C4.5: programs for machine learning
C4.5: programs for machine learning
Data mining: concepts and techniques
Data mining: concepts and techniques
Correlation-based Feature Selection for Discrete and Numeric Class Machine Learning
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
VLDB '06 Proceedings of the 32nd international conference on Very large data bases
Mining unconnected patterns in workflows
Information Systems
Improving process models by discovering decision points
Information Systems
Adaptive quality of service management for enterprise services
ACM Transactions on the Web (TWEB)
Supporting the dynamic evolution of Web service protocols in service-oriented architectures
ACM Transactions on the Web (TWEB)
Predictive business operations management
International Journal of Computational Science and Engineering
BP-Mon: query-based monitoring of BPEL business processes
ACM SIGMOD Record
Querying business processes with BP-QL
Information Systems
Mining taxonomies of process models
Data & Knowledge Engineering
Querying and monitoring distributed business processes
Proceedings of the VLDB Endowment
Information Systems
Automating the loading of business process data warehouses
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
Monitoring and analyzing influential factors of business process performance
EDOC'09 Proceedings of the 13th IEEE international conference on Enterprise Distributed Object Computing
SPDW+: a seamless approach for capturing quality metrics in software development environments
Software Quality Control
Cross-layer adaptation and monitoring of service-based applications
ICSOC/ServiceWave'09 Proceedings of the 2009 international conference on Service-oriented computing
Adaptation of service-based applications based on process quality factor analysis
ICSOC/ServiceWave'09 Proceedings of the 2009 international conference on Service-oriented computing
Defining process performance indicators: an ontological approach
OTM'10 Proceedings of the 2010 international conference on On the move to meaningful internet systems - Volume Part I
Improving server power management in research and development data centers
COMPUTE '11 Proceedings of the Fourth Annual ACM Bangalore Conference
Service research challenges and solutions for the future internet
TTL: a transformation, transference and loading approach for active monitoring
DaWaK'11 Proceedings of the 13th international conference on Data warehousing and knowledge discovery
IPVita: an intelligent platform of virtual travel agency
APWeb'06 Proceedings of the 8th Asia-Pacific Web conference on Frontiers of WWW Research and Development
Predictive business operations management
DNIS'05 Proceedings of the 4th international conference on Databases in Networked Information Systems
Mining hierarchies of models: from abstract views to concrete specifications
BPM'05 Proceedings of the 3rd international conference on Business Process Management
Challenges in business process analysis and optimization
TES'05 Proceedings of the 6th international conference on Technologies for E-Services
AutoScale: Dynamic, Robust Capacity Management for Multi-Tier Data Centers
ACM Transactions on Computer Systems (TOCS)
On the definition and design-time analysis of process performance indicators
Information Systems
Exact analysis of the M/M/k/setup class of Markov chains via recursive renewal reward
Proceedings of the ACM SIGMETRICS/international conference on Measurement and modeling of computer systems
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As IT systems become more and more complex and as business operations become increasingly automated, there is a growing need from business managers to have better control on business operations and on how these are aligned with business goals. This paper describes iBOM, a platform for business operation management developed by HP that allows users to i) analyze operations from a business perspective and manage them based on business goals; ii) define business metrics, perform intelligent analysis on them to understand causes of undesired metric values, and predict future values; iii) optimize operations to improve business metrics. A key aspect is that all this functionality is readily available almost at the click of the mouse. The description of the work proceeds from some specific requirements to the solution developed to address them. We also show that the platform is indeed general, as demonstrated by subsequent deployment domains other than finance.