Bayesian Networks to Encode Rawlsian Fair Equality of Opportunity (with D. Liu, Z. Shafi, W. Fleisher, and S. Alfeld), *Proceedings of the 2021 AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society * (AIES), May 2021.

POTION: Optimizing Graph Structure for Targeted Diffusion (with S. Yu, L. Torres, S. Alfeld, and Y. Vorobeychik), *Proceedings of the 2021 SIAM Data Mining Conference* (SDM), May 2021.

Collaborative Information Sharing for ML-Based Threat Detection (with T. Ongun, S. Boboila, A. Oprea, A. Nottingham, J. Hiser, and J. Davidson), *The 2021 SIAM SDM Workshop on AI for Cybersecurity* (AI4CS), April 2021.

PATHATTACK: Attacking Shortest Paths in Complex Networks (with B.A. Miller, Z. Shafi, W. Ruml, Y. Vorobeychik, and S. Alfeld), arXiv:2104.03761v1, April 2021.

Exploring Impossibility Results for Algorithmic Fairness Using PrSAT (with B. Fitelson), Technical Report, March 2021.

Understanding the Limitations of Network Online Learning (with T. LaRock, T. Sakharov, and S. Bhadra), *Applied Network Science* 5:60, Springer Open, 2020.

What Science Can Do For Democracy: A Complexity Science Approach (with H. Farrell, D. Garcia, S. Lewandowsky, P. Palacios, D. Ross, D. Sornette, K. Thebault, and K. Wiesner), *Humanities & Social Sciences Communications* 7, Article 30, 2020, Nature.

GLEE: Geometric Laplacian Eigenmap Embedding (with L. Torres and K. S. Chan), *Journal of Complex Networks* 8(2), cnaa007, 2020, Oxford University Press.

Residual Core Maximization: An Efficient Algorithm for Maximizing the Size of the k-Core (with R. Laishram, A.E. Sariyüce, A. Pinar, and S. Soundarajan), *Proceedings of the 2020 SIAM International Conference on Data Mining* (SDM 2020), 2020.

HYPA: Efficient Detection of Path Anomalies in Time Series Data on Networks (with T. LaRock, V. Nanumyan, I. Scholtes, G. Casiraghi, and F. Schweitzer), *Proceedings of the 2020 SIAM International Conference on Data Mining* (SDM 2020), 2020.

Reshaping A Nation: Mobility, Commuting, and Contact Patterns during the COVID-19 Outbreak (with B. Klein, T. LaRock, S. McCabe, L. Torres, L. Friedland, F. Privitera, B. Lake, M.U.G. Kraemer, J. S. Brownstein, D. Lazer, S.V. Scarpino, A. Vespignani, and M. Chinazzi), Network Science Institute Technical Report. Northeastern University, Boston, MA, May 2020.

Assessing Changes in Commuting and Individual Mobility in Major Metropolitan Areas in the United States during the COVID-19 Outbreak (with B. Klein, T. LaRock, S. McCabe, L. Torres, F. Privitera, B. Lake, M.U.G. Kraemer, J.S. Brownstein, D. Lazer, S.V. Scarpino, M. Chinazzi, and A. Vespignani), Network Science Institute Technical Report. Northeastern University, Boston, MA, March 2020.

Topological Effects on Attacks Against Vertex Classification (with B.A. Miller, M. Çamurcu, A.J. Gomez, and K.S. Chan), arXiv:2003.05822v1, March 2020.

Deep Reinforcement Learning for Task-driven Discovery of Incomplete Networks (with P. Morales and R. S. Caceres), *Proceedings of the 8th International Conference on Complex Networks and their Applications* (Complex Networks 2019), Lisbon, Portugal, December 2019, Springer Verlag.

Success in Books: Predicting Book Sales Before Publication (with X. Wang, B. Yucesoy, O. Varol, and A.-L. Barabási), *EPJ Data Science* 8:31, Springer Open, October 2019.

Improving Robustness to Attacks Against Vertex Classification (with B.A. Miller, M. Çamurcu, A. Gomez, and K. Chan), *The 15th International Workshop on Mining and Learning with Graphs* (MLG'19; held in conjunction with KDD'19), Anchorage, AL, August 2019. [**Best Paper Award**]

L2P: An Algorithm for Estimating Heavy-tailed Outcomes (with X. Wang and O. Varol), arXiv:1908.04628v1, August 2019.

Non-backtracking Cycles: Length Spectrum Theory and Graph Mining Applications (with L. Torres and P. Suárez-Serrato), *Applied Network Science* 4:41, Springer Open, 2019.

Multilevel Network Alignment (with
S. Zhang, H. Tong, and R. Maciejewski), *Proceedings of the 2019 World Wide Web Conference* (WWW'19), San Francisco, CA, May 2019.

Stability of Democracies: A Complex Systems Perspective (with
K. Wiesner, A. Birdi, H. Farrell, D. Garcia, S. Lewandowsky, P. Palacios, D. Ross, D. Sornette, and K. Thébault), *European Journal of Physics*, November 2018. (Press Release)

Robustness Analysis and Anomaly Detection of Interdependent Physical and Social Networks (with T. Abdelzaher, J. Han, and C. Faloutsos), Technical Report (HDTRA1-10-1-0120), University of Illinois Urbana-Champaign, September 2018.

Reducing Network Incompleteness Through Online Learning: A Feasibility Study (with T. LaRock, T. Sakharov, and S. Bhadra), *The 14th International Workshop on Mining and Learning with Graphs* (MLG'18; held in conjunction with KDD'18), London, United Kingdon, August 2018.

Measuring and Improving the Core Resilience of Networks (with R. Laishram, A.E. Sariyüce, A. Pinar, and S. Soundarajan), *Proceedings of the 2018 World Wide Web Conference* (WWW'18), Lyon, France, April 2018.

Patterns and Anomalies in K-cores of Real-world Graphs with Applications (with K. Shin and C. Faloutsos), *Knowledge and Information Systems* 54(3): 677-710, 2018.

ε-WGX: Adaptive Edge Probing for Enhancing Incomplete Networks (with S. Soundarajan, A. Pinar, and B. Gallagher), *Proceedings of the 2017 ACM on Web Science Conference* (WebSci'17), Troy, NY, June 2017.

CoreScope: Graph Mining Using k-Core Analysis--Patterns, Anomalies, and Algorithms (with K. Shin and C. Faloutsos), *Proceedings of the 16th IEEE International Conference on Data Mining* (ICDM'16), Barcelona, Spain, December 2016.

Some Advances in Role Discovery in Graphs (with S. Gilpin, C.-T. Kuo, and I. Davidson), arXiv:1609.02646v1, September 2016.

MaxReach: Reducing Network Incompleteness through Node Probes (with S. Soundarajan, B. Gallagher, and A. Pinar), *Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining* (ASONAM'16), San Francisco, CA, August 2016.

NimbleCore: A Space-efficient External Memory Algorithm for Estimating Core Numbers
(with P. Govindan, S. Soundarajan, and C. Faloutsos), *Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining* (ASONAM'16), San Francisco, CA, August 2016.

GOTCHA! Network-based Fraud Detection for Social Security Fraud (with V. Van Vlasselaer, L. Akoglu, M. Snoeck, and B. Baesens), *Management Science*, pp 1-21, July 2016. [permalink]

Eigen-Optimization on Large Graphs by Edge Manipulation (with C. Chen, H. Tong, B.A. Prakash, M. Faloutsos, and C. Faloutsos), *ACM Transactions on Knowledge Discovery in Data* (TKDD), 10(4), Article 49, June 2016.

Current and Future Challenges in Mining Large Networks: Report on the Second SDM Workshop on Mining Networks and Graphs (with L.B. Holder, R. Caceres, D.F. Gleich, E.J. Riedy, M. Khan, N.V. Chawla, R. Kumar, Y. Wu, C. Klymko, and B.A. Prakash), *SIGKDD Explorations* 18(1): 39-45 (2016).

Fast Best-Effort Search on Graphs with Multiple Attributes (with S. Basu Roy and S. Papadimitriou), *Proceedings of the 32nd IEEE International Conference on Data Engineering* (ICDE'16), Helsinki, Finland, May 2016. [Extended abstract of our 2015 TKDE article.]

Generating Graph Snapshots from Streaming Edge Data (with S. Soundarajan, A. Tamersoy, E.B. Khalil, D.H. Chau, B. Gallagher, and K. Roundy), *Proceedings of the 25th International World Wide Web Conference* (WWW'16), Montreal, Canada, April 2016.

Node Immunization on Large Graphs: Theory and Algorithms (with C. Chen, H. Tong, B.A. Prakash, C.E. Tsourakakis, C. Faloutsos, D.H. Chau), *IEEE Transactions on Knowledge and Data Engineering* (TKDE), 28(1):113-126, 2016.

MaxOutProbe: An Algorithm for Increasing the Size of Partially Observed Networks (with S. Soundarajan, B. Gallagher, and A. Pinar), *NIPS Workshop on Networks in the Social and Information Sciences*, Montreal, Canada, December 2015.

A Probabilistic Model for Using Social Networks in Personalized Item Recommendation (with A. Chaney and D. Blei), *Proceedings of the 9th ACM Recommender Systems Conference* (RecSys'15), Vienna, Austria, September 2015.

AFRAID: Fraud Detection via Active Inference in Time-evolving Social Networks (with V. Van Vlasselaer, L. Akoglu, M. Snoeck, and B. Baesens), *Proceedings of the 7th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining* (ASONAM'15, Industrial Track), Paris, France, August 2015.

Minimizing Dissemination in a Population While Maintaining its Community Structure (with C. Zhang), *The 1st ACM SIGKDD Workshop on Population Informatics for Big Data* (PopInfo'15), Sydney, Australia, August 2015.

APATE: A Novel Approach for Automated Credit Card Transaction Fraud Detection using Network-Based Extensions (with C. Bravo, V. Van Vlasselaer, O. Caelen, L. Akoglu, M. Snoeck, and B. Baesens), * Decision Support Systems* (DSS), 75: 38-48, 2015.

MET: A Fast Algorithm for Minimizing Propagation in Large Graphs with Small Eigen-Gaps (with L.T. Le and H. Tong), * Proceedings of the 2015 SIAM International Conference on Data Mining * (SDM'15), Vancouver, British Columbia, Canada, April 2015.

EP-MEANS: An Efficient Nonparametric Clustering of Empirical Probability Distributions (with K. Henderson and B. Gallagher), * Proceedings of the 30th ACM SIGAPP Symposium On Applied Computing * (SAC'15), Salamanca, Spain, April 2015.

Guilt-by-Constellation: Fraud Detection by Suspicious Clique Memberships (with V. Van Vlasselaer, L. Akoglu, M. Snoeck, and B. Baesens), * Proceedings of the 48th Annual Hawaii International Conference on System Sciences* (HICSS'15), Kauai, HI, January 2015.

Fast Best-Effort Search on Graphs with Multiple Attributes (with S. Basu Roy and S. Papadimitriou), * IEEE Transactions on Knowledge and Data Engineering* (TKDE), 27(3):755-768, 2015.

A Proposal for Decreasing Geographical Inequality in College Admissions (with B. Fitelson), Chapter 12 Appendix in *The Future of Affirmative Action*, Eds: J. Renker and J. Miller, The Century Foundation Press, 2014.

Threatening Privacy across Social Graphs: A Structural Features Approach (with P. Govindan, J. Xu, S. Hill, and C. Volinsky), * Proceedings of the 14th IEEE International Conference on Data Mining (ICDM) Workshops*, Shenzhen, China, December 2014. (Presented at DaMNet'14: *Workshop on Data Mining in Networks*)

Finding the Most Appropriate Auxiliary Data for Social Graph De-anonymization (with P. Govindan and S. Soundarajan), * The 1st ACM SIGKDD Workshop on Data Ethics*, New York, NY, August 2014.

Measuring Coverage and Divergence of Reading Behaviors Among Friends (with L.T. Le), * The 1st ACM SIGKDD Workshop on Data Science for News Publishing* (NewsKDD'14), New York, NY, August 2014.

A Guide to Selecting a Network Similarity Method (with S. Soundarajan and B. Gallagher), * Proceedings of the 2014 SIAM International Conference on Data Mining* (SDM'14), Philadelphia, PA, April 2014.

Social Order in Online Social Networks, *Encyclopedia of Social Network Analysis and Mining*, Springer, 2014: 1918-1920.

Hyperlocal: Inferring Location of IP Addresses in Real-time Bid Requests for Mobile Ads (with L.T. Le, F. Provost, and L. Moores), * Proceedings of the 6th ACM SIGSPATIAL International Workshop on Location-Based Social Networks* (LBSN'13), Orlando, FL, November 2013.

Network Similarity via Multiple Social Theories (with M. Berlingerio, D. Koutra, and C. Faloutsos), * Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining* (ASONAM'13), Niagara Falls, Canada, August 2013. [Long version]

Guided Learning for Role Discovery (GLRD): Framework, Algorithms, and Applications
(with S. Gilpin and I. Davidson),
* Proceedings of the 19th ACM SIGKDD Conference
on Knowledge Discovery and Data Mining* (KDD'13), Chicago, IL, August 2013.

Entelecheia: Detecting P2P Botnets in their Waiting Stage
(with H. Hang, X. Wei, and M. Faloutsos),
* Proceedings of the 12th IEEE IFIP Networking Conference* (Networking'13), Brooklyn, NY, May 2013.

Gelling, and Melting, Large Graphs by Edge Manipulation
(with H. Tong, B.A. Prakash, M. Faloutsos, and C. Faloutsos),
* Proceedings of the 21st ACM Conference on Information and Knowledge Management* (CIKM'12), Maui, HI, October 2012. [**Best Paper Award**]

RolX: Structural Role Extraction and Mining in Large Networks
(with K. Henderson, B. Gallagher, H. Tong, S. Basu, L. Akoglu, D. Koutra, C. Faloutsos, and L. Li),
* Proceedings of the 18th ACM SIGKDD Conference
on Knowledge Discovery and Data Mining* (KDD'12), Beijing, China, August 2012. [**Code is available in SNAP.**]

Measuring Tie Strength in Implicit Social Networks
(with M. Gupte),
* Proceedings of the 4th ACM International Conference on Web Science* (WebSci'12), Evanston, IL, June 2012.
[Appeared as a poster at the *2011 NIPS Workshop on
Computational Social Science and the Wisdom of Crowds*, and as an extended abstract in the *Notes of the 3rd Workshop on Information in Networks*
(WIN'11), New York, NY, September 2011.]

Gateway Finder in Large Graphs: Problem Definitions and Fast Solutions
(with H. Tong, S. Papadimitriou, C. Faloutsos, and P.S. Yu),
* Information Retrieval*, 15(3-4): 391-411, 2012.

Correcting Evaluation Bias of Relational Classifiers with Network Cross Validation
(with J. Neville, B. Gallagher, and T. Wang),
* Knowledge and Information Systems (KAIS)*, 30(1): 31-55, 2012.

Correcting Bias in Statistical Tests for Network Classifier Evaluation
(with T. Wang, J. Neville, and B. Gallagher),
*Proceedings of the 2011 European Conference on Machine Learning & Principles and Practice of Knowledge Discovery in Databases* (ECML-PKDD'11), Athens, Greece, September 2011.

It's Who You Know: Graph Mining Using Recursive Structural Features
(with K. Henderson, B. Gallagher, L. Li, L. Akoglu, H. Tong, and C. Faloutsos),
*Proceedings of the 17th ACM SIGKDD Conference on Knowledge Discovery and Data Mining*
(KDD'11), San Diego, CA, August 2011.

Ranking Information in Networks
(with K. Henderson),
*Proceedings of the 2011 International Conference on Social Computing, Behavioral-Cultural Modeling, & Prediction*
(SBP'11), College Park, MD, March 2011. [Extended abstract in the *Notes of the 2nd Workshop on Information in Networks* (WIN'10), New York, NY, September 2010.]

Massively Parallel Acceleration of a Document-Similarity Classifier to Detect Web Attacks
(with C. Ulmer, M. Gokhale, B. Gallagher, and P. Top),
* Journal of Parallel and Distributed Computing*, 71(2): 225-235, 2011.

Detecting Novel Discrepancies in Communication Networks
(with J. Abello and N. Devanur),
* Proceedings of the 10th IEEE International Conference on Data Mining* (ICDM'10), Sydney, Australia, December 2010.
[Extended abstract
in the *Notes of the 2nd Workshop on Information in Networks*
(WIN'10), New York, NY, September 2010.]

On the Vulnerability of Large Graphs: Measures and Fast Immunization Algorithms
(with H. Tong, B.A. Prakash, C. Tsourakakis, C. Faloutsos, and D.H. Chau),
* Proceedings of the 10th IEEE International
Conference on Data Mining* (ICDM'10), Sydney, Australia, December 2010.

Profiling-by-Association: A Resilient Traffic Profiling Solution for the Internet Backbone
(with M. Iliofotou, B. Gallagher, G. Xie, and M. Faloutsos),
* Proceedings of the 6th ACM International Conference on Emerging Networking Experiments and Technologies* (CoNEXT'10), Philadelphia, PA, November 2010.

A Renewal Theory Approach to Anomaly Detection in Communication Networks
(with B. Thompson),
* Notes of the 2nd Workshop on Information in Networks*
(WIN'10), New York, NY, September 2010.

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*
(SBP'10), Bethesda, MD, March 2010. [Extended abstract in the * Notes of the 1st Workshop on Information in Networks* (WIN'09), New York, NY, September 2009.]

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), 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**]

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'09), 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.

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*
(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* (SNAKDD'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), * Proceedings of the 2007 IEEE International Conference on Data Mining (ICDM) Workshops*, Omaha, NE, October 2007. (Presented at MGCS'07: the * Workshop on Mining Graphs and Complex Structures*),

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* (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.