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DIAL Publications

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

2015

  1. Andrea Dal Pozzolo, Olivier Caelen, Reid A. Johnson, and Gianluca Bontempi. “Calibrating Probability with Undersampling for Unbalanced Classification.” Proceedings of the 6th IEEE Symposium on Computational Intelligence and Data Mining (CIDM), pp. 159–166, 2015. PDF
  2. Yang Yang, Ryan N. Lichtenwalter, and Nitesh V. Chawla. “Evaluating Link Prediction Methods.” Knowledge and Information Systems (KAIS), 45(3):751–782, 2015. PDF
  3. Chao Huang, Dong Wang, and Nitesh V. Chawla. “Towards Time-Sensitive Truth Discovery in Social Sensing Applications.” Proceedings of the 12th IEEE International Conference on Mobile Ad Hoc and Sensor Systems (MASS), pp. 154–162, 2015. PDF
  4. Everaldo Aguiar, Saurabh Nagrecha, and Nitesh V. Chawla. “Predicting Online Video Engagement Using Clickstreams.” Proceedings of the IEEE International Conference on Data Science and Advanced Analytics (DSAA), pp. 1–10, 2015. arXiv PDF
  5. Keith Feldman, Darcy A. Davis, and Nitesh V. Chawla. “Scaling and Contextualizing Personalized Healthcare: A Case Study of Disease Prediction Algorithm Integration.” Journal of Biomedical Informatics (JBI), vol. 57, pp. 377–385, 2015. PDF
  6. Reid A. Johnson, Ruobin Gong, Siobhan Greatorex-Voith, Anushka Anand, and Alan Fritzler. “A Data-Driven Framework for Identifying High School Students at Risk of Not Graduating on Time.” Bloomberg Data for Good Exchange. 2015. PDF
  7. Yuxiao Dong, Nitesh V. Chawla, Jie Tang, and Yang Yang. “The Evolution of Social Relationships and Strategies Across the Lifespan.” Proceedings of the 26th European Conference on Machine Learning and the 19th European Conference on Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD), pp. 245–249, 2015. PDF
  8. Yuxiao Dong, Fabio Pinelli, Yiannis Gkoufas, Zubair Nabi, Francesco Calabrese, and Nitesh V. Chawla. “Inferring Unusual Crowd Events from Mobile Phone Call Detail Records.” Proceedings of the 26th European Conference on Machine Learning and the 19th European Conference on Principles and Practice of Knowledge Discovery in Databases (ECML/PKDD), pp. 474–492, 2015. arXiv PDF
  9. Sibel B. Kusimba, Yang Yang, and Nitesh V. Chawla. “Family Networks of Mobile Money in Kenya.” Information Technologies & International Development (ITID), 11(3):1–21, 2015. PDF
  10. Yuxiao Dong, Reid A. Johnson, Yang Yang, and Nitesh V. Chawla. “Collaboration Signatures Reveal Scientific Impact.” Proceedings of the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), pp. 480–487, 2015. PDF
  11. Saurabh Nagrecha, Nitesh V. Chawla, and Horst Bunke. “Recurrent Subgraph Prediction.” Proceedings of the IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), pp. 416–423, 2015. PDF
  12. Yuxiao Dong, Jing Zhang, Jie Tang, Nitesh V. Chawla, and Bai Wang. “CoupledLP: Link Prediction in Coupled Networks.” Proceedings of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pp. 199–208, 2015. PDF
  13. Himabindu Lakkaraju, Everaldo Aguiar, Carl Shan, David I. Miller, Rayid Ghani, and Kecia L. Addison. “A Machine Learning Framework to Identify Students at Risk of Adverse Academic Outcomes.” Proceedings of the 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pp. 1908–1918, 2015. PDF
  14. Keith Feldman and Nitesh V. Chawla. “Does Medical School Training Relate to Practice? Evidence from Big Data.” Big Data Journal, 3(2):103–113, 2015. PDF
  15. Reid A. Johnson, Troy Raeder, and Nitesh V. Chawla. “Optimizing Classifiers for Hypothetical Scenarios.” Proceedings of the 19th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), pp. 264–276, 2015. PDF
  16. Everaldo Aguiar, Himabindu Lakkaraju, Nasir Bhanpuri, David I. Miller, Ben Yuhas, and Kecia L. Addison. “Who, When, and Why: A Machine Learning Approach to Prioritizing Students at Risk of Not Graduating High School on Time.” Proceedings of the 5th International Conference on Learning Analytics and Knowledge (LAK), pp. 93–102, 2015. PDF
  17. Frederick Nwanganga, Everaldo Aguiar, G. Alex Ambrose, Victoria E. Goodrich, and Nitesh V. Chawla. “Qualitatively Exploring Electronic Portfolios: A Text Mining Approach to Measuring Student Emotion as an Early Warning Indicator.” Proceedings of the 5th International Conference on Learning Analytics and Knowledge (LAK), pp. 422–423, 2015. PDF
  18. Yuxiao Dong, Jie Tang, and Nitesh V. Chawla. “Inferring Social Status and Rich Club Effects in Enterprise Communication Networks.” PLoS one, 10(3):e0119446, 2015. arXiv PDF
  19. Yuxiao Dong, Reid A. Johnson, and Nitesh V. Chawla. “Will This Paper Increase Your h-Index? Scientific Impact Prediction.” Proceedings of the 8th ACM International Conference on Web Search and Data Mining (WSDM), pp. 149–158, 2015. arXivPDF
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