... This paper presents a lightweight, scalable framework that integrates fuzzy C-means clustering with a Variable Selection Ensemble Machine Learning Algorithm to detect and mitigate various types of DoS attacks, including black hole, grey hole, flooding and scheduling attacks. Findings The proposed...

... defect – prediction models. Corresponding author Sihan Chen sihanchen@csu.edu.cn 27 05 2025 17 06 2025 17 06 2025 © 2025 Emerald Publishing Limited 2025 Emerald Publishing Limited Licensed re-use rights only Deep learning Machine learning Feature selection Web...

... Limited Licensed re-use rights only IoT Network security Intrusion detection system (IDS) Machine learning Smart village Neural networks are used to learn patterns from data in deep learning, a subfield of machine learning. Many areas, including anomaly detection, have benefited from its...

..., training and evaluating the ability to detect Android malware based on popular machine learning algorithms such as Random Forest, support vector machine, K-nearest neighbor, logistic regression and one of the most powerful machine learning algorithms currently available, gradient boosting regression...

... physical interoperability together are required. Design/methodology/approach This paper aims to identify the most relevant points in the development of semantic models and machine learning solutions to the interoperability problem, and how these solutions are implemented in CPS. The research analyzes...

... Natural language processing Fake news Machine learning Gated recurrent unit Bidirectional LSTM (bi-LSTM) Hyperparameters Fine tuning In earlier times, people get their daily news and analysis from different sources like newspapers, televisions, etc. But with the arrival of the internet...

...Quang-Vinh Dang Purpose This study aims to explain the state-of-the-art machine learning models that are used in the intrusion detection problem for human-being understandable and study the relationship between the explainability and the performance of the models. Design/methodology/approach...

... (FTF-IDF) and uses the neutrosophic reasoning to analyze and generate weights for terms in natural languages. The paper also propose a comparative study between the popular FTF-IDF and NTF-IDF and their impacts on different machine learning (ML) classifiers for document categorization goals. Design...

... the service. The setting price of the new accommodation is often based on location, the number of beds, type of house and so on. The main problem is to predict the most reasonable price for the host. This paper aims to study the use of machine learning and sentiment analysis for predicting the price of online...

...Paolo Dello Vicario; Valentina Tortolini Purpose The purpose of this paper is to define a methodology to analyze links between programming topics and libraries starting from GitHub data. Design/methodology/approach This paper developed an analysis over machine learning repositories on GitHub...

... for achieving the viability of projects. Despite its importance and adoption growth, the success rate of crowdfunding campaigns was 47% in 2017, and it has decreased over the years. A way of increasing the chances of success of campaigns would be to predict, by using machine learning techniques, if a campaign...

... the same combination, the purity and F-measure criteria reach more than 90% for all the considered data sets. Originality/value The originality of this paper lies in two aspects: first, a new machine learning pipeline for RDF data is presented; second, an efficient process to identify...

.... Section 3 introduces the methodology adopted during this research. Section 4 deals with the results obtained, in terms of the machine learning performances’ and the generated association rules. The results are discussed in Section 5 and Section 6 concludes. Identifying all the learners at risk...

... Semantic web Machine learning Web services Given the growing popularity and increased presence of web services (WS), efficient mechanisms and tools are required to facilitate their matchmaking, publishing, discovery and semantic annotation. Service categorization is considered to be an essential...