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DIAL Publications

2017

  1. Jermaine Marshall, Arturo Argueta, Dong Wang. “A Neural Network Approach for Truth Discovery in Social Sensing.” IEEE 14th International Conference on Mobile Ad Hoc and Sensor Systems (MASS) 2017, 2017 PDF
  2. Saebi, Mandana, Jian Xu, Lance M. Kaplan, Bruno Ribeiro, and Nitesh V. Chawla. “Efficient Modeling of Higher-order Dependencies in Networks: From Algorithm to Application for Anomaly Detection.” ArXiv, (2017). PDF
  3. Huang, Hong, Yuxiao Dong, Jie Tang, Hongxia Yang, Nitesh V. Chawla, and Xiaoming Fu. “Will Triadic Closure Strengthen Ties in Social Networks?.” ACM Transactions on Knowledge Discovery from Data (TKDD), 12(3): 30., 2017. PDF
  4. Daheng Wang, Meng Jiang, Xueying Wang, Nitesh Chawla, Paul Brunts. “Multifaceted Event Analysis on Cross-Media Network Data.” 1st International Workshop On Heterogenous Networks Analysis and Mining (HeteroNAM), 2017. PDF
  5. Jun Tao, Chaoli Wang, Nitesh V. Chawla, Lei Shi, and Seung Hyun Kim. “Semantic Flow Graph: A Framework for Discovering Object Relationships in Flow Fields.” IEEE Transactions on Visualization and Computer Graphics, 2017. PDF
  6. Yuxiao Dong, Nitesh V. Chawla, Jie Tang, Yang Yang, Yang Yang. “User Modeling on Demographic Attributes in Big Mobile Social Networks.” ACM Transactions on Information Systems (TOIS), 35(4): 35, 2017. PDF
  7. Keith Feldman, Louis Faust, Xian Wu, Chao Huang, Nitesh V. Chawla. “Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline.” Towards Integrative Machine Learning and Knowledge Extraction. Springer, Cham: 150-169., 2017. PDF arXiv
  8. Saurabh Nagrecha, Pamela Bilo Thomas, Keith Feldman, Nitesh V. Chawla. “Predicting Chronic Heart Failure Using Diagnoses Graphs.” International Cross-Domain Conference for Machine Learning and Knowledge Extraction (CD-MAKE). Springer, Cham, 2017. PDF
  9. Shazia Afzal, Bikram Sengupta, Munira Syed, Nitesh Chawla, G. Alex Ambrose and Malolan Chetlur. “The ABC of MOOCs: Affect and its Inter-play with Behaviour and Cognition.” Proceedings of the 7th Affective Computing and Intelligent Interaction (ACII), 2017. PDF
  10. Pingjie Tang, Jed Pitera, Dmitry Zubarev, Nitesh V. Chawla. “Heterogeneous Materials Information Network Construction and Relevance Search.” Proceedings of the 4th IEEE International Conference on Data Science and Advanced Analytics (DSAA) Best Paper Award, 2017. PDF
  11. Abstract
  12. Frederick Nwanganga, Mandana Saebi, Gregory Madey, Nitesh Chawla. “A Minimum-Cost Flow Model for Workload Optimization on Cloud Infrastructure.” Proceedings of the 10th International Conference on Cloud Computing (Cloud), 2017. arXiv
  13. Chuxu Zhang, Lu Yu, Xiangliang Zhang, Nitesh Chawla. “ImWalkMF: Joint Matrix Factorization and Implicit Walk Integrative Learning for Recommendation.” Proceedings of the IEEE International Conference on Big Data (Big Data), 2017.
  14. Xian Wu, Yuxiao dong, Jun Tao, Chao Huang, Nitesh Chawla. “Fake Review Detection via Modeling Temporal and Behavioral Patterns.” Proceedings of the IEEE International Conference on Big Data (Big Data), 2017.
  15. Shuo Wang, Jieyun Song, Yide Yang, Yining Zhang, Nitesh V. Chawla,, Jun Ma and Haijun Wang. “Interaction between obesity and the Hypoxia Inducible Factor 3 Alpha Subunit rs3826795 polymorphism in relation with plasma alanine aminotransferase.” BMC medical genetics 18(1): 80, 2017. PDF
  16. Xian Wu, Yuxiao dong, Chao Huang, Jian Xu, Nitesh Chawla. “UAPD: Predicting Urban Anomalies from Spatial-Temporal Data.” Proceedings of the European Conference on Machine Learning & Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2017. PDF
  17. Aastha Nigam, Henry K. Dambanemuya, Madhav Joshi, Nitesh Chawla. “Harvesting Social Signals to Inform Peace Processes Implementation and Monitoring.” Big data Journal, 5(4): 337-355, 2017. PDF
  18. Yuxiao Dong, Hao Ma, Zhihong Shen, and Kuansan Wang. “A Century of Science: Globalization of Scientific Collaborations, Citations, and Innovations.” Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2017. arXiv PDF
  19. Yuxiao Dong, Nitesh V. Chawla, and Ananthram Swami. “metapath2vec: Scalable Representation Learning for Heterogeneous Networks.” Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2017. PDF
  20. Yuxiao Dong, Reid A. Johnson, Jian Xu, and Nitesh V. Chawla. “Structural Diversity and Homophily: A Study Across More Than One Hundred Big Networks.” Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), 2017. arXiv PDF
  21. Alberto Fernández, Sara del Río, Nitesh V. Chawla, and Francisco Herrera. “An Insight into Imbalanced Big Data Classification: Outcomes and Challenges.” Complex & Intelligent Systems, 3(2):105–120, 2017. PDF
  22. Md Mursalin, Yuan Zhang, Yuehui Chen, and Nitesh V. Chawla. “Automated Epileptic Seizure Detection Using Improved Correlation-based Feature Selection with Random Forest Classifier.” Neurocomputing, 241:204–214, 2017. PDF
  23. Chao Huang, Dong Wang, and Nitesh V. Chawla. “Scalable Uncertainty-Aware Truth Discovery in Big Data Social Sensing Applications for Cyber-Physical Systems.” IEEE Transactions on Big Data (TBD), 2017. PDF
  24. Louis Faust, Rachael Purta, David Hachen, Aaron Striegel, Christian Poellabauer, Omar Lizardo, and Nitesh V. Chawla. “Exploring Compliance: Observations from a Large Scale Fitbit Study.” Proceedings of the 2nd International Workshop on Social Sensing (SocialSens), 2017. PDF
  25. Jun Tao, Jian Xu, Chaoli Wang, and Nitesh V. Chawla. “HoNVis: Visualizing and Exploring Higher-Order Networks.” Proceedings of the 10th IEEE Pacific Visualization Symposium (PacificVis), 2017. arXiv PDF
  26. Saurabh Nagrecha, John Z. Dillon, and Nitesh V. Chawla. “MOOC Dropout Prediction: Lessons Learned from Making Pipelines Interpretable.” Proceedings of the 26th International Conference on World Wide Web Companion, 2017. PDF
  27. Pablo González, Jorge Díez, Nitesh V. Chawla, and Juan José del Coz. “Why is Quantification an Interesting Learning Problem?.” Progress in Artificial Intelligence (PRAI), 6(1):53–58, 2017. PDF

2016

  1. Shuo Wang, Jieyun Song, Xiaorui Shang, Nitesh V. Chawla, Yide Yang, Xiangrui Meng, Haijun Wang, and Jun Ma. “Physical Activity and Sedentary Behavior Can Modulate the Effect of the PNPLA3 Variant on Childhood NAFLD: A Case-Control Study in a Chinese Population.” BMC Medical Genetics. 2016. PDF
  2. Dipanwita Dasgupta, Beenish Chaudhry, Kimberly Green Reeves, and Nitesh V. Chawla. “A Survey of Tablet Applications for Promoting Successful Aging in Older Adults.” IEEE Access. 2016. PDF
  3. Dipanwita Dasgupta, Reid A. Johnson, Beenish Chaudhry, Emily Koh, and Nitesh V. Chawla. “Design and Evaluation of Medication Adherence Application with Communication for Seniors in Independent Living Communities.” Proceedings of the American Medical Informatics Association (AMIA) Annual Symposium. 2016. PDF
  4. Aastha Nigam, Salvador Aguinaga, and Nitesh V. Chawla. “Connecting the Dots to Infer Followers’ Topical Interest on Twitter.” IEEE International Conference on Behavioral, Economic, and Socio-Cultural Computing (BESC). 2016. PDF
  5. Siddharth Pal, Yuxiao Dong, Nitesh V. Chawla, Ananthram Swami, and Ram Ramanathan. “Deep Learning for Network Analysis: Problems, Approaches and Challenges.” Proceedings of the 35th Annual International Conference for Military Communications (MILCOM). 2016. PDF
  6. Dipanwita Dasgupta and Nitesh V. Chawla. “MedCare: Leveraging Medication Similarity for Disease Prediction.” Proceedings of the IEEE International Conference on Data Science and Advanced Analytics (DSAA). 2016. PDF
  7. Dipanwita Dasgupta, Kimberly Green Reeves, Beenish Chaudhry, Mayra Duarte, and Nitesh V. Chawla. “eSeniorCare: Technology for Promoting Well-Being of Older Adults in Independent Living Facilities.” Proceedings of the IEEE International Conference on Health Informatics (ICHI). 2016. PDF
  8. Keith Feldman, Nicholas Hazekamp, and Nitesh V. Chawla. “Mining the Clinical Narrative: All Text Are Not Equal.” Proceedings of the IEEE International Conference on Health Informatics (ICHI). 2016. PDF
  9. Ashwin Bahulkar, Boleslaw K. Szymanski, Omar Lizardo, Yuxiao Dong, Yang Yang, and Nitesh V. Chawla. “Analysis of Link Formation, Persistence and Dissolution in NetSense Data.” Proceedings of the 6th Workshop on Social Network Analysis in Applications (SNAA). 2016. PDF
  10. Saurabh Nagrecha and Nitesh V. Chawla. “Quantifying Decision Making for Data Science: From Data Acquisition to Modeling.” EPJ Data Science, 5:27, 2016. PDF
  11. Keith Feldman, Gregor Stiglic, Dipanwita Dasgupta, Mark Kricheff, Zoran Obradovic, and Nitesh V. Chawla. “Insights into Population Health Management Through Disease Diagnoses Networks.” Scientific Reports, 6:30465, 2016. PDF
  12. Sibel Kusimba, Yang Yang, and Nitesh V. Chawla. “Hearthholds of Mobile Money in Western Kenya.” Science Advances, 3(2):266–279, 2016. PDF
  13. Jian Xu, Thanuka L. Wickramarathne, and Nitesh V. Chawla. “Representing Higher-Order Dependencies in Networks.” Science Advances, 2(5):e1600028, 2016. PDF
  14. Beenish Chaudhry, Kimberly Green Reeves, and Nitesh V. Chawla. “Successful Aging for Low-Income Older Adults: Towards Design Principles.” Proceedings of the 10th EAI International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth). 2016. PDF
  15. Aastha Nigam and Nitesh V. Chawla. “Link Prediction in a Semi-bipartite Network for Recommendation.” Proceedings of the Asian Conference on Intelligent Information and Database Systems (ACIIDS), pp. 127–135, 2016. PDF
  16. Yuxiao Dong, Reid A. Johnson, and Nitesh V. Chawla. “Can Scientific Impact Be Predicted?.” IEEE Transactions on Big Data (TBD), 2(1):18–30, 2016. PDF
  17. Yuxiao Dong, Omar Lizardo, and Nitesh V. Chawla. “Do the Young Live in a “Smaller World” Than the Old? Age-Specific Degrees of Separation in a Large-Scale Mobile Communication Network.” arXiv
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