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440 articles for “Machine Learning”
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Research ArticleOpen accessPhrase in the titleArabic Poetry Authorship Attribution using Machine Learning TechniquesAl-Falahi Ahmed, Ramdani Mohamed, Bellafkih MostafaIn this study, authorship attribution in Arabic poetry will be conducted to determine the authorship of a specified text after documents with recognized authorships have been allocated. This work also measures the impact performance of Naïve Bayes, Support Vector Machine and Linear discriminant analysis for Arabic poetry authorship attribution using text mining classification. Several features such as lexical features, character … …Journal of Computer Science, Vol. 15, Issue 7 · 27 Jul 2019 · 150,975 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleA Hybrid Machine Learning Approach to Predictive Analytics in Precision Agriculture for Sustainable Crop OptimizationJignesh Kariya, Pankaj MudholkarDriven by data-enabled technologies, precision agriculture is evolving into an innovative way to increase agricultural productivity and sustainability. Conventional agricultural practices face several challenges, such as poor soil quality, inappropriate crop selection, improper resource utilization, and unpredictable climate conditions. To address these limitations, this paper proposes a hybrid machine learning framework for sustainable crop optimization and predictive analysis in precision … …Journal of Computer Science, Vol. 22, Issue 10 · 10 Oct 2026 · 865 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleA Machine Learning-Based Sentiment Analysis of Article 370 Tweets to Support Government Policy DecisionsSubhasis Mohapatra, Sudhir Kumar Mohapatra, Sweta Samantaray et al.This study proposes a robust sentiment analysis framework to evaluate public opinion on the abrogation of Article 370 using Twitter data. The methodology begins with tweet collection through the Twitter API, followed by systematic preprocessing. Sentiment labels were generated using the Text Blob lexicon-based polarity scoring approach to facilitate the construction of a large-scale sentiment dataset. Features are extracted, and … …Journal of Computer Science, Vol. 22, Issue 6 · 2 Jul 2026 · 914 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleAn Intelligent Hybrid Machine Learning Model for Paddy Disease DetectionS. Hrushikesava Raju, S. Adinarayna, U. Sesadri et al.Most countries rely on paddy/rice as a preferred staple crop due to its desirable agronomic characteristics. However, during the growth cycle, undetected or delayed identification of diseases can significantly reduce crop yield. To address this, machine learning approaches are increasingly employed for early-stage disease detection. Traditional Recurrent Neural Networks (RNNs), while useful for sequential data, suffer from limitations such as … …Journal of Computer Science, Vol. 22, Issue 4 · 29 Apr 2026 · 1,747 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleMoney Laundering Detection in Financial Institutions Using Machine LearningNoor Samer Masood, Rasha Hassan Sakr, Amal Abou EleneenThis research aims to develop a system based on machine learning techniques for the accurate detection and classification of money laundering transactions. This system utilizes real and synthetic financial data, including the IBM AML dataset and synthetic financial databases. The methodology included data collection and cleaning, feature extraction from transaction behavior, and training several classification algorithms, including Random Forest, Support … …Journal of Computer Science, Vol. 22, Issue 4 · 16 Apr 2026 · 2,325 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleDeveloping an Effective Churn Prediction Model for Telecommunications: Enhancing Customer Retention through Advanced Machine Learning TechniquesAshu Goyal, Anuj Gupta, Sharad Kumar et al.Customer churn poses a significant challenge for the telecommunications sector, resulting in substantial revenue losses and increased customer acquisition costs. This research creates an efficient churn prediction model that combines state-of-the-art machine learning with ensemble learning to maximize customer retention. With the IBM Telco Customer Churn dataset, several baseline models, including Gradient Boosting, AdaBoost, Logistic Regression, Random Forest, and Support … …Journal of Computer Science, Vol. 22, Issue 1 · 3 Feb 2026 · 3,164 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleA Comparative Study of Machine Learning Algorithms for Skin Cancer DetectionVineeth Victor, Amit Kumr Tyagi, Khushboo Tripathi et al.The skin is the largest organ in the human body, covering an area of around 20 square feet. Our skin keeps us safe from germs and the environment, helps us regulate our body temperature, and gives us the ability to feel touch, heat, and cold. More than 95 percent of all skin cancers are caused by ultraviolet (UV) radiation. UV … …Journal of Computer Science, Vol. 21, Issue 12 · 23 Jan 2026 · 1,859 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleIdentification of Fraud in Accidental and Healthcare Insurance Using Local Outlier Factor: A Machine Learning ApproachJyoti Lele, Vaidehi Deshmukh, Abhinav Chandra, Radhika DesaiAn unsupervised machine learning model that uses the mechanism of the Local Outlier Factor to flag and detect ambiguous as well as potentially fraudulent claims in Accidental and Healthcare insurance is proposed in this paper. It entirely automates the manual investigation of claims by claim appraisers in any organization. The ethos of this model is to comprehensively automate and expedite … …Journal of Computer Science, Vol. 21, Issue 12 · 22 Jan 2026 · 1,575 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleAnalyzing Public Sentiment on Demonetization Using SVM: A Machine Learning ApproachKaliappan M, Guruprakash B, Rajalakshmi et al.The Indian economy experienced significant disruption following the implementation of demonetization, a policy initiative aimed at eliminating black money, controlling inflation, and promoting financial inclusion. However, this currency ban generated widespread debate and polarized public opinion. This study analyzes public sentiment toward demonetization using social media data, specifically Twitter posts characterized by mixed sentiments, sarcasm, and nuanced linguistic expressions. We … …Journal of Computer Science, Vol. 21, Issue 11 · 18 Dec 2025 · 2,235 accessesView PDFCite
Research ArticleOpen accessPhrase in the titlePredicting Financial Statement Failure of Listed Firms in Market for Alternative Investment (mai) using Machine LearningPattanapong Kumsin, Salakjit Ninlaphay, Anupong SukprasertThe purpose of this research is to investigate the financial ratios of companies listed on the Market for Alternative Investment (mai) in Thailand, as well as the likelihood of these companies' financial statement failure. It also intends to create a financial statement failure predicting model for companies listed on the mai and assess the performance of various forecasting models using … …Journal of Computer Science, Vol. 21, Issue 9 · 24 Nov 2025 · 2,240 accessesView PDFCite