Pang-Ning Tan

Ronald Nussbaum, Abdol-Hossein Esfahanian, Pang-Ning Tan: Clustering Social Networks Using Distance-Preserving Subgraphs. The Influence of Technology on Social Network Analysis and Mining 2013: 331-349

Prakash Mandayam Comar, Pang-Ning Tan, Anil K. Jain: Simultaneous classification and community detection on heterogeneous network data. Data Min. Knowl. Discov. 25(3): 420-449 (2012)

Prakash Mandayam Comar, Pang-Ning Tan, Anil K. Jain: A framework for joint community detection across multiple related networks. Neurocomputing 76(1): 93-104 (2012)

Prakash Mandayam Comar, Lei Liu, Sabyasachi Saha, Antonio Nucci, Pang-Ning Tan: Weighted linear kernel with tree transformed features for malware detection. CIKM 2012: 2287-2290

Lei Liu, Prakash Mandayam Comar, Sabyasachi Saha, Pang-Ning Tan, Antonio Nucci: Recursive NMF: Efficient label tree learning for large multi-class problems. ICPR 2012: 2148-2151

Pang-Ning Tan, Sanjay Chawla, Chin Kuan Ho, James Bailey (Eds.): Advances in Knowledge Discovery and Data Mining - 16th Pacific-Asia Conference, PAKDD 2012, Kuala Lumpur, Malaysia, May 29-June 1, 2012, Proceedings, Part I. Lecture Notes in Computer Science 7301, Springer 2012, isbn 978-3-642-30216-9

Pang-Ning Tan, Sanjay Chawla, Chin Kuan Ho, James Bailey (Eds.): Advances in Knowledge Discovery and Data Mining - 16th Pacific-Asia Conference, PAKDD 2012, Kuala Lumpur, Malaysia, May 29 - June 1, 2012, Proceedings, Part II. Lecture Notes in Computer Science 7302, Springer 2012, isbn 978-3-642-30219-0

Samah Jamal Fodeh, William F. Punch, Pang-Ning Tan: On ontology-driven document clustering using core semantic features. Knowl. Inf. Syst. 28(2): 395-421 (2011)

Zubin Abraham, Pang-Ning Tan, Fan Xin: Smoothed Quantile Regression for Statistical Downscaling of Extreme Events in Climate Modeling. CIDU 2011: 92-106

Prakash Mandayam Comar, Pang-Ning Tan, Anil K. Jain: LinkBoost: A Novel Cost-Sensitive Boosting Framework for Community-Level Network Link Prediction. ICDM 2011: 131-140

Feilong Chen, Supranamaya Ranjan, Pang-Ning Tan: Detecting bots via incremental LS-SVM learning with dynamic feature adaptation. KDD 2011: 386-394

Jerry Scripps, Pang-Ning Tan: Constrained overlapping clusters: minimizing the negative effects of bridge-nodes. Statistical Analysis and Data Mining 3(1): 20-37 (2010)

Haibin Cheng, Pang-Ning Tan, Rong Jin: Efficient Algorithm for Localized Support Vector Machine. IEEE Trans. Knowl. Data Eng. 22(4): 537-549 (2010)

Ronald Nussbaum, Abdol-Hossein Esfahanian, Pang-Ning Tan: Clustering Social Networks Using Distance-Preserving Subgraphs. ASONAM 2010: 380-385

Prakash Mandayam Comar, Pang-Ning Tan, Anil Kumar Jain: Multi task learning on multiple related networks. CIKM 2010: 1737-1740

Zubin Abraham, Pang-Ning Tan: An Integrated Framework for Simultaneous Classification and Regression of Time-Series Data. SDM 2010: 653-664

Lei Liu, Pang-Ning Tan: A Framework for Co-classification of Articles and Users in Wikipedia. Web Intelligence 2010: 212-215

Prakash Mandayam Comar, Pang-Ning Tan, Anil Kumar Jain: Identifying Cohesive Subgroups and Their Correspondences in Multiple Related Networks. Web Intelligence 2010: 476-483

Jerry Scripps, Pang-Ning Tan, Feilong Chen, Abdol-Hossein Esfahanian: A Matrix Alignment Approach for Collective Classification. ASONAM 2009: 155-159

Ronald Nussbaum, Abdol-Hossein Esfahanian, Pang-Ning Tan: History-Based Email Prioritization. ASONAM 2009: 364-365

Feilong Chen, Pang-Ning Tan, Anil K. Jain: A co-classification framework for detecting web spam and spammers in social media web sites. CIKM 2009: 1807-1810

Zubin Abraham, Pang-Ning Tan: A Semi-supervised Framework for Simultaneous Classification and Regression of Zero-Inflated Time Series Data with Application to Precipitation Prediction. ICDM Workshops 2009: 644-649

Jerry Scripps, Pang-Ning Tan, Abdol-Hossein Esfahanian: Measuring the effects of preprocessing decisions and network forces in dynamic network analysis. KDD 2009: 747-756

Samah Jamal Fodeh, William F. Punch, Pang-Ning Tan: Combining statistics and semantics via ensemble model for document clustering. SAC 2009: 1446-1450

Haibin Cheng, Pang-Ning Tan, Christopher Potter, Steven A. Klooster: Detection and Characterization of Anomalies in Multivariate Time Series. SDM 2009: 413-424

Hui Xiong, Michael Steinbach, Pang-Ning Tan, Vipin Kumar, Wenjun Zhou: Pattern Preserving Clustering. Encyclopedia of Data Warehousing and Mining 2009: 1505-1510

Pang-Ning Tan: Neural Networks. Encyclopedia of Database Systems 2009: 1906-1909

Pang-Ning Tan: Receiver Operating Characteristic. Encyclopedia of Database Systems 2009: 2349-2352

H. D. K. Moonesinghe, Pang-Ning Tan: Outrank: a Graph-Based Outlier Detection Framework Using Random Walk. International Journal on Artificial Intelligence Tools 17(1): 19-36 (2008)

Haibin Cheng, Pang-Ning Tan, Christopher Potter, Steven A. Klooster: Data mining for visual exploration and detection of ecosystem disturbances. GIS 2008: 60

Haibin Cheng, Pang-Ning Tan, Christopher Potter, Steven A. Klooster: A Robust Graph-Based Algorithm for Detection and Characterization of Anomalies in Noisy Multivariate Time Series. ICDM Workshops 2008: 349-358

Jerry Scripps, Pang-Ning Tan, Feilong Chen, Abdol-Hossein Esfahanian: A matrix alignment approach for link prediction. ICPR 2008: 1-4

Haibin Cheng, Ruofei Zhang, Yefei Peng, Jianchang Mao, Pang-Ning Tan: Maximum Margin Active Learning for Sequence Labeling with Different Length. ICDM 2008: 345-359

Haibin Cheng, Pang-Ning Tan: Semi-supervised learning with data calibration for long-term time series forecasting. KDD 2008: 133-141

Feilong Chen, Jerry Scripps, Pang-Ning Tan: Link Mining for a Social Bookmarking Web Site. Web Intelligence 2008: 169-175

Hamed Valizadegan, Pang-Ning Tan: A Prototype-driven Framework for Change Detection in Data Stream Classification. CIDM 2007: 88-95

Haibin Cheng, Pang-Ning Tan, Jon Sticklen, William F. Punch: Recommendation via Query Centered Random Walk on K-Partite Graph. ICDM 2007: 457-462

Jerry Scripps, Pang-Ning Tan, Abdol-Hossein Esfahanian: Exploration of Link Structure and Community-Based Node Roles in Network Analysis. ICDM 2007: 649-654

Samah Jamal Fodeh, Pang-Ning Tan: Incorporating Background Knowledge for Subjective Rule Evaluation. ICTAI (2) 2007: 148-155

H. D. K. Moonesinghe, Hamed Valizadegan, Samah Jamal Fodeh, Pang-Ning Tan: A Probabilistic Substructure-Based Approach for Graph Classification. ICTAI (1) 2007: 346-349

Haibin Cheng, Pang-Ning Tan, Rong Jin: Localized Support Vector Machine and Its Efficient Algorithm. SDM 2007

Hamed Valizadegan, Pang-Ning Tan: Kernel Based Detection of Mislabeled Training Examples. SDM 2007

Hui Xiong, Pang-Ning Tan, Vipin Kumar: Hyperclique pattern discovery. Data Min. Knowl. Discov. 13(2): 219-242 (2006)

Bo Wang, Sohraab Soltani, Jonathan K. Shapiro, Pang-Ning Tan: Local Detection of Selfish Routing Behavior in Ad Hoc Networks. Journal of Interconnection Networks 7(1): 133-146 (2006)

Hui Xiong, Shashi Shekhar, Pang-Ning Tan, Vipin Kumar: TAPER: A Two-Step Approach for All-Strong-Pairs Correlation Query in Large Databases. IEEE Trans. Knowl. Data Eng. 18(4): 493-508 (2006)

Jing Gao, Pang-Ning Tan: Converting Output Scores from Outlier Detection Algorithms into Probability Estimates. ICDM 2006: 212-221

H. D. K. Moonesinghe, Samah Jamal Fodeh, Pang-Ning Tan: Frequent Closed Itemset Mining Using Prefix Graphs with an Efficient Flow-Based Pruning Strategy. ICDM 2006: 426-435

Brian D. Connelly, Christopher W. Bowron, Li Xiao, Pang-Ning Tan, Chen Wang: Adaptively Routing P2P Queries Using Association Analysis. ICPP 2006: 281-288

H. D. K. Moonesinghe, Pang-Ning Tan: Outlier Detection Using Random Walks. ICTAI 2006: 532-539

Haibin Cheng, Pang-Ning Tan, Jing Gao, Jerry Scripps: Multistep-Ahead Time Series Prediction. PAKDD 2006: 765-774

Jing Gao, Haibin Cheng, Pang-Ning Tan: Semi-supervised outlier detection. SAC 2006: 635-636

Jing Gao, Haibin Cheng, Pang-Ning Tan: A Novel Framework for Incorporating Labeled Examples into Anomaly Detection. SDM 2006

Jing Gao, Pang-Ning Tan, Haibin Cheng: Semi-Supervised Clustering with Partial Background Information. SDM 2006

Jerry Scripps, Pang-Ning Tan: Clustering in the Presence of Bridge-Nodes. SDM 2006

Pang-Ning Tan, Michael Steinbach, Vipin Kumar: Introduction to Data Mining. Addison-Wesley 2005, isbn 0-321-32136-7

Bo Wang, Sohraab Soltani, Jonathan K. Shapiro, Pang-Ning Tan: Local Detection of Selfish Routing Behavior in Ad Hoc Networks. ISPAN 2005: 392-399

Jing Gao, Jianzhong Li, Zhaogong Zhang, Pang-Ning Tan: An Incremental Data Stream Clustering Algorithm Based on Dense Units Detection. PAKDD 2005: 420-425

Pang-Ning Tan, Vipin Kumar, Jaideep Srivastava: Selecting the right objective measure for association analysis. Inf. Syst. 29(4): 293-313 (2004)

Behrouz Minaei-Bidgoli, Pang-Ning Tan, William F. Punch: Mining interesting contrast rules for a web-based educational system. ICMLA 2004: 320-327

Michael Steinbach, Pang-Ning Tan, Vipin Kumar: Support envelopes: a technique for exploring the structure of association patterns. KDD 2004: 296-305

Hui Xiong, Shashi Shekhar, Pang-Ning Tan, Vipin Kumar: Exploiting a support-based upper bound of Pearson's correlation coefficient for efficiently identifying strongly correlated pairs. KDD 2004: 334-343

Michael Steinbach, Pang-Ning Tan, Hui Xiong, Vipin Kumar: Generalizing the notion of support. KDD 2004: 689-694

Pang-Ning Tan, Rong Jin: Ordering patterns by combining opinions from multiple sources. KDD 2004: 695-700

Aysel Ozgur, Pang-Ning Tan, Vipin Kumar: RBA: An Integrated Framework for Regression based on Association Rules. SDM 2004

Hui Xiong, Michael Steinbach, Pang-Ning Tan, Vipin Kumar: HICAP: Hierarchical Clustering with Pattern Preservation. SDM 2004

Hui Xiong, Pang-Ning Tan, Vipin Kumar: Mining Strong Affinity Association Patterns in Data Sets with Skewed Support Distribution. ICDM 2003: 387-394

Michael Steinbach, Pang-Ning Tan, Vipin Kumar, Steven A. Klooster, Christopher Potter: Discovery of climate indices using clustering. KDD 2003: 446-455

Pang-Ning Tan, Vipin Kumar: Discovery of Web Robot Sessions Based on their Navigational Patterns. Data Min. Knowl. Discov. 6(1): 9-35 (2002)

Pang-Ning Tan, Vipin Kumar, Jaideep Srivastava: Selecting the right interestingness measure for association patterns. KDD 2002: 32-41

Vipin Kumar, Mahesh V. Joshi, Eui-Hong Han, Pang-Ning Tan, Michael Steinbach: High Performance Data Mining. VECPAR 2002: 111-125

Pang-Ning Tan, Vipin Kumar: Mining Indirect Associations in Web Data. WEBKDD 2001: 145-166

Jaideep Srivastava, Robert Cooley, Mukund Deshpande, Pang-Ning Tan: Web Usage Mining: Discovery and Applications of Usage Patterns from Web Data. SIGKDD Explorations 1(2): 12-23 (2000)

Pang-Ning Tan, Hannah Blau, Steven A. Harp, Robert P. Goldman: Textual data mining of service center call records. KDD 2000: 417-423

Pang-Ning Tan, Vipin Kumar, Jaideep Srivastava: Indirect Association: Mining Higher Order Dependencies in Data. PKDD 2000: 632-637

Robert Cooley, Pang-Ning Tan, Jaideep Srivastava: Discovery of Interesting Usage Patterns from Web Data. WEBKDD 1999: 163-182