Abstract
For several years now, thanks to the emergence of new information and communication technologies, information has become increasingly available and accessible. The IT field today has a very large amount of data allowing the search for any information. However, exploiting this large amount of data makes finding and classifying precise data complex and time consuming. This difficulty has motivated the development of new adapted data classification tools. Classification is first used to refer to the division of a set of individuals into classes so that every individual belongs to one class and only one. But the term classification is also used to designate nested systems of classes so we can say that it is a statistical operation which consists in grouping objects (individuals or variables or observations) into a limited number of groups (classes, segments), and to classify individuals according to some of their characteristics. There are different types of classification, but one of the most intuitive and widely used is supervised classification. The overall objective of the classification is to identify the classes to which objects belong based on descriptive features (attributes, characteristics). Data classification is a delicate problem that arises in many sciences such as data mining analysis. The broker's primary goal is to reduce the overhead costs associated with managing web service level agreements, while maintaining compatibility with existing infrastructure and vendors.
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Bakraouy, Z., Baina, A., Bellafkih, M. (2021). Agreement-Broker: Performance Analysis Using KNN, SVM, and ANN Classifiers. In: Abraham, A., et al. Proceedings of the 12th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2020). SoCPaR 2020. Advances in Intelligent Systems and Computing, vol 1383. Springer, Cham. https://doi.org/10.1007/978-3-030-73689-7_82
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