Titlebook: Artificial Intelligence Applications and Innovations; 16th IFIP WG 12.5 In Ilias Maglogiannis,Lazaros Iliadis,Elias Pimenidis Conference pr

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An Adaptive Approach on Credit Card Fraud Detection Using Transaction Aggregation and Word Embedding which is trained on the merchant names of the transactions. The other contribution is introducing a new strategy for training dataset generation employing the sliding window approach in a given time frame to adapt to the changes on the trends of fraudulent transactions. In the experiments, the feat

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Boosted Ensemble Learning for Anomaly Detection in 5G RANaffic in a city. Our ensemble learns the functional behaviour of an application by training on logs from normal execution time. It can then detect deviations from normal behaviour and also be retrained on false positive cases found during validation. Anomaly detection in RAN shows that our ensemble

看法等

Machine Learning for Cognitive Load Classification – A Case Study on Contact-Free Approach HRV features were extracted in a controlled study to determine three levels of CL i.e., S0: low CL, S1: normal CL and S2: high CL. To get the best classification accuracy with the ML algorithms, different optimizations such as kernel functions were chosen with different feature matrices both for bi

nephritis

crockery

PolicyCLOUD: Analytics as a Service Facilitating Efficient Data-Driven Public Policy Managementdata ready for use. An innovative approach for analytics as a service is introduced and linked with a policy development toolkit, which is an integrated web-based environment to fulfil the requirements of the public policy ecosystem stakeholders.

Guaff豪情痛饮

fatty-streak

HILAR

An Innovative Graph-Based Approach to Advance Feature Selection from Multiple Textual Documentsost text classifiers employed and decreases the number of features required to achieve ‘state-of-the-art’ accuracy. Well-known datasets used for the experimentations reported in this paper include ., ., . and ..

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Explainable AI Methods and Applications,centrating in one region of the projection space. This region is identified using Density-based Spatial Clustering of Applications with Noise. Applicant companies which are projected within this region are labeled potential funding recipients and will be suggested the most competitive funding mechanisms.