5th International Symposium on Data Mining Applications [electronic resource] /
Contributor(s): Alenezi, Mamdouh [editor.] | Qureshi, Basit [editor.] | SpringerLink (Online service).
Series: Advances in Intelligent Systems and Computing: 753Publisher: Cham : Springer International Publishing : Imprint: Springer, 2018Edition: 1st ed. 2018.Description: XVI, 248 p. 98 illus. | Binding - Card Paper |.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319787534.Subject(s): Computer Engineering
| Computational Intelligence | Artificial IntelligenceDDC classification: 006.3 Online resources: Click here to access eBook in Springer Nature platform. (Within Campus only.)
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Springer Nature eBookSummary: The 5th Symposium on Data Mining Applications (SDMA 2018) provides valuable opportunities for technical collaboration among data mining and machine learning researchers in Saudi Arabia, Gulf Cooperation Council (GCC) countries and the Middle East region. This book gathers the proceedings of the SDMA 2018. All papers were peer-reviewed based on a strict policy concerning the originality, significance to the area, scientific vigor and quality of the contribution, and address the following research areas. • Applications: Applications of data mining in domains including databases, social networks, web, bioinformatics, finance, healthcare, and security. • Algorithms: Data mining and machine learning foundations, algorithms, models, and theory. • Text Mining: Semantic analysis and mining text in Arabic, semi-structured, streaming, multimedia data. • Framework: Data mining frameworks, platforms and systems implementation. • Visualizations: Data visualization and modeling.
The 5th Symposium on Data Mining Applications (SDMA 2018) provides valuable opportunities for technical collaboration among data mining and machine learning researchers in Saudi Arabia, Gulf Cooperation Council (GCC) countries and the Middle East region. This book gathers the proceedings of the SDMA 2018. All papers were peer-reviewed based on a strict policy concerning the originality, significance to the area, scientific vigor and quality of the contribution, and address the following research areas. • Applications: Applications of data mining in domains including databases, social networks, web, bioinformatics, finance, healthcare, and security. • Algorithms: Data mining and machine learning foundations, algorithms, models, and theory. • Text Mining: Semantic analysis and mining text in Arabic, semi-structured, streaming, multimedia data. • Framework: Data mining frameworks, platforms and systems implementation. • Visualizations: Data visualization and modeling.
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