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32 articles for “supervised methods”
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Research ArticleOpen accessIn the abstractOptimized Feature Selection Approach for Semi-Supervised Sentiment Analysis of E-Commerce FeedbackAlok Kumar Jena, Kakita Murali Gopal et al.In this globalized world, people prefer to buy products online without any hesitation. Usually, to acquire the quality of the product or brand, they examine the product’s reviews, which is a tedious job to do manually. The wide use of social media also encourages the users, to keep their views on the product in a global platform. By using machine … …Journal of Computer Science, Vol. 21, Issue 2 · 16 Jan 2025 · 6,179 accessesView PDFCite
Research ArticleOpen accessIn the abstractCybersecurity Mechanism for Automatic Detection of IoT Intrusions Using Machine LearningCheikhane Seyed, MBaye Kebe, Mohamed El Moustapha El Arby et al.This article proposes an ML-based cyber security mechanism to optimize intrusion detection that attacks internet objects (IoT). Our approach consists of bringing together several learning methods namely supervised learning, unsupervised learning and reinforcement learning within the same Canvas. The objective is to choose among them the most optimal for classifying and predicting attacks while minimizing the impact linked to the … …Journal of Computer Science, Vol. 20, Issue 1 · 11 Dec 2023 · 6,176 accessesView PDFCite
Review ArticleOpen accessIn the abstractCrime Prediction Using Machine Learning: A Comparative AnalysisAbdulrahman Alsubayhin, Muhammad Ramzan, Bander AlzahraniIn the past few years, Machine Learning (ML) methods have acquired extensive attention from researchers and even criminology practitioners for their potential in crime prediction and crime forecast. To date, many research studies have already been performed on crime prediction using machine learning techniques. Some common methods that have been used include KNNs, Decision trees, Naïve Bayes, and random forest, … …Journal of Computer Science, Vol. 19, Issue 9 · 29 Aug 2023 · 8,063 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Systematic Review Regarding the Prediction of Academic PerformancePercy De-La-Cruz, Rommel Rojas-Coaquira, Hugo Vega-Huerta et al.The prediction of students' academic performance is an area of great concern for universities and educational institutions since academic performance is one of the most important aspects of the learning process. To analyze this behavior, this study makes a critical analysis of the topic of interest and aims to review, analyze and summarize the latest research advances related to the … …Journal of Computer Science, Vol. 18, Issue 12 · 23 Dec 2022 · 8,602 accessesView PDFCite
Research ArticleOpen accessIn the abstractEvaluation of Transfer Learning for Mask DetectionZahin Akram, Arifuzzaman Arman, Mohammad Rakib Imtiaz, Syed Athar Bin AmirThe use of masks has become crucial in combating the Coronavirus pandemic. Unfortunately, the regulation of wearing a mask is not being upheld by many citizens which is contributing to the spread of the disease. To aid the efforts of regulations and to maintain safety in public areas, both large like parks or small like public transport, Artificial Intelligent systems … …Journal of Computer Science, Vol. 18, Issue 2 · 3 Mar 2022 · 6,931 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Survey on Event Detection Models for Text Data StreamsWafa Zubair AL-Dyani, Farzana Kabir Ahmad, Siti Sakira KamaruddinEvent Detection (ED) is a study area that attracts the attention of decision-makers from various disciplines in order to help them in taking the right decision. ED has been examined on various text streams like Twitter, Facebook, Emails, Blogs, Web Forums and newswires. Many ED models have been proposed in literature. In general, ED model consists of six main phases: … …Journal of Computer Science, Vol. 16, Issue 7 · 14 Jul 2020 · 7,038 accessesView PDFCite
Review ArticleOpen accessIn the abstractWord Sense Disambiguation: Survey StudyAhmed H. Aliwy, Hawraa A. TaherThe process of identifying the correct sense of a given word in a particular sentence is called Word Sense Disambiguation (WSD). It is complex problem because it involves drawing knowledge from various sources. Significant amount of effort has been put into resolving this problem in machine learning since its inception but the toil is still ongoing. Many techniques were used … …Journal of Computer Science, Vol. 15, Issue 7 · 26 Jul 2019 · 8,388 accessesView PDFCite
Literature ReviewOpen accessIn the abstractEfficient Morphometric Techniques in Alzheimer’s Disease Detection: Survey and ToolsVinutha N., P. Deepa Shenoy, K.R. VenugopalThe development of advance techniques in the multiple fields such as image processing, data mining and machine learning are required for the early detection of Alzheimer’s Disease (AD) and to prevent the progression of the disease to the later stages. The longitudinal and cross sectional images of elderly subjects were obtained from the standard datasets like ADNI, OASIS, MIRIAD and … …Neuroscience International, Vol. 7, Issue 2 · 4 Oct 2017 · 8,450 accessesView PDFCite
Research ArticleOpen accessIn the abstractPrototype-Based Sample Selection for Active HashingCheong Hee ParkSeveral hashing-based methods for Approximate Nearest Neighbors (ANN) search in a large data set have been proposed recently. In particular, semi-supervised hashing utilizes semantic similarity given for a small fraction of pairwise data samples and active hashing aims to improve the performance for ANN search by relying on an expert for the labeling of the most informative points. In this … …Journal of Computer Science, Vol. 11, Issue 7 · 2 Nov 2015 · 6,736 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Survey of Anomaly Detection Using Data Mining Methods for Hypertext Transfer Protocol Web ServicesMohsen Kakavand, Norwati Mustapha, Aida Mustapha et al.In contrast to traditional Intrusion Detection Systems (IDSs), data mining anomaly detection methods/techniques has been widely used in the domain of network traffic data for intrusion detection and cyber threat. Data mining is widely recognized as popular and important intelligent and automatic tools to assist humans in big data security analysis and anomaly detection over IDSs. In this study we … …Journal of Computer Science, Vol. 11, Issue 1 · 22 Jan 2015 · 9,252 accessesView PDFCite