An overview of data warehousing and OLAP technology
ACM SIGMOD Record
Beyond market baskets: generalizing association rules to correlations
SIGMOD '97 Proceedings of the 1997 ACM SIGMOD international conference on Management of data
Discovering models of software processes from event-based data
ACM Transactions on Software Engineering and Methodology (TOSEM)
Real world performance of association rule algorithms
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Data Cube: A Relational Aggregation Operator Generalizing Group-By, Cross-Tab, and Sub-Totals
Data Mining and Knowledge Discovery
Advanced planning and scheduling with outsourcing in manufacturing supply chain
Computers and Industrial Engineering - Supply chain management
Distributed and Parallel Databases
Alternative Interest Measures for Mining Associations in Databases
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
Selecting the right interestingness measure for association patterns
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Workflow mining: a survey of issues and approaches
Data & Knowledge Engineering
Process mining: a research agenda
Computers in Industry - Special issue: Process/workflow mining
Building Association-Rule Based Sequential Classifiers for Web-Document Prediction
Data Mining and Knowledge Discovery
Workflow Management: Models, Methods, and Systems
Workflow Management: Models, Methods, and Systems
Mining and Reasoning on Workflows
IEEE Transactions on Knowledge and Data Engineering
FEEDBACKFLOW-An Adaptive Workflow Generator for Systems Management
ICAC '05 Proceedings of the Second International Conference on Automatic Computing
Discovering Social Networks from Event Logs
Computer Supported Cooperative Work
Interestingness measures for data mining: A survey
ACM Computing Surveys (CSUR)
YAWL: yet another workflow language
Information Systems
Deadline-based escalation in process-aware information systems
Decision Support Systems
Using AI and semantic web technologies to attack process complexity in open systems
Knowledge-Based Systems
Business process mining: An industrial application
Information Systems
A semi-automatic approach for workflow staff assignment
Computers in Industry
An Optimal Approach for Workflow Staff Assignment Based on Hidden Markov Models
OTM '08 Proceedings of the OTM Confederated International Workshops and Posters on On the Move to Meaningful Internet Systems: 2008 Workshops: ADI, AWeSoMe, COMBEK, EI2N, IWSSA, MONET, OnToContent + QSI, ORM, PerSys, RDDS, SEMELS, and SWWS
The design of intelligent workflow monitoring with agent technology
Knowledge-Based Systems
An adaptive work distribution mechanism based on reinforcement learning
Expert Systems with Applications: An International Journal
Re-examination of interestingness measures in pattern mining: a unified framework
Data Mining and Knowledge Discovery
Advanced resource planning as a decision support module for ERP
Computers in Industry
Workflow resource patterns: identification, representation and tool support
CAiSE'05 Proceedings of the 17th international conference on Advanced Information Systems Engineering
Mining staff assignment rules from event-based data
BPM'05 Proceedings of the Third international conference on Business Process Management
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Currently, workflow technology is widely used to facilitate the business process in enterprise information systems (EIS), and it has the potential to reduce design time, enhance product quality and decrease product cost. However, significant limitations still exist: as an important task in the context of workflow, many present resource allocation (also known as ''staff assignment'') operations are still performed manually, which are time-consuming. This paper presents a data mining approach to address the resource allocation problem (RAP) and improve the productivity of workflow resource management. Specifically, an Apriori-like algorithm is used to find the frequent patterns from the event log, and association rules are generated according to predefined resource allocation constraints. Subsequently, a correlation measure named lift is utilized to annotate the negatively correlated resource allocation rules for resource reservation. Finally, the rules are ranked using the confidence measures as resource allocation rules. Comparative experiments are performed using C4.5, SVM, ID3, Naive Bayes and the presented approach, and the results show that the presented approach is effective in both accuracy and candidate resource recommendations.