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118 results for “Data-driven”
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Research ArticleOpen accessIn the keywordsOptimized 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 · 6,185 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Design of MAC Model Based on the Separation of Duties and Data Coloring: DSDC-MACSoon-Book Lee, Yoo-Hwan Kim, Jin-Woo Kim, Chee-Yang SongAmong the access control methods for database security, there is Mandatory Access Control (MAC) model in which the security level is set to both the subject and the object to enhance the security control. Legacy MAC models have focused only on one thing, either confidentiality or integrity. Thus, it can cause collisions between security policies in supporting confidentiality and integrity … …Journal of Computer Science, Vol. 16, Issue 1 · 19 Jan 2020 · 7,463 accessesView PDFCite
Research NotesOpen accessIn the abstractMetadata Stewardship and Quality in Telecom SectorBhola Gan Chaudhuri, Shalli RaniThe spread of the telecom network infrastructure, constellations of satellites and the use of the Internet of Things (IoT) have brought about unprecedented volumes of heterogeneous information which facilitate the contemporary monitoring systems of the environment and the earth. Metadata control and information quality have also become significant in the telecom industry in controlling data reliably, enhancing data services, and … …Journal of Computer Science, Vol. 22, Issue 10 · 22 Oct 2026 · 426 accessesView PDFCite
Research ArticleOpen accessIn the abstractA 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 · 879 accessesView PDFCite
Research ArticleOpen accessIn the abstractDetermination of Crop Yield Detection and Prediction With Multimodal Data Using Fusion TechniquesKutlwano Sedimo, Rajalakshmi Selveraj, Venumadhav Kuthadi, Thulaganyo DimakatsoMost often, soil, environmental, and agronomic data are used in pieces, hence limiting the performance of crop selection and yield forecasting. This study develops an integrated, fusion-based framework that combines soil image classification, environmental feature analysis, and input-driven yield prediction to support precise agricultural decision-making. The system consists of three major modules: (i) a CNN for the classification of soil … …Journal of Computer Science, Vol. 22, Issue 10 · 5 Oct 2026 · 494 accessesView PDFCite
Research ArticleOpen accessIn the abstractDynamic Knowledge Driven Multi-Scale Spatiotemporal Fusion Framework for Reliable Multi-Horizon Traffic Flow ForecastingDeepika M S, P. Deepa Shenoy, Venugopal K RAccurate traffic flow forecasting remains a core challenge in intelligent transportation systems. Urban traffic patterns are characterised by complex spatiotemporal dependencies and inherent uncertainties, which complicate traffic forecasting. This study proposes a Dynamic Knowledge-Driven Spatiotemporal Fusion (DKDMSF) architecture to extract features of Multi-Scale traffic dynamics across various temporal traffic horizons. DKDMSF integrates Dynamic Spatial Attention (DSA) and Adaptive Graph Learning … …Journal of Computer Science, Vol. 22, Issue 9 · 30 Sep 2026 · 422 accessesView PDFCite
Research ArticleOpen accessIn the abstractDengue Fever Prediction Empowered by Radial Basis Function Networks, Dynamic Mode Decomposition, and Learning-Based Foraging AlgorithmArchana T, Faritha Banu JDengue fever is presently considered a major health threat that must be addressed. External and internal factors that induce nonlinear oscillations in the occurrence of dengue disease have made optimal resource allocation stimulating. Public health initiatives aimed at eradicating this vector use accurate and timely data through field processes. In dengue-endemic nations, early dengue prediction remains a main concern for … …Journal of Computer Science, Vol. 22, Issue 4 · 16 Apr 2026 · 1,505 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Systematic Literature Review on Data Integration: Issues, Data Types, ArchitectureMimi Haryani Tasani, Mohd Kamir YusofData integration is an important process that enables organizations to merge data from various sources, creating a consolidated viewpoint that supports better decision-making, increased effectiveness, and deeper insights. Although data integration has advantages, it also comes with difficulties like maintaining data quality, adhering to compliance regulations, resolving technical issues, and merging with older systems. Effective management of data quality, robust … …Journal of Computer Science, Vol. 22, Issue 2 · 18 Feb 2026 · 1,815 accessesView PDFCite
Review ArticleOpen accessIn the abstractAI-Driven Innovations in Meat Quality and Safety: Applications, Challenges, and Future DirectionsEmrobowansan Monday IdamokoroArtificial Intelligence (AI) is revolutionizing the meat sector by improving efficiency, accurateness, as well as sustainability in meat production, quality evaluation, and safety control. The conventional systems of meat inspection, handling, and processing are usually time consuming, labour-intensive, prone to contamination during handling and often susceptible to human errors. The use of artificial intelligence to drive technologies, including Deep Learning … …American Journal of Biochemistry and Biotechnology, Vol. 21, Issue 3 · 28 Jan 2026 · 3,686 accessesView PDFCite
Review ArticleOpen accessIn the abstractBibliometric Analysis of Missing Value Imputation (MVI) Research Using Python and VOSviewer: Trends and Future DirectionsSamsul Arifin, Muhammad Faisal, Edwin Kristianto Sijabat et al.Incomplete data is a pervasive issue in data science, posing significant challenges for statistical analysis and machine learning applications. Missing Value Imputation (MVI) has thus emerged as a critical area of research aimed at mitigating data quality issues and improving decision-making accuracy. This study presents a comprehensive bibliometric analysis of MVI research using Scopus-indexed publications from 2000 to 2024. The … …Journal of Computer Science, Vol. 21, Issue 12 · 20 Jan 2026 · 1,968 accessesView PDFCite