Distributed data clustering can be efficient and exact
ACM SIGKDD Explorations Newsletter - Special issue on “Scalable data mining algorithms”
Artificial Intelligence: Structures and Strategies for Complex Problem Solving
Artificial Intelligence: Structures and Strategies for Complex Problem Solving
Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence
Multiagent Systems: A Modern Approach to Distributed Artificial Intelligence
Pattern Recognition with Fuzzy Objective Function Algorithms
Pattern Recognition with Fuzzy Objective Function Algorithms
Advances in Distributed and Parallel Knowledge Discovery
Advances in Distributed and Parallel Knowledge Discovery
Parallel and Distributed Association Mining: A Survey
IEEE Concurrency
Efficient Mining of Association Rules in Distributed Databases
IEEE Transactions on Knowledge and Data Engineering
Effect of Data Skewness and Workload Balance in Parallel Data Mining
IEEE Transactions on Knowledge and Data Engineering
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
Parallel and Distributed Data Mining: An Introduction
Revised Papers from Large-Scale Parallel Data Mining, Workshop on Large-Scale Parallel KDD Systems, SIGKDD
Cluster ensembles --- a knowledge reuse framework for combining multiple partitions
The Journal of Machine Learning Research
Multi-agent Technology for Distributed Data Mining and Classification
IAT '03 Proceedings of the IEEE/WIC International Conference on Intelligent Agent Technology
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)
Distributed data mining on agent grid: issues, platform and development toolkit
Future Generation Computer Systems - Special section: Data mining in grid computing environments
Genetic algorithm based multi-agent system applied to test generation
Computers & Education
Service-oriented middleware for distributed data mining on the grid
Journal of Parallel and Distributed Computing
Top 10 algorithms in data mining
Knowledge and Information Systems
EMADS: An extendible multi-agent data miner
Knowledge-Based Systems
Parallel K-Means Clustering Based on MapReduce
CloudCom '09 Proceedings of the 1st International Conference on Cloud Computing
An Introduction to MultiAgent Systems
An Introduction to MultiAgent Systems
Distributed data mining and agents
Engineering Applications of Artificial Intelligence
A multi-agent based approach to clustering: harnessing the power of agents
ADMI'11 Proceedings of the 7th international conference on Agents and Data Mining Interaction
Agent enriched distributed association rules mining: a review
ADMI'11 Proceedings of the 7th international conference on Agents and Data Mining Interaction
ADMI'11 Proceedings of the 7th international conference on Agents and Data Mining Interaction
Pricing analysis in online auctions using clustering and regression tree approach
ADMI'11 Proceedings of the 7th international conference on Agents and Data Mining Interaction
Data cloud for distributed data mining via pipelined mapreduce
ADMI'11 Proceedings of the 7th international conference on Agents and Data Mining Interaction
Hi-index | 12.05 |
The main focus of this research project is the problem of extracting useful information from the Brazilian federal procurement process databases used by government auditors in the process of corruption detection and prevention to identify cartel formation among applicants. Extracting useful information to enhance cartel detection is a complex problem from many perspectives due to the large volume of data used to correlate information and the dynamic and diversified strategies companies use to hide their fraudulent operations. To attack the problem of data volume, we have used two data mining model functions, clustering and association rules, and a multi-agent approach to address the dynamic strategies of companies that are involved in cartel formation. To integrate both solutions, we have developed AGMI, an agent-mining tool that was validated using real data from the Brazilian Office of the Comptroller General, an institution of government auditing, where several measures are currently used to prevent and fight corruption. Our approach resulted in explicit knowledge discovery because AGMI presented many association rules that provided a 90% correct identification of cartel formation, according to expert assessment. According to auditing specialists, the extracted knowledge could help in the detection, prevention and monitoring of cartels that act in public procurement processes.