The Experts below are selected from a list of 39 Experts worldwide ranked by ideXlab platform

Pwpj Paul Grefen - One of the best experts on this subject based on the ideXlab platform.

  • Fast Business Process similarity search with feature-based similarity estimation
    2010
    Co-Authors: Zhiqiang Yan, Remco M. Dijkman, Pwpj Paul Grefen
    Abstract:

    Nowadays, Business Process management plays an important role in the management of organizations. More and more organizations describe their operations as Business Processes, and the intra- and interorganizational interactions between operations as services. It is common for organizations to have collections of hundreds or even thousands of Business Processes. Consequently, techniques are required to quickly find Relevant Business Process models in such a collection. Currently, techniques exist that can rank all Business Process models in a collection based on their similarity to a query Business Process model. However, those techniques compare the query model with each model in the collection in terms of graph structure, which is inefficient and computationally complex. Therefore, this paper presents a technique to make this more efficient. The technique selects small characteristic model fragments, called features, which are used to efficiently estimate model similarities and classify them as Relevant, irRelevant or potentially Relevant to a query model. Only potentially Relevant models must be compared using the existing techniques. Experiments show that this helps to retrieve similar models at least 3.5 times faster without impacting the quality of the results; and 5.5 times faster if a quality reduction of 1% is acceptable.

  • OTM Conferences (1) - Fast Business Process similarity search with feature-based similarity estimation
    On the Move to Meaningful Internet Systems: OTM 2010, 2010
    Co-Authors: Zhiqiang Yan, Remco M. Dijkman, Pwpj Paul Grefen
    Abstract:

    Nowadays, Business Process management plays an important role in the management of organizations. More and more organizations describe their operations as Business Processes, and the intra- and inter-organizational interactions between operations as services. It is common for organizations to have collections of hundreds or even thousands of Business Processes. Consequently, techniques are required to quickly find Relevant Business Process models in such a collection. Currently, techniques exist that can rank all Business Process models in a collection based on their similarity to a query Business Process model. However, those techniques compare the query model with each model in the collection in terms of graph structure, which is inefficient and computationally complex. Therefore, this paper presents a technique to make this more efficient. The technique selects small characteristic model fragments, called features, which are used to efficiently estimate model similarities and classify them as Relevant, irRelevant or potentially Relevant to a query model. Only potentially Relevant models must be compared using the existing techniques. Experiments show that this helps to retrieve similar models at least 3.5 times faster without impacting the quality of the results; and 5.5 times faster if a quality reduction of 1% is acceptable.

Zhiqiang Yan - One of the best experts on this subject based on the ideXlab platform.

  • Fast Business Process similarity search with feature-based similarity estimation
    2010
    Co-Authors: Zhiqiang Yan, Remco M. Dijkman, Pwpj Paul Grefen
    Abstract:

    Nowadays, Business Process management plays an important role in the management of organizations. More and more organizations describe their operations as Business Processes, and the intra- and interorganizational interactions between operations as services. It is common for organizations to have collections of hundreds or even thousands of Business Processes. Consequently, techniques are required to quickly find Relevant Business Process models in such a collection. Currently, techniques exist that can rank all Business Process models in a collection based on their similarity to a query Business Process model. However, those techniques compare the query model with each model in the collection in terms of graph structure, which is inefficient and computationally complex. Therefore, this paper presents a technique to make this more efficient. The technique selects small characteristic model fragments, called features, which are used to efficiently estimate model similarities and classify them as Relevant, irRelevant or potentially Relevant to a query model. Only potentially Relevant models must be compared using the existing techniques. Experiments show that this helps to retrieve similar models at least 3.5 times faster without impacting the quality of the results; and 5.5 times faster if a quality reduction of 1% is acceptable.

  • OTM Conferences (1) - Fast Business Process similarity search with feature-based similarity estimation
    On the Move to Meaningful Internet Systems: OTM 2010, 2010
    Co-Authors: Zhiqiang Yan, Remco M. Dijkman, Pwpj Paul Grefen
    Abstract:

    Nowadays, Business Process management plays an important role in the management of organizations. More and more organizations describe their operations as Business Processes, and the intra- and inter-organizational interactions between operations as services. It is common for organizations to have collections of hundreds or even thousands of Business Processes. Consequently, techniques are required to quickly find Relevant Business Process models in such a collection. Currently, techniques exist that can rank all Business Process models in a collection based on their similarity to a query Business Process model. However, those techniques compare the query model with each model in the collection in terms of graph structure, which is inefficient and computationally complex. Therefore, this paper presents a technique to make this more efficient. The technique selects small characteristic model fragments, called features, which are used to efficiently estimate model similarities and classify them as Relevant, irRelevant or potentially Relevant to a query model. Only potentially Relevant models must be compared using the existing techniques. Experiments show that this helps to retrieve similar models at least 3.5 times faster without impacting the quality of the results; and 5.5 times faster if a quality reduction of 1% is acceptable.

Remco M. Dijkman - One of the best experts on this subject based on the ideXlab platform.

  • Fast Business Process similarity search with feature-based similarity estimation
    2010
    Co-Authors: Zhiqiang Yan, Remco M. Dijkman, Pwpj Paul Grefen
    Abstract:

    Nowadays, Business Process management plays an important role in the management of organizations. More and more organizations describe their operations as Business Processes, and the intra- and interorganizational interactions between operations as services. It is common for organizations to have collections of hundreds or even thousands of Business Processes. Consequently, techniques are required to quickly find Relevant Business Process models in such a collection. Currently, techniques exist that can rank all Business Process models in a collection based on their similarity to a query Business Process model. However, those techniques compare the query model with each model in the collection in terms of graph structure, which is inefficient and computationally complex. Therefore, this paper presents a technique to make this more efficient. The technique selects small characteristic model fragments, called features, which are used to efficiently estimate model similarities and classify them as Relevant, irRelevant or potentially Relevant to a query model. Only potentially Relevant models must be compared using the existing techniques. Experiments show that this helps to retrieve similar models at least 3.5 times faster without impacting the quality of the results; and 5.5 times faster if a quality reduction of 1% is acceptable.

  • OTM Conferences (1) - Fast Business Process similarity search with feature-based similarity estimation
    On the Move to Meaningful Internet Systems: OTM 2010, 2010
    Co-Authors: Zhiqiang Yan, Remco M. Dijkman, Pwpj Paul Grefen
    Abstract:

    Nowadays, Business Process management plays an important role in the management of organizations. More and more organizations describe their operations as Business Processes, and the intra- and inter-organizational interactions between operations as services. It is common for organizations to have collections of hundreds or even thousands of Business Processes. Consequently, techniques are required to quickly find Relevant Business Process models in such a collection. Currently, techniques exist that can rank all Business Process models in a collection based on their similarity to a query Business Process model. However, those techniques compare the query model with each model in the collection in terms of graph structure, which is inefficient and computationally complex. Therefore, this paper presents a technique to make this more efficient. The technique selects small characteristic model fragments, called features, which are used to efficiently estimate model similarities and classify them as Relevant, irRelevant or potentially Relevant to a query model. Only potentially Relevant models must be compared using the existing techniques. Experiments show that this helps to retrieve similar models at least 3.5 times faster without impacting the quality of the results; and 5.5 times faster if a quality reduction of 1% is acceptable.

Jean-pierre Lorré - One of the best experts on this subject based on the ideXlab platform.

  • Business Process Management Workshops - Event-Based Business Process Editor and Simulator
    Business Process Management Workshops, 2010
    Co-Authors: Vatcharaphun Rajsiri, Nicholas Fleury, Graham Crosmarie, Jean-pierre Lorré
    Abstract:

    The growing of Business market dictates new requirements of agility to the Business Process environment. An event-driven approach can deal with this issue since an event can be defined as a significant change in the state of a system or an environment. This paper is focused on the combination of the event-driven approach and the Business Process modeling one by developing a cloud-enabled event-based Business Process editor and simulator. BPMN2.0 is the Relevant Business Process formalism used since it can represent graphically various kind of operating activities and events.

Vatcharaphun Rajsiri - One of the best experts on this subject based on the ideXlab platform.

  • Business Process Management Workshops - Event-Based Business Process Editor and Simulator
    Business Process Management Workshops, 2010
    Co-Authors: Vatcharaphun Rajsiri, Nicholas Fleury, Graham Crosmarie, Jean-pierre Lorré
    Abstract:

    The growing of Business market dictates new requirements of agility to the Business Process environment. An event-driven approach can deal with this issue since an event can be defined as a significant change in the state of a system or an environment. This paper is focused on the combination of the event-driven approach and the Business Process modeling one by developing a cloud-enabled event-based Business Process editor and simulator. BPMN2.0 is the Relevant Business Process formalism used since it can represent graphically various kind of operating activities and events.