ADDAM 2014 - International Workshop on Agent-Based Distributed Data Analysis and Mining

Analysis of distributed data is a challenge that local governments, private sector and academics are increasingly faced with. The need to process huge data volumes and to extract useful information from them raises the need to research innovative methods and technologies in this field. Analysis and mining of distributed data requires highly scalable solutions. One way to achieve the scalability is to apply decentralized approaches, including suitable abstractions such as multi-agent systems.
The AGENDA workshop provides a forum for discussing theoretical and practical problems, approaches and solutions for analysing, mining and processing large-scale distributed data and data flows. A particular focus of AGENDA is on decentralized techniques, such as multi-agent systems, for this purpose. The workshop welcomes theoretical work and applied dissemination including, but not restricted to the following topics:
Principles and foundations for distributed data analysis and mining.
Formal models of distributed data
Challenges and formal problem descriptions
Platforms and architectures for distributed data analysis and mining
Technologies and platforms (e.g. agent-based cloud computing)
Paradigms and methodologies (e.g. different types of agent-based models)
Agent-based databases and distributed query languages for information retrieval
Agent interaction protocols for distributed data processing
Mechanism design and optimization including auctions or negotiation, based on distributed data
Methods and algorithms for distributed data processing
Distributed pre-processing and dimension reduction
Time and space windows for distributed data processing
Location determination and hashing of distributed data
Trust/reputation analysis
Distributed clustering and classification
Distributed forecasting
Machine learning based on distributed data
Computationally intensive methods for distributed data processing (e.g. kernel-based methods, bootstrap, resampling, cross-validation)
Simulation and performance evaluation of systems based on distributed data
Generation and re-use of distributed data
Distributed and agent-based simulation environments
Evaluation methods, metrics, benchmarks, and testbeds
Practical applications of distributed agent-based data analysis and mining, including
Web and text mining, information retrieval from social networks
Strategy design in computer games
Ambient intelligence, smart spaces, smart homes
Human-computer interaction intelligence, recommender systems
Image recognition
E-markets, e-commence and business services
E-health and tele-health
E-education and intelligent tutor systems
Traffic, transportation and logistics
Smart grid / energy management
Intelligent automation systems
Logistics and manufacturing