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Scalable Semantic Annotation using Lattice-based Ontologies
Jackie Man-Kit Leung, Thomas Mandl, Edward A. Lee, Elizabeth Latronico, Charles Shelton, Stavros Tripakis, Ben Lickly

Citation
Jackie Man-Kit Leung, Thomas Mandl, Edward A. Lee, Elizabeth Latronico, Charles Shelton, Stavros Tripakis, Ben Lickly. "Scalable Semantic Annotation using Lattice-based Ontologies". 12th International Conference on Model Driven Engineering Languages and Systems, ACM/IEEE, 393-407, 8, October, 2009; (recipient of the MODELS 2009 Distinguished Paper Award).

Abstract
Including semantic information in models helps to expose modeling errors early in the design process, engage a designer in a deeper understanding of the model, and standardize concepts and terminology across a development team. It is impractical, however, for model builders to manually annotate every modeling element with semantic properties. This paper demonstrates a correct, scalable and automated method to infer semantic properties using lattice-based ontologies, given relatively few manual annotations. Semantic concepts and their relationships are formalized as a lattice, and relationships within and between components are expressed as a set of constraints and acceptance criteria relative to the lattice. Our inference engine automatically infers properties wherever they are not explicitly specified. Our implementation leverages the infrastructure in the Ptolemy II type system to get efficient and scalable inference and consistency checking. We demonstrate the approach on a non-trivial Ptolemy II model of an adaptive cruise control system.

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Citation formats  
  • HTML
    Jackie Man-Kit Leung, Thomas Mandl, Edward A. Lee, Elizabeth
    Latronico, Charles Shelton, Stavros Tripakis, Ben Lickly.
    <a
    href="http://chess.eecs.berkeley.edu/pubs/611.html"
    >Scalable Semantic Annotation using Lattice-based
    Ontologies</a>, 12th International Conference on Model
    Driven Engineering Languages and Systems, ACM/IEEE, 393-407,
    8, October, 2009; (recipient of the MODELS 2009
    Distinguished Paper Award).
  • Plain text
    Jackie Man-Kit Leung, Thomas Mandl, Edward A. Lee, Elizabeth
    Latronico, Charles Shelton, Stavros Tripakis, Ben Lickly.
    "Scalable Semantic Annotation using Lattice-based
    Ontologies". 12th International Conference on Model
    Driven Engineering Languages and Systems, ACM/IEEE, 393-407,
    8, October, 2009; (recipient of the MODELS 2009
    Distinguished Paper Award).
  • BibTeX
    @inproceedings{LeungMandlLeeLatronicoSheltonTripakisLickly09_ScalableSemanticAnnotationUsingLatticebasedOntologies,
        author = {Jackie Man-Kit Leung and Thomas Mandl and Edward
                  A. Lee and Elizabeth Latronico and Charles Shelton
                  and Stavros Tripakis and Ben Lickly},
        title = {Scalable Semantic Annotation using Lattice-based
                  Ontologies},
        booktitle = {12th International Conference on Model Driven
                  Engineering Languages and Systems},
        organization = {ACM/IEEE},
        pages = {393-407},
        day = {8},
        month = {October},
        year = {2009},
        note = {(recipient of the MODELS 2009 Distinguished Paper
                  Award)},
        abstract = {Including semantic information in models helps to
                  expose modeling errors early in the design
                  process, engage a designer in a deeper
                  understanding of the model, and standardize
                  concepts and terminology across a development
                  team. It is impractical, however, for model
                  builders to manually annotate every modeling
                  element with semantic properties. This paper
                  demonstrates a correct, scalable and automated
                  method to infer semantic properties using
                  lattice-based ontologies, given relatively few
                  manual annotations. Semantic concepts and their
                  relationships are formalized as a lattice, and
                  relationships within and between components are
                  expressed as a set of constraints and acceptance
                  criteria relative to the lattice. Our inference
                  engine automatically infers properties wherever
                  they are not explicitly specified. Our
                  implementation leverages the infrastructure in the
                  Ptolemy II type system to get efficient and
                  scalable inference and consistency checking. We
                  demonstrate the approach on a non-trivial Ptolemy
                  II model of an adaptive cruise control system. },
        URL = {http://chess.eecs.berkeley.edu/pubs/611.html}
    }
    

Posted by Christopher Brooks on 4 Aug 2009.
Groups: pthomas
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