Research ArticleOpen accessPhrase in the titlePersonalized Recommendation System: Web of Things Using Modular Density-Based Community DiscoveryVinod Patidar, Jayashree A. Patil, Sonika Thapak et al.Community discovery is the cornerstone and core of study in customized recommendation, assembling group features and social network analysis on the web of things. Conventional community discovery methods, however, struggle with difficulties including low accuracy, delayed convergence, modularity resolution limits and more when dealing with more complicated social networks. Because of this, differential evolution and module density are included in … …Journal of Computer Science, Vol. 20, Issue 9 · 21 Jun 2024 · 5,628 accessesView PDFCite
Research ArticleOpen accessIn the abstractHybrid Enhanced Neighbourhood and Latent Factor Model for Cold-Start RecommendationsAmritha P, Rajkumar KKAmong different recommendation strategies, collaborative filtering remains a commonly utilized method for generating personalized suggestions. The traditional collaborative algorithms face performance declines due to the sparse rating of data and the item cold-start problem. To overcome these challenges, this paper introduces a novel hybrid model called HCE-KNNCF (Hybrid Cognition-Enabled K-Nearest Neighbor Collaborative Filtering). The proposed model generates predicted rating by … …Journal of Computer Science, Vol. 22, Issue 9 · 21 Sep 2026 · 622 accessesView PDFCite
Research ArticleOpen accessIn the abstractMedFusion: A Unified Multimodal Framework for Visual Question Answering and Explainable Medical RecommendationSatyajit Mahapatra, Jibitesh Mishra, Kumar Janardan Patra et al.In clinical decision-making, the ability to ask visual questions about medical images and receive accurate, personalized, and interpretable recommendations can significantly enhance practitioner support systems. This paper presents MedFusion, a unified multimodal framework that integrates Visual Question Answering (VQA), personalized medical recommendation, and explainability within a single architecture. The proposed model employs co-attention–based visual–textual fusion augmented with retrieval-enhanced reasoning to … …Journal of Computer Science, Vol. 22, Issue 5 · 20 May 2026 · 1,360 accessesView PDFCite
Research ArticleOpen accessIn the abstractAn AI-Powered Integrated Care Model Combining Traditional Chinese Medicine and Western Medicine for Personalized Alzheimer’s Disease ManagementShurong Li, Yiming Chen, Jin Xu et al.Alzheimer's Disease (AD) gradually reduces memory and cognition. While Western medicine focuses on pharmacological treatments, it frequently ignores holistic factors such as mood and digestion. Traditional Chinese Medicine (TCM) addresses these issues through a wellness-oriented approach. However, the combination of both systems in patient care is uncommon. Current Alzheimer's disease treatments are often siloed, relying solely on Western or alternative … …American Journal of Biochemistry and Biotechnology, Vol. 21, Issue 4 · 16 Feb 2026 · 2,063 accessesView PDFCite
Research ArticleOpen accessIn the abstractPost-COVID Impact Analysis and Effective Recommendation Solutions Over Risk Prediction Using Hybrid ModelBoddeti Jaggan Mohan Ravi Kumar, P. V. G. D. Prasad Reddy, G SrinivasThe COVID-19 pandemic (2019-2022) resulted in significant global mortality, largely attributed to the virus's unpredictable pathophysiology, rapid disease progression affecting multiple organ systems, and initial lack of effective treatments. This study systematically examines post-COVID-19 complications across major organ systems, including respiratory dysfunction, cardiovascular complications, renal disorders, musculoskeletal pain, gastrointestinal disturbances, neurological sequelae, alopecia, endocrine and metabolic dysregulation, and mental health … …Journal of Computer Science, Vol. 21, Issue 11 · 23 Dec 2025 · 1,643 accessesView PDFCite
Review ArticleOpen accessIn the abstractWeb Scraping for Product Recommendations: A Review of Techniques and ApplicationsAmarinder Kaur, Deepak PrasharA comprehensive method for developing a reliable product recommender system leveraging sophisticated web scraping technologies, machine learning, and natural language processing techniques. The proposed system addresses key challenges in personalized product recommendation, including the difficulty of integrating diverse data from multiple e-commerce platforms, ensuring data quality, and improving recommendation accuracy to enhance user experience. Specifically, this research tackles issues related … …Journal of Computer Science, Vol. 21, Issue 6 · 21 Jun 2025 · 4,225 accessesView PDFCite
Research ArticleOpen accessIn the abstractThe Impact of Artificial Intelligence on Social Media ContentElsir Ali Saad Mohamed, Murtada Elbashir Osman, Badur Algasim MohamedArtificial Intelligence (AI) has become a powerful tool for creating and managing social media content. Social media platforms have integrated AI technology into their algorithms to optimize the user experience. However, the impact of AI on social media is a topic of debate. This research aims to explore the effects of AI and its implications for content creators and consumers. … …Journal of Social Sciences, Vol. 20, Issue 1 · 22 Apr 2024 · 39,784 accessesView PDFCite
Research ArticleOpen accessIn the abstractMicro-Retargeted Advertising and Online Shoppers' Motivation in NigeriaJoseph Wilson, Yusuf Mu'azu, Fredrick WilsonOnline shopping is increasingly gaining popularity worldwide, as the experience is perceived not only to replicate but sometimes exceed that of traditional retail. The rapid transformation of the e-commerce sector compels online stores to adopt innovative strategies to attract and retain customers, enhance service delivery, increase product visibility, and remain competitive. The integration of big data and artificial intelligence has … …Journal of Social Sciences, Vol. 21, Issue 1 · 15 Aug 2025 · 5,437 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Study on Emotion Analysis and Music Recommendation Using Transfer LearningKrishna Kumar Singh, Payal DemblaAs more and more people access and consume music through streaming platforms and digital services, music recommendation has grown in importance within the music industry. Given the abundance of music at our disposal, music recommendation algorithms are essential for guiding users toward new music and for creating individualized listening experiences. People frequently seek out music that fits their current emotional … …Journal of Computer Science, Vol. 19, Issue 6 · 16 May 2023 · 7,109 accessesView PDFCite