K. Elgarroussi, S. Wang, R. Banerjee, and C. F. Eick, Aconcagua: A Novel Spatio-temporal Emotion Change Analysis Framework, in Proceedings of 2018 ACM SIGSPATIAL 2nd workshop on AI for Geographic Knowledge Discovery(ACM SIGSPATIAL GeoAI), 2018. Link

R. Banerjee, K. Elgarroussi, S. Wang, Y. Zhang, and C. F. Eick, Tweet Emotion Mapping: Understanding US Emotions in Time and Space, in Proceedings of IEEE International Conference on Artificial Intelligence and Knowledge Engineering (IEEE AIKE 2018), 2018. Link

R. Banerjee, C. F. Eick, K. Elgarroussi, S. Wang, and Y. Zhang, A Framework to Analyze Change in US Emotions, 2018 Data Science Conference, 2018.

A. M. Aryal and S. Wang, Spark-SNN: Density-based Clustering on Spark, in Proceedings of 2018 IEEE 3rd International Conference on Big Data Analysis (ICBDA 2018), 2018. Link

K. Kang and S. Wang, Analyze and Predicate for College Student Online Program Dropout, in Proceedings of 2018 ACM 2nd International Conference of Compute and Data Analysis (ICCDA 2018), 2018. Link

S. Wang and C. F. Eick, A Data Mining Framework for Environmental and Geo-Spatial Data Analysis, International Journal of Data Science and Analytics (2018) 5:83. Link

S. Wang, C. F. Eick, MR-SNN: Design of Parallel Shared Nearest Neighbor Clustering on Hadoop, in Proceedings of IEEE International Conference on Big Data Analysis 2017 (ICBDA 2017), 2017. Link

A. M. Aryal, S. Wang, Discovery of Patterns in Spatial-temporal Data Using Clustering Techniques, in Proceedings of 2017 IEEE 2nd International Conference on Image, Vision and Computing Workshops on Database and Data Mining (ICDDM 2017), 2017. Link

Y. Zhang, S. Wang, A. M. Aryal, C. F. Eick, Serial versus Parallel: a Comparison of Spatio-temporal Clustering Approaches, in Proceedings of the 23rd International Symposium on Methodologies for Intelligent Systems (ISMIS 2017), 2017. Link

S. Wang, A Framework for Location-based Social Media Analysis on Hadoop Ecosystem, in Proceedings of the Third International Conference on CyberGIS and Geospatial Data Science, 2016.

S. Wang, C. F. Eick, Q. Xu, A Spatiotemporal Data Mining Framework for Mining Ozone Pollution Data, in Proceedings of the 13th International Conference on Geo-computation, 2015.

S. Wang, T. Cai, C. F. Eick, New Clustering and Analyzing Technique for Mining Multi-source Enriched Geo-spatial Data, in Proceedings of the ACM SIGMOD Workshop on Managing and Mining Enriched Geo-Spatial Data, 2014. Link

S. Wang, C. F. Eick, A Polygon-based Clustering and Analysis Framework for Mining Spatial Datasets, the International Journal of GeoInformatica, Volume 18 Issue 3, Pages: 569-594, July 2014, DOI: 10.1007/s10707-013-0190-2. Link

S. Wang, T. Cai, C. F. Eick, New Spatiotemporal Clustering Algorithms and their Applications to Ozone Pollution, in Proceedings of the 13th IEEE International Conference on Data Mining Workshop (ICDMW) on Spatial and Spatiotemporal Data Mining (SSTDM-13), 2013. Link

Z. Cao, S. Wang, C. F. Eick, Analyzing the Composition of Cities Using Spatial Clustering, in Proceedings of the 19th ACM SIGKDD conference on Knowledge Discovery and Data Mining Workshop (KDD) on Urban Computing (UrbComp 2013), 2013. Link

S. Wang, C. F. Eick, A Spatial Temporal Analysis Framework for Mining Geospatial Datasets, presented at the First International Conference on Space, Time, and CyberGIS (CyberGIS 12), 2012. Link