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Constructing and Visualizing Models using Mime-based Machine-learning Framework
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LEGO-MM: LEarning Structured Model by Probabilistic loGic Ontology Tree for MultiMedia.

Jinhui Tang, Shiyu Chang, Guo-Jun Qi

    IEEE Transactions on Image Processing : a Publication of the IEEE Signal Processing Society
    |January 24, 2017
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces LEGO-MM, a novel framework for building complex multimedia concept models by integrating existing models and new data. LEGO-MM significantly outperforms methods that construct models from scratch.

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    Area of Science:

    • Computer Science
    • Artificial Intelligence
    • Multimedia Analysis

    Background:

    • Multimedia ontology research has yielded public concept models.
    • Current methods primarily focus on building new concepts from scratch.
    • A gap exists in methods for constructing new concepts upon existing models.

    Purpose of the Study:

    • To propose a novel framework, LEGO-MM, for constructing complex multimedia concept models.
    • To enable seamless integration of new training examples with existing primitive concept models.
    • To address the limitations of current 'from scratch' concept model construction.

    Main Methods:

    • LEGO-MM utilizes probabilistic logic ontology trees to hierarchically combine existing concept models.
    • Logic operations are formulated as 'lego connectors' for model integration.
    • New target training information is incorporated to disambiguate logic trees and correct errors.

    Main Results:

    • LEGO-MM demonstrated significantly superior performance on a large vehicle dataset from ImageNet.
    • The framework effectively integrates new data with existing primitive concept models.
    • Experimental results validate the efficacy of the proposed approach over state-of-the-art methods.

    Conclusions:

    • LEGO-MM offers an effective approach for building complex concept models by leveraging existing resources.
    • The framework provides a method to construct an extensive vocabulary of concepts.
    • This research advances multimedia ontology by enabling efficient and accurate concept model construction.