Nonoccurring Behavior Analytics: A New Area

Nonoccurring behaviors (NOBs) refer to those behaviors that should happen but do not take place for some reasons. They are widely seen in online, business, government, health, medical, scientific, and social data and applications. Very limited research has been undertaken to explore such behaviors owing to their invisibility and the significant challenges in analyzing NOBs. This article outlines the concept, intrinsic characteristics, significant challenges, main issues, research directions, and state-of-the-art work related to NOBs, followed by the prospects for and applications of NOB analytics.

Authors

• Longbing Cao Macquarie University
• Philip S. Yu University of Illinois, Chicago
• Vipin Kumar

Keywords

• Behavioral science
• Complexity theory
• Analytical models
• Intelligent systems
• Computational modeling
• Economics
• Behavioral Analysis
• Machine Learning
• Public Services
• Behavioral Data
• Data Mining
• Behavioral Sciences
• Perspective Of Model
• Science Activities
• Representation Of Behavior
• Association Rule Mining
• Financial Business
• Social Media
• Negation
• Similarity Measure
• Behavioral Elements
• Behavioral Sequences
• Coupling Relationship
• Computational Complexity Analysis
• Pattern Mining
• Pruning Strategy
• Business Impact
• Hidden Nature
• nonoccurring behavior
• occurring behavior
• behavior analysis
• negative sequence analysis
• negative behavior analysis
• behavior informatics