Titlebook: Advances in Information Systems, Artificial Intelligence and KnowledgeManagement; 6th International Co Inès Saad,Camille Rosenthal-Sabroux,

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Advances in Information Systems, Artificial Intelligence and KnowledgeManagement978-3-031-51664-1Series ISSN 1865-1348 Series E-ISSN 1865-1356

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https://doi.org/10.1057/9780230281202vailable set of options. The Recommender System (RS) solves the problem of information overload by suggesting items of interest to the user. It has grown in popularity over the last few decades, and a significant amount of research has been conducted in this field. Among them, Collaborative Filterin

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Human Resources and Market Reforms to capture information intended to permit competitive advances. In this context, regarding Multi-Criteria Decision-Making/Aiding problems, several DSSs have been proposed to support DMs to deal with complex problems. This paper presents the DSS constructed to implement the FITradeoff method. Severa

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Citizenship and Democratizationns have been proposed. The most famous methods are based on the Synthetic Minority Over-sampling Technique (SMOTE), which creates new synthetic instances in the minority class. In this paper, we study the efficiency of the SMOTE-based methods on some imbalanced data sets. We then propose extending t

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Training Policy and Decentralizations) to this problem. This paper summarizes the different GA based approaches for community detection in PPIs and provides a taxonomy of these methods. Detailed comparative studies are then provided comparing an evolutionary graph-clustering approach (EGCPI) based on the partitioning paradigm and an e

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Nasreen Chowdhory,Biswajit Mohanty model based on a process approach. This can be achieved by adopting a multidisciplinary approach that combines the fields of Knowledge Management, Business Process Management and Process Mining. Therefore, to improve their performance and increase their responsiveness, organizations must identify,

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Nasreen Chowdhory,Biswajit Mohanty monitoring for surveillance and assisted living purposes. However, recognizing human activities is a challenging task because of the variety of human actions in daily life. In this work, we propose to extract skeletons from RGB images using deep learning architectures while adopting hand-crafted fe