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Article

Automatic Classification of Web Images as UML Static Diagrams Using Machine Learning Techniques

Knowledge Reuse Group, Departamento de Informática, Universidad Carlos III de Madrid. Av. Universidad 30, 28911 Leganés (Madrid), Spain
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Appl. Sci. 2020, 10(7), 2406; https://doi.org/10.3390/app10072406
Received: 14 February 2020 / Revised: 25 March 2020 / Accepted: 30 March 2020 / Published: 1 April 2020
(This article belongs to the Special Issue Knowledge Retrieval and Reuse)
Our purpose in this research is to develop a method to automatically and efficiently classify web images as Unified Modeling Language (UML) static diagrams, and to produce a computer tool that implements this function. The tool receives a bitmap file (in different formats) as an input and communicates whether the image corresponds to a diagram. For pragmatic reasons, we restricted ourselves to the simplest kinds of diagrams that are more useful for automated software reuse: computer-edited 2D representations of static diagrams. The tool does not require that the images are explicitly or implicitly tagged as UML diagrams. The tool extracts graphical characteristics from each image (such as grayscale histogram, color histogram and elementary geometric forms) and uses a combination of rules to classify it. The rules are obtained with machine learning techniques (rule induction) from a sample of 19,000 web images manually classified by experts. In this work, we do not consider the textual contents of the images. Our tool reaches nearly 95% of agreement with manually classified instances, improving the effectiveness of related research works. Moreover, using a training dataset 15 times bigger, the time required to process each image and extract its graphical features (0.680 s) is seven times lower. View Full-Text
Keywords: UML diagram recognition; image processing; image classification; rule induction; classification tool UML diagram recognition; image processing; image classification; rule induction; classification tool
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MDPI and ACS Style

Moreno, V.; Génova, G.; Alejandres, M.; Fraga, A. Automatic Classification of Web Images as UML Static Diagrams Using Machine Learning Techniques. Appl. Sci. 2020, 10, 2406. https://doi.org/10.3390/app10072406

AMA Style

Moreno V, Génova G, Alejandres M, Fraga A. Automatic Classification of Web Images as UML Static Diagrams Using Machine Learning Techniques. Applied Sciences. 2020; 10(7):2406. https://doi.org/10.3390/app10072406

Chicago/Turabian Style

Moreno, Valentín, Gonzalo Génova, Manuela Alejandres, and Anabel Fraga. 2020. "Automatic Classification of Web Images as UML Static Diagrams Using Machine Learning Techniques" Applied Sciences 10, no. 7: 2406. https://doi.org/10.3390/app10072406

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