Emerging Research Trends and New Horizons

The upcoming new horizons and recent research trends in Big Data Analytics frameworks, techniques and algorithms are as reflected in research papers recently published in conferences such as ACM International Conference on Knowledge Discovery and Data Mining (ACM SIG KDD), SIAM International Conference on Data Mining (SDM), IEEE International Conference on Data Engineering (ICDE) and ACM International Conference on Information and Knowledge Management (CIKM). In this chapter, we shall survey the research trends and the possible new horizons coming up in Big Data Analytics.

[1]  Philip S. Yu,et al.  Outlier detection in graph streams , 2011, 2011 IEEE 27th International Conference on Data Engineering.

[2]  Philip S. Yu,et al.  GraphScope: parameter-free mining of large time-evolving graphs , 2007, KDD '07.

[3]  Steve Harenberg,et al.  Anomaly detection in dynamic networks: a survey , 2015 .

[4]  Weiru Liu,et al.  Detecting anomalies in graphs with numeric labels , 2011, CIKM '11.

[5]  Charu C. Aggarwal,et al.  Outlier Detection for Temporal Data: A Survey , 2014, IEEE Transactions on Knowledge and Data Engineering.

[6]  Ambuj K. Singh,et al.  NetSpot: Spotting Significant Anomalous Regions on Dynamic Networks , 2013, SDM.

[7]  Ananthram Swami,et al.  Practical Black-Box Attacks against Deep Learning Systems using Adversarial Examples , 2016, ArXiv.

[8]  Christos Faloutsos,et al.  A General Suspiciousness Metric for Dense Blocks in Multimodal Data , 2015, 2015 IEEE International Conference on Data Mining.

[9]  Charu C. Aggarwal,et al.  Evolutionary Clustering and Analysis of Bibliographic Networks , 2011, 2011 International Conference on Advances in Social Networks Analysis and Mining.

[10]  Wei Liu,et al.  On Sparse Feature Attacks in Adversarial Learning , 2014, ICDM.

[11]  James Bailey,et al.  An Efficient Adversarial Learning Strategy for Constructing Robust Classification Boundaries , 2012, Australasian Conference on Artificial Intelligence.

[12]  Charu C. Aggarwal,et al.  Evolutionary Network Analysis , 2014, ACM Comput. Surv..

[13]  Claudia Eckert,et al.  Support vector machines under adversarial label contamination , 2015, Neurocomputing.

[14]  Ananthram Swami,et al.  Practical Black-Box Attacks against Machine Learning , 2016, AsiaCCS.

[15]  James Bailey,et al.  Structure-Aware Distance Measures for Comparing Clusterings in Graphs , 2014, PAKDD.

[16]  K Rama Krishniah,et al.  Security Evaluation of Pattern Classifiers under Attack , 2016 .