Activity monitoring: noticing interesting changes in behavior
KDD '99 Proceedings of the fifth ACM SIGKDD international conference on Knowledge discovery and data mining
Outlier detection for high dimensional data
SIGMOD '01 Proceedings of the 2001 ACM SIGMOD international conference on Management of data
Understanding and Using Context
Personal and Ubiquitous Computing
Machine Learning for User Modeling
User Modeling and User-Adapted Interaction
User Modeling and User-Adapted Interaction
A unifying framework for detecting outliers and change points from non-stationary time series data
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Web usage mining: discovery and applications of usage patterns from Web data
ACM SIGKDD Explorations Newsletter
Designing and implementing a family of intrusion detection systems
Proceedings of the 9th European software engineering conference held jointly with 11th ACM SIGSOFT international symposium on Foundations of software engineering
Applying data mining in investigating money laundering crimes
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Understanding Terror Networks
Early detection of insider trading in option markets
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
A Survey of Outlier Detection Methodologies
Artificial Intelligence Review
Mining interesting knowledge from weblogs: a survey
Data & Knowledge Engineering
Using relational knowledge discovery to prevent securities fraud
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Behavior-based modeling and its application to Email analysis
ACM Transactions on Internet Technology (TOIT)
On the structural properties of massive telecom call graphs: findings and implications
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Social Computing: From Social Informatics to Social Intelligence
IEEE Intelligent Systems
Relational data pre-processing techniques for improved securities fraud detection
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Detecting changes in large data sets of payment card data: a case study
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Social ties and their relevance to churn in mobile telecom networks
EDBT '08 Proceedings of the 11th international conference on Extending database technology: Advances in database technology
Mining Impact-Targeted Activity Patterns in Imbalanced Data
IEEE Transactions on Knowledge and Data Engineering
EOCS-MCP 2008 Workshop Organization
COMPSAC '08 Proceedings of the 2008 32nd Annual IEEE International Computer Software and Applications Conference
Contextualized Recommendation Based on Reality Mining From Mobile Subscribers
Cybernetics and Systems
Metasynthesis: M-space, M-interaction, and M-computing for open complex giant systems
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
An e-customer behavior model with online analytical mining for internet marketing planning
Decision Support Systems
Mining high impact exceptional behavior patterns
PAKDD'07 Proceedings of the 2007 international conference on Emerging technologies in knowledge discovery and data mining
Activity mining: challenges and prospects
ADMA'06 Proceedings of the Second international conference on Advanced Data Mining and Applications
A novel evolutionary data mining algorithm with applications to churn prediction
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Neural Networks
Recommendation of similar users, resources and social networks in a Social Internetworking Scenario
Information Sciences: an International Journal
Agent-based subspace clustering
PAKDD'11 Proceedings of the 15th Pacific-Asia conference on Advances in knowledge discovery and data mining - Volume Part II
Proceedings of the 20th ACM international conference on Information and knowledge management
Evaluating the regularity of human behavior from mobile phone usage logs
PAKDD'11 Proceedings of the 15th international conference on New Frontiers in Applied Data Mining
Explicit and implicit user preferences in online dating
PAKDD'11 Proceedings of the 15th international conference on New Frontiers in Applied Data Mining
Blogger-Link-Topic model for blog mining
PAKDD'11 Proceedings of the 15th international conference on New Frontiers in Applied Data Mining
A random indexing approach for web user clustering and web prefetching
PAKDD'11 Proceedings of the 15th international conference on New Frontiers in Applied Data Mining
Emotional reactions to real-world events in social networks
PAKDD'11 Proceedings of the 15th international conference on New Frontiers in Applied Data Mining
Constructing personal knowledge base: automatic key-phrase extraction from multiple-domain web pages
PAKDD'11 Proceedings of the 15th international conference on New Frontiers in Applied Data Mining
Discovering valuable user behavior patterns in mobile commerce environments
PAKDD'11 Proceedings of the 15th international conference on New Frontiers in Applied Data Mining
A novel method for community detection in complex network using new representation for communities
PAKDD'11 Proceedings of the 15th international conference on New Frontiers in Applied Data Mining
Link prediction on evolving data using tensor factorization
PAKDD'11 Proceedings of the 15th international conference on New Frontiers in Applied Data Mining
Efficient mining top-k regular-frequent itemset using compressed tidsets
PAKDD'11 Proceedings of the 15th international conference on New Frontiers in Applied Data Mining
A method of similarity measure and visualization for long time series using binary patterns
PAKDD'11 Proceedings of the 15th international conference on New Frontiers in Applied Data Mining
A BIRCH-Based clustering method for large time series databases
PAKDD'11 Proceedings of the 15th international conference on New Frontiers in Applied Data Mining
PAKDD'11 Proceedings of the 15th international conference on New Frontiers in Applied Data Mining
Towards recommender system using particle swarm optimization based web usage clustering
PAKDD'11 Proceedings of the 15th international conference on New Frontiers in Applied Data Mining
Mining tourist preferences with twice-learning
PAKDD'11 Proceedings of the 15th international conference on New Frontiers in Applied Data Mining
Actionable knowledge discovery and delivery
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
Towards group behavioral reason mining
Expert Systems with Applications: An International Journal
Distributed customer behavior prediction using multiplex data: A collaborative MK-SVM approach
Knowledge-Based Systems
Summarizing clinical pathways from event logs
Journal of Biomedical Informatics
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The in-depth analysis of human behavior has been increasingly recognized as a crucial means for disclosing interior driving forces, causes and impact on businesses in handling many challenging issues such as behavior modeling and analysis in virtual organizations, web community analysis, counter-terrorism and stopping crime. The modeling and analysis of behaviors in virtual organizations is an open area. Traditional behavior modeling mainly relies on qualitative methods from behavioral science and social science perspectives. On the other hand, so-called behavior analysis is actually based on human demographic and business usage data, such as churn prediction in the telecommunication industry, in which behavior-oriented elements are hidden in routinely collected transactional data. As a result, it is ineffective or even impossible to deeply scrutinize native behavior intention, lifecycle and impact on complex problems and business issues. In this paper, we propose the approach of behavior informatics (BI), in order to support explicit and quantitative behavior involvement through a conversion from source data to behavioral data, and further conduct genuine analysis of behavior patterns and impacts. BI consists of key components including behavior representation, behavioral data construction, behavior impact analysis, behavior pattern analysis, behavior simulation, and behavior presentation and behavior use. We discuss the concepts of behavior and an abstract behavioral model, as well as the research tasks, process and theoretical underpinnings of BI. Two real-world case studies are demonstrated to illustrate the use of BI in dealing with complex enterprise problems, namely analyzing exceptional market microstructure behavior for market surveillance and mining for high impact behavior patterns in social security data for governmental debt prevention. Substantial experiments have shown that BI has the potential to greatly complement the existing empirical and specific means by finding deeper and more informative patterns leading to greater in-depth behavior understanding. BI creates new directions and means to enhance the quantitative, formal and systematic modeling and analysis of behaviors in both physical and virtual organizations.