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241 articles for “recommendation systems”
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A Polymer-Based Recommender System for Precision Agriculture: Enhancing Crop Yield Analysis Using IoT Technology
Abstract: This study introduces an innovative recommender system that employs polymer-based sensors combined with advanced data analytics to deliver personalized recommendations for crop management optimization. The use of polymer-based materials in sensor design allows for the creation of durable, cost-effective, and efficient sensors, well-suited for the challenging conditions typical in agricultural environments. These sensors are designed to withstand variations in numerous factors like temperature of the surrounding, humidity level, and at …
Published in Journal of Polymer & Composites · Vol. 13, Issue 2, 2025 · pp. 86–95 Read article
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A Novel Hybrid Link Prediction Algorithm for E-Commerce Recommender System Based upon Common Neighbor and Resource Allocation Methods
Abstract: Link prediction is a challenging task in recommender systems, as it requires the ability to accurately predict future links between users and items. In this study, we propose a novel hybrid link prediction algorithm for e-commerce recommender systems that combines the common neighbor and resource allocation methods. The common neighbor method is a straightforward and intuitive algorithm that calculates the number of shared neighbors between two nodes. The intuition is …
Published in International Journal of Data Structure Studies · Vol. 1, Issue 1, 2023 · pp. 12–17 Read article
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Fuzzy Logic Driven Nutrition-based Recommendation System for Gujarati Cardiac Patients: Integrating Cultural Preferences and Patient Feedback
Abstract: This article focuses on developing a comprehensive dataset for accurate dietary recommendations tailored to Gujarati cardiac patients' needs. The dataset comprises nutritional details of over 90 Gujarati food and fruit products, meticulously collected through primary and secondary data collection methods. Each food item's nutritive values, including proteins, carbohydrates, fats, fiber, and calories, are meticulously recorded to facilitate precise dietary recommendations. The dataset integrates cultural preferences and seasonal variations in food …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 59–83 Read article
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CHROMAWEAR: An AI Assisted Personalized Fashion Design Recommender System for Diverse Skin Tones to Enhance Fashion Choices
Abstract: In the age of fashion, we receive the same question every day: What should I wear today to look nice? The fashion industry is always changing, welcoming inclusivity and diversity. Still, despite the advancements, there are difficulties meeting people's varied needs, especially with regard to skin tone. This research work presents a personalized fashion design recommender system with artificial intelligence support to improve the fashion choices of people with different …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 49–58 Read article
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DR. REVIVE: An AI-Powered Medical Recommendation System for Optimised Resources and Improved Patient Care
Abstract: Dr. Revive is an AI-powered medical recommendation system designed to enhance virtual healthcare interactions by connecting patients, doctors, and healthcare stakeholders. Leveraging advanced machine learning algorithms, it analyses user-reported symptoms to provide initial medical recommendations, serving as a reliable first point of guidance. With access to a comprehensive medical database, the platform delivers accurate and timely advice, empowering patients while supporting healthcare professionals with data-driven decision-making. By offering a complete …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 14, Issue 3, 2024 · pp. 1–10 Read article
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Recipe-Fusion: Multimodal Food Recipe Recommendation System
Abstract: The food recipe recommendation system using data science is a software solution designed to help users discover new and delicious food options based on their food history and other relevant data. This system recommends various recipes based on the input given by the user and it helps to filter out the recipes on course type, diet type, and nature of the food (including non-veg, and veg) using a recommendation technique. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 82–91 Read article
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Enhancing User Engagement and Content Relevance: A Novel Approach to Social Media Post Recommendation System
Abstract: The social media post recommendation system is an innovative solution aimed at optimizing content delivery for users in today's digital age. Its primary motive is to tailor online experiences, ensuring users receive posts most relevant to their preferences. Various machine learning algorithms are employed to suggest related posts. This system leverages advanced algorithms and analytics, producing key results that highlight user engagement metrics and content relevance. Preliminary findings of this …
Published in International Journal of Algorithms Design and Analysis Review · Vol. 2, Issue 2, 2024 · pp. 1–7 Read article
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A Study of the Impact of AI-Powered Recommendation Systems on Consumer Purchase Decisions in the E-Commerce Industry
Abstract: Through personalized suggestions, the e-commerce industry has been affected so much that it has been overtaken by AI-powered recommendation systems. This paper examines the effects of AI-powered recommendations on online shoppers and how they influence product discovery, the engagement level of shoppers, and unplanned purchases. Emerging from the results of a survey of 55 graduates and MBA students, more than 70% of respondents claim that AI has helped them find …
Published in Current Trends in Information Technology · Vol. 16, Issue 1, 2025 · pp. 01–06 Read article
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An Analysis of Graph Database in Data Modelling and Analysis for a Recommendation System
Abstract: This research work focuses on graph databases, mainly Neo4j databases, in recommendation systems for e-commerce websites. The importance of research is that it explains how graph databases efficiently handle the complex relationship between user-items, which is difficult for traditional databases. Sparsity, limited diversity, and high setup costs are the challenges traditional databases face. This research work overcomes these problems using Ne04j with Cypher query language and graph algorithms (PageRank, Shortest …
Published in Journal of Advanced Database Management & Systems · Vol. 12, Issue 3, 2025 · pp. 33–39 Read article
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Elevating Seamless Housing Navigation with Precise Recommendations for Personalized Rental Experiences
Abstract: The demand for rental housing has increased significantly in recent years, making more effective and individualized methods of housing navigation necessary. Renters become frustrated and ineffective when using traditional ways of researching rental houses since they frequently involve manual searches and little customization. By using sophisticated recommendation systems to deliver exact recommendations catered to user preferences, this research article suggests a novel way to improve house navigation. The proposed approach …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 3, 2024 · pp. 50–62 Read article
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Real-time Facial Recognition with Convolutional Neural Networks for Personalized Music Therapy
Abstract: In this project, a web-based application has been developed that integrates computer vision-based facial recognition, multiple algorithms, and machine learning approaches. The given system obtains a user’s emotions in the real-time frame by analyzing facial expressions such as eyes, mouth, the forehead, and so on. It detects emotions like happiness, sadness, that is neutrality, or rock. For a given detected emotion, language, and a user’s chosen artist, the system recommends …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 11, Issue 2, 2024 · pp. 67–76 Read article
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AIducate: Your Smart Tutor–A Survey
Abstract: The ongoing “datafication” of our social reality has led directly to the emergence of new data-driven business models across various sectors, including education. As a result, the market for educational services is rapidly expanding. Educational technology (EdTech) companies are at the forefront, offering data-driven pedagogical solutions that are reshaping the landscape of learning. Despite the market's growth, few companies are harnessing the full potential of artificial intelligence (AI) and machine …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 2, 2024 · pp. 25–30 Read article
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A Review of Machine Learning Applications in Web Data Mining
Abstract: The rapid development of Internet technology has resulted in a rapidly changing and intricate digital environment that requires new methods for organizing and evaluating online data. This study examines the use of machine learning (ML) in web data mining, focusing on its ability to extract relevant insights from huge amounts of online data. Web data mining, which is divided into three categories: content mining, structure mining, and use mining, uses …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 1, 2025 · pp. 39–47 Read article
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Hyper Personalization Using AI: Elevate Fitness
Abstract: In the modern era, many individuals find it challenging to prioritize their health and well-being due to busy lifestyles filled with work, academic, and personal obligations. Conventional fitness and nutrition programs often apply uniform strategies that overlook individual differences in body type, preferences, and goals. This lack of real-time feedback and contextual customization often leads to poor user engagement and unsatisfactory results over time. Elevate is a comprehensive, AI-powered fitness …
Published in Journal of Mobile Computing, Communications & Mobile Networks · Vol. 12, Issue 3, 2025 · pp. 10–21 Read article
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E-Commerce Clothing Platform with Virtual Try-On
Abstract: The inability to physically evaluate garments remains a major limitation in online clothing commerce. Customers often depend on static product images and generalized sizing charts, which do not accurately represent individual body proportions. This frequently leads to uncertainty during purchase decisions and increased product return rates. To address this limitation, this research proposes a web-based clothing e-commerce platform integrated with an intelligent virtual try-on mechanism. The system allows users to …
Published in E-Commerce for Future & Trends · Vol. 13, Issue 1, 2026 · pp. 17–24 Read article
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Application of Resource Allocation Similarity Based Link Prediction in Wireless Networks
Abstract: Link prediction in wireless networks plays a crucial role in predicting missing connections within multiplex networks. This study focuses on the utilization of similarity-based link prediction methods in wireless networks. These methods assume that the likelihood of linkage between nodes is determined by their similarity, based on shared features. Several similarity measures, such as Common Neighbors (CN), Preferential Attachment (PA), Adamic-Adar (AA), and Resource Allocation (RA) indices, are commonly employed …
Published in International Journal of Wireless Security and Networks · Vol. 1, Issue 2, 2023 · pp. 37–42 Read article
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A Survey of Seasonal-based Movie Recommendations Using Machine Learning Through a Hybrid Approach with User Interest in Various OTT Platforms
Abstract: No matter their age, gender, race, color, or region, everyone enjoys watching films particularly during festival season. We are all, in the most basic sense, connected to one another through this beautiful medium, but what really grabs attention is the fact that, regardless of how unique our choices and combinations are in terms of picture show preference, one thing remains constant. Certain people have a preference for certain types of …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 1, 2024 · pp. 24–29 Read article
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Diet(Nutrition) Recommender using Machine Learning
Abstract: In an era where maintaining a healthy lifestyle has become a priority, personalized dietary recommendations play a crucial role in guiding individuals towards achieving their nutritional goals. The Diet Recommendation System is an inno- vative application that combines user-specific data with machine learning algorithms to provide tailored dietary suggestions. This system is designed to simplify the process of meal planning and promote healthier eating habits. The Diet Recommendation System is …
Published in International Journal of Nutritions · Vol. 2, Issue 2, 2025 Read article
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Visual Recognition with Convolutional Neural Networks for Object Detection
Abstract: Various research and development have taken place over the years on computer vision which is a branch of AI. AI disciplines like a vision system is applied in various fields like self-driving cars, face detection by social media apps and law enforcement software’s google lens and so on. The proposed system deals with design and implementation of an efficient way of training a GPU using python libraries to process and …
Published in Trends in Opto-electro & Optical Communication · Vol. 14, Issue 2, 2024 · pp. 07–13 Read article
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FoodieHUB: Food Recipe Suggestion Using AI-ML On Web
Abstract: Finding a delicious recipe to cook with limited ingredients at home can be a challenging task. Many individuals struggle to prepare meals using only the ingredients they have on hand, creating uncertainty and limiting options. This project aims to develop a recipe recommendation system that utilizes machine learning algorithms to suggest recipes based on available ingredients, dietary preferences, cuisine types, cooking time, and user ratings. The project utilizes a Gradient …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 01–07 Read article