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https://hdl.handle.net/11499/51548
Title: | Web-Based Visualization and Analysis Framework for Graph Data | Authors: | Şentürk, F. Bilici, M.A. Tanışman, S. Aytaç, V. |
Keywords: | Clustering algorithms Data mining Data visualization Graphic methods Image segmentation Web services Websites Analysis frameworks AS graph Data clustering Graph data Images segmentations Visualization and analysis Visualization framework Web interface Web-based analysis Web-based visualization Graph theory |
Publisher: | Springer Science and Business Media Deutschland GmbH | Abstract: | Graph theory has many applications in computer science. Graphs are involved in the mathematical modeling of problems belonging to very popular computer and data science, such as data mining, data clustering, computer network, image segmentation, etc. Graph theory is used in computer science to solve problems modeled as graphs. However, many applications do not have an interface that displays and edits graphs instantly. Moreover, these applications are not supported with a web interface. In this study, a web interface has been developed that support graph theory concepts, display more than one graph simultaneously, have a user-friendly interface, and include algorithms to analyze graphs. Also, we present a web service for these graph analyzing algorithms. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. | Description: | 2nd International Semantic Intelligence Conference, ISIC 2022 -- 17 May 2022 through 19 May 2022 -- 291239 | URI: | https://doi.org/10.1007/978-981-19-7126-6_2 https://hdl.handle.net/11499/51548 |
ISBN: | 9789811971259 | ISSN: | 1876-1100 |
Appears in Collections: | Mühendislik Fakültesi Koleksiyonu Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection |
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