The Experts below are selected from a list of 12183 Experts worldwide ranked by ideXlab platform

S Sosale - One of the best experts on this subject based on the ideXlab platform.

  • product Modularization for life cycle engineering
    Robotics and Computer-integrated Manufacturing, 1999
    Co-Authors: S Sosale
    Abstract:

    Abstract Modular products consist of detachable modules, which can be manufactured, assembled, and serviced separately. Some of the modules may be reusable, recyclable or re-manufacturable upon product retirement. Thus, modular design can provide benefits to many aspects of product life cycle. This paper presents an integrated modular design methodology for life cycle engineering. The methodology consists of three phases: problem definition, interaction analysis and module formation. The methodology identifies the factors related to the design objectives, relates these factors to design components through interaction analysis, and clusters components into modules. Two case studies along with detailed analysis are provided to illustrate the methodology and the algorithms.

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

  • human and automatic Modularizations of process models to enhance their comprehension
    Information Systems, 2011
    Co-Authors: Hajo A Reijers, Jan Mendling, Remco M Dijkman
    Abstract:

    Modularization is a widely advocated mechanism to manage a business process model's size and complexity. However, the widespread use of subprocesses in models does not rest on solid evidence for its benefits to enhance their comprehension, nor are the criteria clear how to identify subprocesses. In this paper, we describe an empirical investigation to test the effectiveness of using subprocesses in real-life process models. Our results suggest that subprocesses may foster the understanding of a complex business process model by their ''information hiding'' quality. Furthermore, we explored different categories of criteria that can be used to automatically derive process fragments that seem suitable to capture as subprocesses. From this exploration, approaches that consider the connectedness of subprocesses seem most attractive to pursue. This insight can be used to develop tool support for the Modularization of business process models.

  • On the usefulness of subprocesses in business process models
    2010
    Co-Authors: Hajo A Reijers, Jan Mendling, Remco M Dijkman
    Abstract:

    To manage the size and complexity of business process models, the use of subprocesses is widely advocated. In this paper, we provide a review of work with respect to the Modularization of business process models, which points at a lack of solid evidence for its bene??ts and the absence of clear criteria for identifying subprocesses. In response to this, we conducted an empirical investigation to test the e??ectiveness of using subprocesses in real-life process models. Our results suggest that Modularization may foster the understanding of a complex business process model by its \information hiding" quality. Furthermore, we explored di??erent categories of criteria that can be used to automatically derive process fragments that seem suitable to capture as subprocesses. From this exploration, approaches that consider the connectedness of subprocesses seem most attractive to pursue. This conclusion can be used to develop tool support for the Modularization of business process models.

Luigi Iannone - One of the best experts on this subject based on the ideXlab platform.

  • evaluating ontology modules using an entropy inspired metric
    Web Intelligence, 2008
    Co-Authors: Paul Doran, Valentina Tamma, Ignazio Palmisano, Terry R Payne, Luigi Iannone
    Abstract:

    The focus of ontology Modularization to date has largely been on the creation of techniques to carry out ontology Modularization. This creates a problem in evaluating the results of the different techniques. Ontology Modularization techniques cannot solely be evaluated by examining their logical properties. Certain applications of ontology Modularization, such as ontology reuse, require a new objective way to evaluate the results. This paper motivates the use of an entropy inspired measure to evaluate ontology modules by arguing that current objective measures of evaluation do not reconcile with the subjective measures employed by Ontology Engineers. Experiments are conducted to show that an entropy based evaluation of ontology modules is beneficial to an Ontology Engineer evaluating the results of ontology module extraction techniques.

  • evaluating ontology modules using an entropy inspired metric
    Web Intelligence, 2008
    Co-Authors: Paul Doran, Valentina Tamma, Ignazio Palmisano, Terry R Payne, Luigi Iannone
    Abstract:

    The focus of ontology Modularization to date has largely been on the creation of techniques to carry out ontology Modularization. This creates a problem in evaluating the results of the different techniques. Ontology Modularization techniques cannot solely be evaluated by examining their logical properties. Certain applications of ontology Modularization, such as ontology reuse, require a new objective way to evaluate the results. This paper motivates the use of an entropy inspired measure to evaluate ontology modules by arguing that current objective measures of evaluation do not reconcile with the subjective measures employed by Ontology Engineers. Experiments are conducted to show that an entropy based evaluation of ontology modules is beneficial to an Ontology Engineer evaluating the results of ontology module extraction techniques.

Francisco M Couto - One of the best experts on this subject based on the ideXlab platform.

  • ontology alignment repair through Modularization and confidence based heuristics
    PLOS ONE, 2015
    Co-Authors: Emanuel Santos, Daniel Faria, Catia Pesquita, Francisco M Couto
    Abstract:

    Ontology Matching aims at identifying a set of semantic correspondences, called an alignment, between related ontologies. In recent years, there has been a growing interest in efficient and effective matching methods for large ontologies. However, alignments produced for large ontologies are often logically incoherent. It was only recently that the use of repair techniques to improve the coherence of ontology alignments began to be explored. This paper presents a novel Modularization technique for ontology alignment repair which extracts fragments of the input ontologies that only contain the necessary classes and relations to resolve all detectable incoherences. The paper presents also an alignment repair algorithm that uses a global repair strategy to minimize both the degree of incoherence and the number of mappings removed from the alignment, while overcoming the scalability problem by employing the proposed Modularization technique. Our evaluation shows that our Modularization technique produces significantly small fragments of the ontologies and that our repair algorithm produces more complete alignments than other current alignment repair systems, while obtaining an equivalent degree of incoherence. Additionally, we also present a variant of our repair algorithm that makes use of the confidence values of the mappings to improve alignment repair. Our repair algorithm was implemented as part of AgreementMakerLight, a free and open-source ontology matching system.

Mark Proctor - One of the best experts on this subject based on the ideXlab platform.