Pang-Ning Tan

According to our database, Pang-Ning Tan authored at least 136 papers between 1999 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Conversational Agents as an Aid for Cancer Survivors' Information Search.

Barikisu Issaka, Young Anna Argyris, Pang-Ning Tan

Proceedings of the 57th Hawaii International Conference on System Sciences, 2024

2023

Self-Recover: Forecasting Block Maxima in Time Series from Predictors with Disparate Temporal Coverage Using Self-Supervised Learning.

Asadullah Hill Galib, Andrew McDonald, Pang-Ning Tan, Lifeng Luo

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Population Graph Cross-Network Node Classification for Autism Detection Across Sample Groups.

Anna Stephens, Francisco Santos, Pang-Ning Tan, Abdol-Hossein Esfahanian

Proceedings of the IEEE International Conference on Data Mining, 2023

Influence Propagation for Linear Threshold Model with Graph Neural Networks.

Francisco Santos, Anna Stephens, Pang-Ning Tan, Abdol-Hossein Esfahanian

Proceedings of the IEEE International Conference on Data Mining, 2023

SimEXT: Self-supervised Representation Learning for Extreme Values in Time Series.

Asadullah Hill Galib, Pang-Ning Tan, Lifeng Luo

Proceedings of the IEEE International Conference on Data Mining, 2023

2022

Beyond Point Prediction: Capturing Zero-Inflated & Heavy-Tailed Spatiotemporal Data with Deep Extreme Mixture Models.

Tyler Wilson, Andrew McDonald, Asadullah Hill Galib, Pang-Ning Tan, Lifeng Luo

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

FACS-GCN: Fairness-Aware Cost-Sensitive Boosting of Graph Convolutional Networks.

Francisco Santos, Junke Ye, Farzan Masrour, Pang-Ning Tan, Abdol-Hossein Esfahanian

Proceedings of the International Joint Conference on Neural Networks, 2022

COMET Flows: Towards Generative Modeling of Multivariate Extremes and Tail Dependence.

Andrew McDonald, Pang-Ning Tan, Lifeng Luo

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

DeepExtrema: A Deep Learning Approach for Forecasting Block Maxima in Time Series Data.

Asadullah Hill Galib, Andrew McDonald, Tyler Wilson, Lifeng Luo, Pang-Ning Tan

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Fairness-Aware Graph Sampling for Network Analysis.

Farzan Masrour, Francisco Santos, Pang-Ning Tan, Abdol-Hossein Esfahanian

Proceedings of the IEEE International Conference on Data Mining, 2022

Using Deep Learning to Identify Linguistic Features that Facilitate or Inhibit the Propagation of Anti- and Pro-Vaccine Content on Social Media.

Young Anna Argyris, Nan Zhang, Bidhan Bashyal, Pang-Ning Tan

Proceedings of the IEEE International Conference on Digital Health, 2022

DeepGPD: A Deep Learning Approach for Modeling Geospatio-Temporal Extreme Events.

Tyler Wilson, Pang-Ning Tan, Lifeng Luo

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

Unsupervised Anomaly Detection by Robust Density Estimation.

Boyang Liu, Pang-Ning Tan, Jiayu Zhou

Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021

Spatio-Temporal Multi-Task Learning via Tensor Decomposition.

Jianpeng Xu, Jiayu Zhou, Pang-Ning Tan, Xi Liu, Lifeng Luo

IEEE Trans. Knowl. Data Eng., 2021

Automated Analysis of the US Drought Monitor Maps With Machine Learning and Multiple Drought Indicators.

Pouyan Hatami Bahman Beiglou, Lifeng Luo, Pang-Ning Tan, Lisi Pei

Frontiers Big Data, 2021

JOHAN: A Joint Online Hurricane Trajectory and Intensity Forecasting Framework.

Ding Wang, Pang-Ning Tan

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

RCA: A Deep Collaborative Autoencoder Approach for Anomaly Detection.

Boyang Liu, Ding Wang, Kaixiang Lin, Pang-Ning Tan, Jiayu Zhou

Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, 2021

Learning Deep Neural Networks under Agnostic Corrupted Supervision.

Boyang Liu, Mengying Sun, Ding Wang, Pang-Ning Tan, Jiayu Zhou

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Convolutional Methods for Predictive Modeling of Geospatial Data.

Tyler Wilson, Pang-Ning Tan, Lifeng Luo

Proceedings of the 2020 SIAM International Conference on Data Mining, 2020

Fairness Perception from a Network-Centric Perspective.

Farzan Masrour, Pang-Ning Tan, Abdol-Hossein Esfahanian

Proceedings of the 20th IEEE International Conference on Data Mining, 2020

OMuLeT: Online Multi-Lead Time Location Prediction for Hurricane Trajectory Forecasting.

Ding Wang, Boyang Liu, Pang-Ning Tan, Lifeng Luo

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Bursting the Filter Bubble: Fairness-Aware Network Link Prediction.

Farzan Masrour, Tyler Wilson, Heng Yan, Pang-Ning Tan, Abdol-Hossein Esfahanian

Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019

Spatially Constrained Spectral Clustering Algorithms for Region Delineation.

Shuai Yuan, Pang-Ning Tan, Kendra Spence Cheruvelil, Sarah M. Collins, Patricia A. Soranno

CoRR, 2019

Deep Multi-view Information Bottleneck.

Qi Wang, Claire Boudreau, Qixing Luo, Pang-Ning Tan, Jiayu Zhou

Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

Augmented Multi-Task Learning by Optimal Transport.

Boyang Liu, Pang-Ning Tan, Jiayu Zhou

Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

Hierarchical LSTM Framework for Long-Term Sea Surface Temperature Forecasting.

Xi Liu, Tyler Wilson, Pang-Ning Tan, Lifeng Luo

Proceedings of the 2019 IEEE International Conference on Data Science and Advanced Analytics, 2019

You have been CAUTE!: early detection of compromised accounts on social media.

Courtland VanDam, Farzan Masrour, Pang-Ning Tan, Tyler Wilson

Proceedings of the ASONAM '19: International Conference on Advances in Social Networks Analysis and Mining, 2019

OPTANE: an OPtimal transport algorithm for NEtwork alignment.

Farzan Masrour, Pang-Ning Tan, Abdol-Hossein Esfahanian

Proceedings of the ASONAM '19: International Conference on Advances in Social Networks Analysis and Mining, 2019

Introduction to Data Mining (Second Edition)

Pang-Ning Tan, Michael S. Steinbach, Anuj Karpatne, Vipin Kumar

Pearson, 2019

2018

Receiver Operating Characteristic.

Pang-Ning Tan

Proceedings of the Encyclopedia of Database Systems, Second Edition, 2018

Neural Networks.

Pang-Ning Tan

Proceedings of the Encyclopedia of Database Systems, Second Edition, 2018

Diffusion size and structural virality: The effects of message and network features on spreading health information on twitter.

Jingbo Meng, Wei Peng, Pang-Ning Tan, Wuyu Liu, Ying Cheng, Arram Bae

Comput. Hum. Behav., 2018

STARS: Soft Multi-Task Learning for Activity Recognition from Multi-Modal Sensor Data.

Xi Liu, Pang-Ning Tan, Lei Liu

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2018

Enhancing Predictive Modeling of Nested Spatial Data through Group-Level Feature Disaggregation.

Boyang Liu, Pang-Ning Tan, Jiayu Zhou

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

MUSCAT: Multi-Scale Spatio-Temporal Learning with Application to Climate Modeling.

Jianpeng Xu, Xi Liu, Tyler Wilson, Pang-Ning Tan, Pouyan Hatami, Lifeng Luo

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018

A Low Rank Weighted Graph Convolutional Approach to Weather Prediction.

Tyler Wilson, Pang-Ning Tan, Lifeng Luo

Proceedings of the IEEE International Conference on Data Mining, 2018

Imputing Structured Missing Values in Spatial Data with Clustered Adversarial Matrix Factorization.

Qi Wang, Pang-Ning Tan, Jiayu Zhou

Proceedings of the IEEE International Conference on Data Mining, 2018

Distribution Preserving Multi-task Regression for Spatio-Temporal Data.

Xi Liu, Pang-Ning Tan, Zubin Abraham, Lifeng Luo, Pouyan Hatami

Proceedings of the IEEE International Conference on Data Mining, 2018

CADET: A Multi-View Learning Framework for Compromised Account Detection on Twitter.

Courtland VanDam, Pang-Ning Tan, Jiliang Tang, Hamid Karimi

Proceedings of the IEEE/ACM 2018 International Conference on Advances in Social Networks Analysis and Mining, 2018

Attributed Network Representation Learning Approaches for Link Prediction.

Farzan Masrour, Pang-Ning Tan, Abdol-Hossein Esfahanian, Courtland VanDam

Proceedings of the IEEE/ACM 2018 International Conference on Advances in Social Networks Analysis and Mining, 2018

2017

Online Multi-Task Learning Framework for Ensemble Forecasting.

Jianpeng Xu, Pang-Ning Tan, Jiayu Zhou, Lifeng Luo

IEEE Trans. Knowl. Data Eng., 2017

Understanding compromised accounts on Twitter.

Courtland VanDam, Jiliang Tang, Pang-Ning Tan

Proceedings of the International Conference on Web Intelligence, 2017

Automated classification of EEG signals for predicting students' cognitive state during learning.

Xi Liu, Pang-Ning Tan, Lei Liu, Steven J. Simske

Proceedings of the International Conference on Web Intelligence, 2017

Hash-Based Feature Learning for Incomplete Continuous-Valued Data.

Shuai Yuan, Pang-Ning Tan, Kendra Spence Cheruvelil, C. Emi Fergus, Nicholas K. Skaff, Patricia A. Soranno

Proceedings of the 2017 SIAM International Conference on Data Mining, 2017

Multi-level Multi-task Learning for Modeling Cross-Scale Interactions in Nested Geospatial Data.

Shuai Yuan, Jiayu Zhou, Pang-Ning Tan, C. Emi Fergus, Tyler Wagner, Patricia A. Soranno

Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

2016

Detecting hashtag hijacking from Twitter.

Courtland VanDam, Pang-Ning Tan

Proceedings of the 8th ACM Conference on Web Science, 2016

GSpartan: a Geospatio-Temporal Multi-task Learning Framework for Multi-location Prediction.

Jianpeng Xu, Pang-Ning Tan, Lifeng Luo, Jiayu Zhou

Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

Synergies that Matter: Efficient Interaction Selection via Sparse Factorization Machine.

Jianpeng Xu, Kaixiang Lin, Pang-Ning Tan, Jiayu Zhou

Proceedings of the 2016 SIAM International Conference on Data Mining, 2016

Macro-scale mobile app market analysis using customized hierarchical categorization.

Xi Liu, Han Hee Song, Mario Baldi, Pang-Ning Tan

Proceedings of the 35th Annual IEEE International Conference on Computer Communications, 2016

Crowdsourcing of network data.

Ding Wang, Prakash Mandayam Comar, Pang-Ning Tan

Proceedings of the 2016 International Joint Conference on Neural Networks, 2016

WISDOM: Weighted incremental spatio-temporal multi-task learning via tensor decomposition.

Jianpeng Xu, Jiayu Zhou, Pang-Ning Tan, Xi Liu, Lifeng Luo

Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016

2015

FORMULA: FactORized MUlti-task LeArning for task discovery in personalized medical models.

Jianpeng Xu, Jiayu Zhou, Pang-Ning Tan

Proceedings of the 2015 SIAM International Conference on Data Mining, Vancouver, BC, Canada, April 30, 2015

Constrained spectral clustering for regionalization: Exploring the trade-off between spatial contiguity and landscape homogeneity.

Shuai Yuan, Pang-Ning Tan, Kendra Spence Cheruvelil, Sarah M. Collins, Patricia A. Soranno

Proceedings of the 2015 IEEE International Conference on Data Science and Advanced Analytics, 2015

MF-Tree: Matrix Factorization Tree for Large Multi-Class Learning.

Lei Liu, Pang-Ning Tan, Xi Liu

Proceedings of the 24th ACM International Conference on Information and Knowledge Management, 2015

2014

Contour regression: A distribution-regularized regression framework for climate modeling.

Zubin Abraham, Pang-Ning Tan, Perdinan, Julie A. Winkler, Shiyuan Zhong, Malgorzata Liszewska

Stat. Anal. Data Min., 2014

ORION: Online Regularized Multi-task Regression and Its Application to Ensemble Forecasting.

Jianpeng Xu, Pang-Ning Tan, Lifeng Luo

Proceedings of the 2014 IEEE International Conference on Data Mining, 2014

Detecting malicious clients in ISP networks using HTTP connectivity graph and flow information.

Lei Liu, Sabyasachi Saha, Ruben Torres, Jianpeng Xu, Pang-Ning Tan, Antonio Nucci, Marco Mellia

Proceedings of the 2014 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 2014

2013

Clustering Social Networks Using Distance-Preserving Subgraphs.

Ronald Nussbaum, Abdol-Hossein Esfahanian, Pang-Ning Tan

Proceedings of the Influence of Technology on Social Network Analysis and Mining, 2013

Missing or Inapplicable: Treatment of Incomplete Continuous-valued Features in Supervised Learning.

Lei Liu, Prakash Mandayam Comar, Antonio Nucci, Sabyasachi Saha, Pang-Ning Tan

Proceedings of the 13th SIAM International Conference on Data Mining, 2013

Distribution Regularized Regression Framework for Climate Modeling.

Zubin Abraham, Malgorzata Liszewska, Perdinan, Pang-Ning Tan, Julie Winkler, Shiyuan Zhong

Proceedings of the 13th SIAM International Conference on Data Mining, 2013

Position Preserving Multi-Output Prediction.

Zubin Abraham, Pang-Ning Tan, Perdinan, Julie Winkler, Shiyuan Zhong, Malgorzata Liszewska

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2013

Combining supervised and unsupervised learning for zero-day malware detection.

Prakash Mandayam Comar, Lei Liu, Sabyasachi Saha, Pang-Ning Tan, Antonio Nucci

Proceedings of the IEEE INFOCOM 2013, Turin, Italy, April 14-19, 2013, 2013

2012

A framework for joint community detection across multiple related networks.

Prakash Mandayam Comar, Pang-Ning Tan, Anil K. Jain

Neurocomputing, 2012

Simultaneous classification and community detection on heterogeneous network data.

Prakash Mandayam Comar, Pang-Ning Tan, Anil K. Jain

Data Min. Knowl. Discov., 2012

Recursive NMF: Efficient label tree learning for large multi-class problems.

Lei Liu, Prakash Mandayam Comar, Sabyasachi Saha, Pang-Ning Tan, Antonio Nucci

Proceedings of the 21st International Conference on Pattern Recognition, 2012

Weighted linear kernel with tree transformed features for malware detection.

Prakash Mandayam Comar, Lei Liu, Sabyasachi Saha, Antonio Nucci, Pang-Ning Tan

Proceedings of the 21st ACM International Conference on Information and Knowledge Management, 2012

2011

On ontology-driven document clustering using core semantic features.

Samah Jamal Fodeh, William F. Punch, Pang-Ning Tan

Knowl. Inf. Syst., 2011

Detecting bots via incremental LS-SVM learning with dynamic feature adaptation.

Feilong Chen, Supranamaya Ranjan, Pang-Ning Tan

Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2011

LinkBoost: A Novel Cost-Sensitive Boosting Framework for Community-Level Network Link Prediction.

Prakash Mandayam Comar, Pang-Ning Tan, Anil K. Jain

Proceedings of the 11th IEEE International Conference on Data Mining, 2011

Smoothed Quantile Regression for Statistical Downscaling of Extreme Events in Climate Modeling.

Zubin Abraham, Pang-Ning Tan, Fan Xin

Proceedings of the 2011 Conference on Intelligent Data Understanding, 2011

Link-Based Network Mining.

Jerry Scripps, Ronald Nussbaum, Pang-Ning Tan, Abdol-Hossein Esfahanian

Proceedings of the Structural Analysis of Complex Networks, 2011

2010

Efficient Algorithm for Localized Support Vector Machine.

Haibin Cheng, Pang-Ning Tan, Rong Jin

IEEE Trans. Knowl. Data Eng., 2010

Constrained overlapping clusters: minimizing the negative effects of bridge-nodes.

Jerry Scripps, Pang-Ning Tan

Stat. Anal. Data Min., 2010

A Framework for Co-classification of Articles and Users in Wikipedia.

Lei Liu, Pang-Ning Tan

Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence, 2010

Identifying Cohesive Subgroups and Their Correspondences in Multiple Related Networks.

Prakash Mandayam Comar, Pang-Ning Tan, Anil Kumar Jain

Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence, 2010

An Integrated Framework for Simultaneous Classification and Regression of Time-Series Data.

Zubin Abraham, Pang-Ning Tan

Proceedings of the SIAM International Conference on Data Mining, 2010

Multi task learning on multiple related networks.

Prakash Mandayam Comar, Pang-Ning Tan, Anil Kumar Jain

Proceedings of the 19th ACM Conference on Information and Knowledge Management, 2010

Clustering Social Networks Using Distance-Preserving Subgraphs.

Ronald Nussbaum, Abdol-Hossein Esfahanian, Pang-Ning Tan

Proceedings of the International Conference on Advances in Social Networks Analysis and Mining, 2010

2009

Receiver Operating Characteristic.

Pang-Ning Tan

Proceedings of the Encyclopedia of Database Systems, 2009

Neural Networks.

Pang-Ning Tan

Proceedings of the Encyclopedia of Database Systems, 2009

Pattern Preserving Clustering.

Hui Xiong, Michael S. Steinbach, Pang-Ning Tan, Vipin Kumar, Wenjun Zhou

Proceedings of the Encyclopedia of Data Warehousing and Mining, Second Edition (4 Volumes), 2009

Detection and Characterization of Anomalies in Multivariate Time Series.

Haibin Cheng, Pang-Ning Tan, Christopher Potter, Steven A. Klooster

Proceedings of the SIAM International Conference on Data Mining, 2009

Combining statistics and semantics via ensemble model for document clustering.

Samah Jamal Fodeh, William F. Punch, Pang-Ning Tan

Proceedings of the 2009 ACM Symposium on Applied Computing (SAC), 2009

Measuring the effects of preprocessing decisions and network forces in dynamic network analysis.

Jerry Scripps, Pang-Ning Tan, Abdol-Hossein Esfahanian

Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Paris, France, June 28, 2009

A Semi-supervised Framework for Simultaneous Classification and Regression of Zero-Inflated Time Series Data with Application to Precipitation Prediction.

Zubin Abraham, Pang-Ning Tan

Proceedings of the ICDM Workshops 2009, 2009

A co-classification framework for detecting web spam and spammers in social media web sites.

Feilong Chen, Pang-Ning Tan, Anil K. Jain

Proceedings of the 18th ACM Conference on Information and Knowledge Management, 2009

A Matrix Alignment Approach for Collective Classification.

Jerry Scripps, Pang-Ning Tan, Feilong Chen, Abdol-Hossein Esfahanian

Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining, 2009

History-Based Email Prioritization.

Ronald Nussbaum, Abdol-Hossein Esfahanian, Pang-Ning Tan

Proceedings of the 2009 International Conference on Advances in Social Network Analysis and Mining, 2009

2008

Outrank: a Graph-Based Outlier Detection Framework Using Random Walk.

H. D. K. Moonesinghe, Pang-Ning Tan

Int. J. Artif. Intell. Tools, 2008

Link Mining for a Social Bookmarking Web Site.

Feilong Chen, Jerry Scripps, Pang-Ning Tan

Proceedings of the 2008 IEEE / WIC / ACM International Conference on Web Intelligence, 2008

Semi-supervised learning with data calibration for long-term time series forecasting.

Haibin Cheng, Pang-Ning Tan

Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2008

Maximum Margin Active Learning for Sequence Labeling with Different Length.

Haibin Cheng, Ruofei Zhang, Yefei Peng, Jianchang Mao, Pang-Ning Tan

Proceedings of the Advances in Data Mining. Medical Applications, 2008

A matrix alignment approach for link prediction.

Jerry Scripps, Pang-Ning Tan, Feilong Chen, Abdol-Hossein Esfahanian

Proceedings of the 19th International Conference on Pattern Recognition (ICPR 2008), 2008

A Robust Graph-Based Algorithm for Detection and Characterization of Anomalies in Noisy Multivariate Time Series.

Haibin Cheng, Pang-Ning Tan, Christopher Potter, Steven A. Klooster

Proceedings of the Workshops Proceedings of the 8th IEEE International Conference on Data Mining (ICDM 2008), 2008

Data mining for visual exploration and detection of ecosystem disturbances.

Haibin Cheng, Pang-Ning Tan, Christopher Potter, Steven A. Klooster

Proceedings of the 16th ACM SIGSPATIAL International Symposium on Advances in Geographic Information Systems, 2008

Detecting Ecosystem Disturbances and Land Cover Change Using Data Mining.

Shyam Boriah, Vipin Kumar, Michael S. Steinbach, Pang-Ning Tan, Christopher Potter, Steven A. Klooster

Proceedings of the Next Generation of Data Mining., 2008

2007

Kernel Based Detection of Mislabeled Training Examples.

Hamed Valizadegan, Pang-Ning Tan

Proceedings of the Seventh SIAM International Conference on Data Mining, 2007

Localized Support Vector Machine and Its Efficient Algorithm.

Haibin Cheng, Pang-Ning Tan, Rong Jin

Proceedings of the Seventh SIAM International Conference on Data Mining, 2007

A Probabilistic Substructure-Based Approach for Graph Classification.

H. D. K. Moonesinghe, Hamed Valizadegan, Samah Jamal Fodeh, Pang-Ning Tan

Proceedings of the 19th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2007), 2007

Incorporating Background Knowledge for Subjective Rule Evaluation.

Samah Jamal Fodeh, Pang-Ning Tan

Proceedings of the 19th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2007), 2007

Exploration of Link Structure and Community-Based Node Roles in Network Analysis.

Jerry Scripps, Pang-Ning Tan, Abdol-Hossein Esfahanian

Proceedings of the 7th IEEE International Conference on Data Mining (ICDM 2007), 2007

Recommendation via Query Centered Random Walk on K-Partite Graph.

Haibin Cheng, Pang-Ning Tan, Jon Sticklen, William F. Punch

Proceedings of the 7th IEEE International Conference on Data Mining (ICDM 2007), 2007

A Prototype-driven Framework for Change Detection in Data Stream Classification.

Hamed Valizadegan, Pang-Ning Tan

Proceedings of the IEEE Symposium on Computational Intelligence and Data Mining, 2007

2006

TAPER: A Two-Step Approach for All-Strong-Pairs Correlation Query in Large Databases.

Hui Xiong, Shashi Shekhar, Pang-Ning Tan, Vipin Kumar

IEEE Trans. Knowl. Data Eng., 2006

Local Detection of Selfish Routing Behavior in Ad Hoc Networks.

Bo Wang, Sohraab Soltani, Jonathan K. Shapiro, Pang-Ning Tan

J. Interconnect. Networks, 2006

Hyperclique pattern discovery.

Hui Xiong, Pang-Ning Tan, Vipin Kumar

Data Min. Knowl. Discov., 2006

Clustering in the Presence of Bridge-Nodes.

Jerry Scripps, Pang-Ning Tan

Proceedings of the Sixth SIAM International Conference on Data Mining, 2006

Semi-Supervised Clustering with Partial Background Information.

Jing Gao, Pang-Ning Tan, Haibin Cheng

Proceedings of the Sixth SIAM International Conference on Data Mining, 2006

A Novel Framework for Incorporating Labeled Examples into Anomaly Detection.

Jing Gao, Haibin Cheng, Pang-Ning Tan

Proceedings of the Sixth SIAM International Conference on Data Mining, 2006

Semi-supervised outlier detection.

Jing Gao, Haibin Cheng, Pang-Ning Tan

Proceedings of the 2006 ACM Symposium on Applied Computing (SAC), 2006

Multistep-Ahead Time Series Prediction.

Haibin Cheng, Pang-Ning Tan, Jing Gao, Jerry Scripps

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2006

Outlier Detection Using Random Walks.

H. D. K. Moonesinghe, Pang-Ning Tan

Proceedings of the 18th IEEE International Conference on Tools with Artificial Intelligence (ICTAI 2006), 2006

Adaptively Routing P2P Queries Using Association Analysis.

Brian D. Connelly, Christopher W. Bowron, Li Xiao, Pang-Ning Tan, Chen Wang

Proceedings of the 2006 International Conference on Parallel Processing (ICPP 2006), 2006

Frequent Closed Itemset Mining Using Prefix Graphs with an Efficient Flow-Based Pruning Strategy.

H. D. K. Moonesinghe, Samah Jamal Fodeh, Pang-Ning Tan

Proceedings of the 6th IEEE International Conference on Data Mining (ICDM 2006), 2006

Converting Output Scores from Outlier Detection Algorithms into Probability Estimates.

Jing Gao, Pang-Ning Tan

Proceedings of the 6th IEEE International Conference on Data Mining (ICDM 2006), 2006

2005

An Incremental Data Stream Clustering Algorithm Based on Dense Units Detection.

Jing Gao, Jianzhong Li, Zhaogong Zhang, Pang-Ning Tan

Proceedings of the Advances in Knowledge Discovery and Data Mining, 2005

Introduction to Data Mining

Pang-Ning Tan, Michael S. Steinbach, Vipin Kumar

Addison-Wesley, ISBN: 0-321-32136-7, 2005

2004

Data Mining.

Vipin Kumar, Pang-Ning Tan, Michael S. Steinbach

Proceedings of the Handbook of Data Structures and Applications., 2004

Selecting the right objective measure for association analysis.

Pang-Ning Tan, Vipin Kumar, Jaideep Srivastava

Inf. Syst., 2004

HICAP: Hierarchical Clustering with Pattern Preservation.

Hui Xiong, Michael S. Steinbach, Pang-Ning Tan, Vipin Kumar

Proceedings of the Fourth SIAM International Conference on Data Mining, 2004

RBA: An Integrated Framework for Regression based on Association Rules.

Aysel Ozgur, Pang-Ning Tan, Vipin Kumar

Proceedings of the Fourth SIAM International Conference on Data Mining, 2004

Exploiting a support-based upper bound of Pearson's correlation coefficient for efficiently identifying strongly correlated pairs.

Hui Xiong, Shashi Shekhar, Pang-Ning Tan, Vipin Kumar

Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2004

Ordering patterns by combining opinions from multiple sources.

Pang-Ning Tan, Rong Jin

Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2004

Generalizing the notion of support.

Michael S. Steinbach, Pang-Ning Tan, Hui Xiong, Vipin Kumar

Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2004

Support envelopes: a technique for exploring the structure of association patterns.

Michael S. Steinbach, Pang-Ning Tan, Vipin Kumar

Proceedings of the Tenth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2004

Mining interesting contrast rules for a web-based educational system.

Behrouz Minaei-Bidgoli, Pang-Ning Tan, William F. Punch

Proceedings of the 2004 International Conference on Machine Learning and Applications, 2004

2003

Discovery of climate indices using clustering.

Michael S. Steinbach, Pang-Ning Tan, Vipin Kumar, Steven A. Klooster, Christopher Potter

Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 24, 2003

Mining Strong Affinity Association Patterns in Data Sets with Skewed Support Distribution.

Hui Xiong, Pang-Ning Tan, Vipin Kumar

Proceedings of the 3rd IEEE International Conference on Data Mining (ICDM 2003), 2003

2002

Discovery of Web Robot Sessions Based on their Navigational Patterns.

Pang-Ning Tan, Vipin Kumar

Data Min. Knowl. Discov., 2002

High Performance Data Mining.

Vipin Kumar, Mahesh V. Joshi, Eui-Hong Han, Pang-Ning Tan, Michael S. Steinbach

Proceedings of the High Performance Computing for Computational Science, 2002

Selecting the right interestingness measure for association patterns.

Pang-Ning Tan, Vipin Kumar, Jaideep Srivastava

Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2002

2001

Mining Indirect Associations in Web Data.

Pang-Ning Tan, Vipin Kumar

Proceedings of the WEBKDD 2001, 2001

2000

Web Usage Mining: Discovery and Applications of Usage Patterns from Web Data.

Jaideep Srivastava, Robert Cooley, Mukund Deshpande, Pang-Ning Tan

SIGKDD Explor., 2000

Indirect Association: Mining Higher Order Dependencies in Data.

Pang-Ning Tan, Vipin Kumar, Jaideep Srivastava

Proceedings of the Principles of Data Mining and Knowledge Discovery, 2000

Textual data mining of service center call records.

Pang-Ning Tan, Hannah Blau, Steven A. Harp, Robert P. Goldman

Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining, 2000

1999

Discovery of Interesting Usage Patterns from Web Data.

Robert Cooley, Pang-Ning Tan, Jaideep Srivastava

Proceedings of the Web Usage Analysis and User Profiling, 1999