Data mining
The International Workshop on Behavior Informatics (BI2010)
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Extended paper deadline: MARCH 7, 2010, 23:59:59 PDT

** Accepted papers will be published in the proceedings by Springer LNCS/LNAI **
** Format can be Springer LNAI with up to 12 pages**
** Papers should be submitted through the BI2010 submission system: **

Call For Papers
The International Workshop on Behavior Informatics (BI2010)
June 20, 2010 Hyderabad, India

Held in conjunction with
The 14th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD2010)

Important dates:
* Electronic submission of full papers: MARCH 7, 2010
* Notification of paper acceptance: March 20, 2010
* Camera-ready copies of accepted papers: March 30, 2010
* BI2010 workshop date: June 21, 2010

Call for papers to Special Sessions with PAKDD-BI2010
" Behavior Representation and Modeling
Submissions on fundamentals for modeling behaviors, behavior networks, group behaviors, behavior interactions, as well as behavioral impacts, trust, reputation, risk, etc.
" Multi-object/agent Behavior Analysis
Submissions on data mining and machine learning for analyzing behaviors in multi-agents, multi-objects, including interaction linkage etc.
" Social Interaction Analysis
Submissions on analyzing interactions occurring in social networks, internet, blogs, communities, government-customer interactions, etc.
" Group Behavior Pattern Mining
Submissions on data mining and machine learning for patterns in group behaviors, community interactions, multi-source and multi-entity interactions, etc.

Call for papers to general sessions

Topics: Contributions on the following and other related topics are solicited:
* (1) Foundations for BI
• Formal methods
• Temporal logic
• Model checking
• Statistic relational learning
• Advanced Bayesian network
• Multiagent systems
• Self-organization systems
• Adaptive systems
• Complex sequence analysis
• Temporal-sequential pattern mining
• Impact-oriented behavior mining
• Event/activity/action mining
• Agent-based data mining
• Frequent pattern mining
• Domain-driven behavior mining
• Behavior data visualization
* (2) Behavior Modeling and Representation
• Abstract behavior model
• Behavior life cycles
• Behavior structure understanding
• Behavior detection and extraction
• Sequential behavior modeling
• Parallel/concurrent behavior modeling
• Distributed behavior modeling
• Behavior dynamics
• Temporal-spatial relationship modeling
• Behavior privacy processing
* (3) Behavior Pattern Analysis
• Frequent behavior pattern
• Behavior classification
• Behavior clustering
• Demographic-behavioral combined pattern
• Interaction pattern analysis
• Stream behavior pattern
• Coupled behavior pattern
• Evolutionary behavior pattern
• Incremental behavior pattern
• Combined behavior pattern
* (4) Behavior Impact Analysis
• Positive/negative impact modeling
• Risk, benefit, cost and trust of behavior
• High-impact behavior identification
• Impact-transferred behavior pattern
• Cause-effect analysis
• Exceptional/outlier behavior
• Critical event detection and prediction
• Behavior reputation and trust
• Behavior security, risk, and privacy
• Personalized behavior
* (5) Behavior Emergence
• Behavior self-organization
• Behavior evolution
• Behavior impact formation and evolution
• Behavior group emergence
• Behavior mobility
• Behavior-environment interaction
• Influence formation and evolution
• Group behavior formation and evolution
• Trend, burst, opinion and event formation and evolution
* (6) Behavior Network
• Intrinsic mechanisms inside a network
• Behavior network topological structures
• Convergence and divergence of associated behavior
• Hidden group and community formation and identification
• Linkage formation and identification
• Community behavior analysis
* (7) Behavior Simulation
• Behavior convergence and divergence process
• Behavior learning and adaptation
• Group behavior formation and evolution
• Behavior interaction and linkage
• Behavior impact formation
• Behavior effect, impact and influence process
• Critical event replay
• Situated behavior interaction
• Organizational/social factor impact process
* (8) Behavior Presentation
• Rule-based behavior presentation
• Flow visualization
• Tree-based behavior representation
• Graph-based behavior modeling and presentation
• Sequence presentation and visualization
• Dynamic/hidden group presentation
• Dynamic/realtime behavior presentation
• Visual behavior network
* (9) Behavior Evaluation Mechanisms
• Behavior impact metrics
• Behavior risk metrics
• Behavior effect/influence metrics
• Behavior pattern significance
• Behavior pattern actionability
* (10) Behavior Use and Management
• Behavior compliance
• Multi-agent behavior analysis
• Web usage mining
• Customer analytics
• Consumer analytics
• Recommender system
• Personalized analysis
• Fraud detection
• Misuse and anomaly detection
• Human-computer interactions
• AI games
• Facial expression and human gesture analysis
• Computational linguistics
• Intelligent decision support system
• Student learning behaviors in intelligent tutoring system
• Criminal behavior analysis
• Organizational behavior analysis
• System behavior analysis
• Social networking behavior analysis
• Behavior analysis in video data
• Enterprise process and workflow analysis

About Behavior Informatics 2010

Objective: BI2010 provides a premier forum for sharing research and engineering results,
as well as potential challenges and prospects encountered in Behavior Informatics, namely towards
deep and quantitative representation, modeling, analysis, mining, presentation, management and applications
of behavioral data, composed of behaviors, behavior subjects and objects, behavior networks, organizational
behavior, social behavior, system behavior, group behavior, behavior evolution, causes and effects, and/or behavior impacts.

Scope: The BI2010 workshop welcomes theoretical work and applied disseminations aiming to:
* Behavior modeling and representation: formalizing behaviors, relationships, impact and networks.
* Behavior analysis and mining: behaviors associated with high impacts are of particular importance,
while impact-oriented behaviors are often sparse, rare and imbalanced isolated in business and data;
analyse impact-oriented behavior patterns involves different pattern types and computational challenges.
* Analysis of behavior social networks: handling challenging issues such as convergence and divergence of behaviors,
and the evolution and emergence of hidden groups and communities.
* Extracting discriminative behavior patterns from high-dimensional, high-frequency,
high-density, and huge amount of data.
* Large intra-class variance between behaviors: Due to the highly overlapped nature of behavior data,
it is extremely difficult to build a robust behavior model which is tolerant for one behavior category
while differentiate amongst other categories.
* Behavior data processing from transactional space to behavior feature space.

Post-workshop publication:
* A special Issue on Behavior Modeling, Analysis and Mining is under planning (to be confirmed).

General Co-Chair:
* Philip S Yu
University of Illinois at Chicago USA

* Longbing Cao, University of Technology Sydney, Australia
* Jaideep Srivastava, University of Minnesota, USA
* Graham Williams, Australian Taxation Office, Australia
* Hiroshi Motoda, Osaka University and AFOSR/AOARD, Japan

Supported by
Behavior Informatics - Special Interest Group (BI-SIG)