Academic Journal
Automatic classification of web images as UML static diagrams using machine learning techniques
| العنوان: | Automatic classification of web images as UML static diagrams using machine learning techniques |
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| المؤلفون: | Moreno Pelayo, Valentín, Génova Fuster, Gonzalo, Alejandres Sánchez, Manuela, Fraga Vázquez, Anabel |
| المساهمون: | European Commission, Ministerio de Economía y Competitividad (España) |
| بيانات النشر: | MDPI |
| سنة النشر: | 2020 |
| المجموعة: | Universidad Carlos III de Madrid: e-Archivo |
| مصطلحات موضوعية: | uml diagram recognition, image processing, image classification, rule induction, classification tool, Informática |
| الوصف: | 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. ; This research has received funding from the CRYSTAL project – Critical System Engineering Acceleration (European Union’s Seventh Framework Program, FP7/2007-2013, ARTEMIS Joint Undertaking grant agreement n° 332830); and from the AMASS project – Architecture-driven, Multi-concern and Seamless Assurance and Certification of Cyber-Physical Systems (H2020-ECSEL grant agreement nº 692474; Spain’s MINECO ref. PCIN-2015-262). |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | English |
| تدمد: | 2076-3417 |
| Relation: | info:eu-repo/grantAgreement/EC/ART-010000-2013-1; info:eu-repo/grantAgreement/EC/692474; Gobierno de España. PCIN-2015-262; 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; http://hdl.handle.net/10016/34175; https://doi.org/10.3390/app10072406; 2406; Applied Sciences (Switzerland); 10; AR/0000029188 |
| DOI: | 10.3390/app10072406 |
| الاتاحة: | http://hdl.handle.net/10016/34175 https://doi.org/10.3390/app10072406 |
| Rights: | © MDPI, 2020 ; Atribución 3.0 España ; http://creativecommons.org/licenses/by/3.0/es/ ; open access |
| رقم الانضمام: | edsbas.AF3C0EBC |
| قاعدة البيانات: | BASE |
Full Text Finder | تدمد: | 20763417 |
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| DOI: | 10.3390/app10072406 |