Intelligent recommendation system. Feb 1, 2024 · Nikita Sawarkar, Dr M M Raghuwanshi, Dr.

Intelligent recommendation system. Deep learning solves complex relations so many researchers An intelligent recommendation sys-tem using ensemble learning is presented in this paper to reduce duplicate and irrelevant recommendations for the customer. Sep 13, 2025 · Learn how to build AI-powered recommendation systems to boost user engagement, personalize experiences, and drive conversions. These May 14, 2020 · Learn How to Build Intelligent Recommendation Systems The NVIDIA Deep Learning Institute offers instructor-led, hands-on training on the fundamental tools and techniques for building highly effective recommender systems. In social platforms, e-commerce, and online services, personalized recommendation has gradually become a basic function, and the era of intelligent recommendation has Aug 14, 2024 · This paper comprehensively explores the integration of cloud computing and advanced recommendation systems, emphasizing their pivotal roles in enhancing user experiences and operational 5 days ago · In addition, an smart recommendation system is designed based on a microservice architecture, integrating visual features, agricultural knowledge and user behavior data, and utilizing the improved DeepFM model for personalized recommendation. The sparse linear method (SLIM) is introduced in our framework to generate the top-N recommendations of courses A recommendation system (or recommender system) is a class of machine learning that uses data to help predict, narrow down, and find what people are looking for among an exponentially growing number of options. In particular, the Feb 1, 2024 · In view of the problems such as low recommendation accuracy, lack of personalization and long running time of the current personalized course recommendation system, this paper studied the personalized intelligent detection and recommendation algorithm system with the help of big data technology, hoping to solve the existing problems. In the design of a recommendation system, in order to fully protect users' privacy, this paper proposes a neural collaborative filtering recommendation model based on federated learning FedAvg algorithm, and verifies the recommendation performance of the Nov 3, 2023 · Download Citation | An intelligent recommendation system in e-commerce using ensemble learning | In today’s world, recommendation systems play a vital role in customer analysis on social media Feb 10, 2025 · The research objectives of this study are to develop an intelligent, data-driven recommendation system that leverages advanced technologies to enhance the alignment between consumer expectations and product recommendations, thereby improving consumer engagement and conversion rates. This paper mainly studies e-commerce intelligent recommendation Nov 29, 2023 · This research provides a design and implementation solution for an intelligent recommendation system for e-commerce platforms, offering references for improving the accuracy of product recommendations and user experience and optimizing the algorithms. This article delves into the development and optimization of intelligent recommendation system algorithms, aiming to address the challenges posed by diverse user demands and the expansion of data scale. Artificial intelligence (AI), particularly computational intelligence and machine learning methods and algorithms, has been naturally applied in the development of recommender systems to improve prediction accuracy and solve In recent years, intelligent recommendation systems using adaptive collaborative filtering have received great attention due to their ability to provide personalized and relevant recommendations. A recommender system (RecSys), or a recommendation system (sometimes replacing system with terms such as platform, engine, or algorithm) and sometimes only called "the algorithm" or "algorithm", [1] is a subclass of information filtering system that provides suggestions for items that are most pertinent to a particular user. The objective of this study is to provide an overview of the current state-of-the-art in the field and highlight the latest trends in the development of recommender systems. Jun 15, 2021 · In this study, we introduce an intelligent recommendation system that can gauge the optimal number and timing of testing for each student. Oct 27, 2025 · An intelligent content-based movie recommendation system built with Python, Streamlit, and The Movie Database (TMDB5000 movies dataset) API. Learn essential tips for creating an effective, AI-driven recommendation engine. With the rapid development of China's mobile Internet and the advent of 5g era, employees from all walks of life will basically use websites to buy all kinds of goods needed in life. Abstract This paper describes the general design and architecture of an intelligent recommendation system aimed mainly at supporting a user in her navigation through the massive amounts of information that she has to cope with in order to find the right information. The Building Intelligent Recommender Systems Deep learning-based recommender systems are the secret ingredient behind personalized online experiences and powerful decision support tools in retail, entertainment, healthcare, finance, and other industries. The Intelligent Recommendation System is a hybrid recommendation engine built using Django and Scikit-learn, designed to provide personalized content recommendations via a REST API. Sep 22, 2025 · A recommendation system is an intelligent algorithm designed to suggest items such as movies, products, music or services based on a user’s past behavior, preferences or similarities with other users. This project aims to fill this gap by developing a machine learning predictive model for an intelligent tourist recommendation system. Feb 22, 2023 · The explosive increase in educational data and information systems has led to new teaching practices, challenges, and learning processes. This Specialization covers all the fundamental techniques in recommender systems, from non-personalized and project-association recommenders through content-based and collaborative filtering techniques, as well as advanced topics like matrix factorization, hybrid machine learning methods for recommender systems, and Learn what an AI-based recommendation system is, how it works, the main types, and where you can use it to personalize experiences and grow your business. This Jan 1, 2018 · Being an essential component of smart education, we propose a novel recommendationsystem for course selection in the specialty of information management inChinese Universities. A recommendation engine, also called a recommender, is an artificial intelligence system that suggests items to a user. It is a simple method that enables to construct an intelligent system which explores the Markov chains to predict the following actions taking into consideration the most recent actions of the user. To effectively manage and analyze this information, it is crucial to adopt innovative methodologies and techniques. Sep 5, 2023 · This study proposes an intelligent recommendation system for personalized learning resources for college students, based on image processing. Deep learning is applicable in various systems like music recommendation, speech recognition, book suggestion, and video on demand. Intelligent recommendation is a very important task in the field of e-commerce. In this paper, the authors begin by explaining the general layout of an e-commerce system These variables contained the name of the system, type of recommendation system, artificial intelligence (AI) or intelligent techniques applied in recommendation system, system modules and type of system’s platform. Intelligent Recommendation System The proposed IRS (Lin et al. In this paper, we develop an AI application course for non-ICT major university students toward convergence with Jun 5, 2024 · In summary, the personalized intelligent book recommendation system for university library proposed in the study has the advantages of high coverage, low resource consumption, high accuracy and so on, which can provide readers with more accurate and personalized recommendation services. Personalized recommendation systems play a pivotal role in alleviating this burden by aiding users in filtering and selecting information tailored to their preferences and requirements. Recommender systems (RSs) offer a solution for advising students and guiding their learning journeys by utilizing statistical methods such as Nov 28, 2023 · Various services and applications based on information and communications technology (ICT) are converging with cultural aspects of historical implementations. The experimental results indicate that there has been a significant improvement in the precision and recall of the recommendation system in com-parison with the other conventional techniques. The rapid growth of e-commerce platforms has resulted in an overwhelming abundance of product information, leading to choice paralysis and Feb 22, 2024 · A recommendation system is an artificial intelligence technology that advises users on things or projects that they may be interested in. They are common in today's digital scene, serving an important role in online shopping, streaming services, social networking, and other platforms where With the continuous increase and rapid iteration of the number of academic achievements published, it is difficult for researchers to find academic materials and literature related to their research fields. Introduction Recent research in Artificial Intelligence (AI) and recommendation systems have focused on developing highly intelligent and interactive algorithms, utilizing information's acquired from healthcare sensor networks. The utilization of recommender systems cannot be overstated, given its potential influence to ameliorate many over-choice challenges. First of all, paper studies the application of collaborative filtering and content-based recommendation Mar 28, 2024 · With the rapid evolution of the Internet and the exponential proliferation of information, users encounter information overload and the conundrum of choice. We encourage authors across the world to submit their original and unpublished works. Jun 13, 2023 · Intelligent Recommendation System The proposed IRS (Lin et al. Learn key steps, tools, and best practices to build intelligent recommendations. K. 4 days ago · Nevertheless, current research often fails to address the need for comprehensive manuals on activities and attractions while traveling. While originally developed for a book recommendation system, these metrics are versatile and can be adapted for various recommendation applications across different domains. Jun 12, 2022 · The personalized recommendation system of university library mainly focuses on readers, applies personalized recommendation technology, and actively recommends books that meet the needs of readers to readers according to the differences of readers’ own information needs. Instead of providing static information when users search and possibly buy products, recommendation systems increase the degree of interactivity to expand the possibilities Nov 1, 2021 · Intelligent recommendation system provides information associated with the selection of alternative cause of action allowing consumers to be directed to services that are customized for them in a large space of potential alternatives (Aguilar et al. com The Intelligent Career Recommendation System helps users discover ideal career paths based on their skills, interests, and experience level. Alternative recommender system techniques are needed to retrieve quickly high quality recommendations even from a huge amount of Jan 14, 2025 · This paper presents a machine learning-based healthcare recommendation system designed to provide personalized medical advice by accurately predicting diseases from patient symptoms. How to use this information to give customer recommendations, improve the accuracy of recommendations and protect information security is a topic worth studying. Serving users with relevant … Intelligent recommendation system is a service that is widely studied in the field of data science, implemented through machine learning technology. Microsoft recommends using a system-assigned managed identity for this quick-start guide. Standard and Premium requests are measured separately (see appendix for details on Standard and Premium features). 75% in disease prediction. Firstly, the importance of personalized learning path recommendation and the challenges SAP Intelligent Product Recommendation leverages historical data and machine learning to streamline and simplify the quotation process and customer experience for configurable products. Recommendation system is the main method to deal with and alleviate network information overload at present, and it has been widely studied and applied in academia. . In particular, the Under the current background of intelligent education, personalized learning path recommendation has become an important means to improve learning efficiency and effect. The study starts with a comprehensive summary of the main taxonomy of recommender systems, including Jun 12, 2024 · Create Intelligent Recommendation Systems with Amazon Personalize Recommendation engines are becoming a crucial part of many digital applications and platforms. Deep learning algorithm has become the most popular research direction in the past decade due to its powerful expression ability, whether it is the ability to fit data patterns or the ability to mine data feature combinations. At the same time, developing a convergence course for non-ICT majors is becoming increasingly popular in universities. Jun 22, 2023 · In this technical survey, we comprehensively summarize the latest advancements in the field of recommender systems. To address the challenges posed by the overwhelming abundance of online recipes, this system provides personalized recipe suggestions based Dec 1, 2024 · The combination of recommender systems and AI in e-commerce has led to a lot of research. Jan 1, 2019 · When the number of books provided by library is relatively large, it becomes difficult for user to select appropriate book from a lot of candidate books. We discuss how to build an intelligent recommendation system using a reinforcement learning approach. They are used by businesses to increase customer engagement, provide a more personalised experience, and improve customer retention. The system integrates content-based and collaborative filtering recommendation algorithms to enhance recommendation accuracy and personalization. Intelligent product recommendation systems are tools that are used to predict the users' choices from a list of suggested items. Jun 5, 2023 · Intelligent recommendation system can greatly save users' time and energy by asking for relevant information and providing powerful guidance and help to users. Feb 28, 2021 · System Design Combined with J2EE technology, the structure of e-commerce intelligent recommendation system can be divided into three parts: presentation layer, business logic layer, and data layer. This paper discusses how to use deep learning technology to build efficient and accurate personalized learning path recommendation system. In recommendation system innovation, deep learning is an enormous thing. It combines Collaborative Filtering and Content-Based Filtering to generate accurate suggestions for users based on their interactions and preferences. Apr 21, 2023 · The intelligent recommendation model of tourist places requires the algorithm to be able to accurately recommend tourist attractions according to the user’s interests. It examines 60 articles from prominent databases and identifies the different methods used in recommendation systems, such as collaborative and content-based approaches with a recent shift towards machine learning. This system simplifies attraction discovery, unveiling hidden value within tourism data at the intersection of AI and IoT. Hybrid approaches to recommendation for instance, pattern-based hybrid models based on semantic relations- seem to hold quite well in enhancing * 1Email: bhagyaasri34@gmail. The innovation of this study lies in proposing an adaptive collaborative intelligent recommendation model (ACIR), which combines adaptive collaborative filtering with context, user behavior, and movie Mar 7, 2024 · Abstract A particularity of intelligent recommender systems in the domain of medicine is the need to take into account a diversity of numerous features, and the limitation is conditioned by the need to control recommendations made by a physician. This goes beyond simple rule-based systems, offering a more nuanced and personalized approach to recommendations. Oct 7, 2024 · You can grant access to the Intelligent Recommendations service by using a system-assigned managed identity and\or a user-assigned managed identity. Recommender Systems (RSs) leverage Artificial Intelligence (AI) to provide users with personalized suggestions aligned with their preferences and interests. Aug 20, 2020 · An intelligent recommendation system analyzes the available information to produce a detailed, individualized picture of each customer and make predictions about their preferences and behavior, specifically their buying propensity. 5 days ago · This study aims to improve the accuracy of agricultural landscape recognition through deep learning models and to construct an intelligent recommendation system by combining multimodal characteristics to provide intelligent support for agricultural production decision-making. Deep learning algorithm has Nov 15, 2014 · Recommender systems are currently being applied in many different domains. In this case, this paper designs a personalized recommendation system for college libraries based on hybrid recommendation algorithm. According to the output values of the model the recommendation system may provide more suitable learning strategies and learning materials to students. The system first implements semantic annotation of images that integrates contextual information through the granular computing concept and a second-order Conditional Random Field (CRF) model, improving Nov 30, 2023 · Finally, based on the mining results, an “employment stickiness” model is constructed, and a design for an intelligent job recommendation system for graduates is developed using data analysis Apr 3, 2025 · You're charged for the real-time recommendation requests (transactions) processed per region by the Intelligent Recommendations service for each Service Endpoint, for each hour, counting the transactions in units of TPS-Hour, and using the tiered pricing table. Also, we use certain user demographic attributes such as the gender and age to create segmented user profiles With the rise of smartphones, online shopping has grown quickly. As we all know, big data has become a key direction in the work of various Internet companies and the recommendation system can be said to be one of the best landing applications of big data. Types of Recommendation Systems The recommendation systems for books take into account complex algorithms which are used to make the recommendations quite accurate according to choices made by individuals. Multiple artificial intelligent techniques have been intro-duced and applied to recommender systems to meet the increased recommendation demands of the big data informa-tion explosion. This repository offers a collection of seven robust similarity metrics designed for intelligent recommendation engines. Thanks to the prowess of the powerful and intelligent recommendation systems enabling e-commerce websites to cater to online customers with the most narrow-down and personalized recommendations. The article first reviews the development history of recommendation systems, from content-based and behavior based recommendation methods, to hybrid recommendation systems, and then to the May 2, 2025 · Discover how to develop an AI recommendation system with this complete guide. Aug 28, 2024 · With the rise of social media, individuals face challenges in decision-making due to the abundance of options available. There are different types of recommendations, including virtual assistants and online suggestions made in real time. Apr 3, 2024 · The rapid development of artificial intelligence has made the application of recommendation system in various fields increasingly extensive, providing users with a more personalized experience. Researchers have proposed the use of association rules, collaborative filtering, Markov chain, recurrent neural network and other technologies for shopping basket recommendation. Big data and artificial intelligence have generated widespread intersection and integration in various fields. Jun 11, 2024 · The Power of AI-Powered Recommendations AI-powered recommendation systems leverage sophisticated algorithms and machine learning techniques to understand user preferences, predict future behavior, and recommend relevant content or products. Using content-based filtering and natural language processing, the system analyzes user input and matches it with the most suitable careers from a comprehensive database. recommendations deep-learning pytorch collaborative-filtering knowledge-graph recommender recommendation-system recommender-systems ctr-prediction graph-neural-networks sequential-recommendation Updated on Feb 23 Python Aug 1, 2023 · This Special Issue on “New Trends in Algorithms for Intelligent Recommendation Systems” provides a platform to exchange new ideas by researchers and practitioners in the field of recommender systems and their applications in many areas. A complete guide for businesses! Feb 1, 2021 · Recommendation systems aim to predict users interests and recommend items most likely to interest them. Feb 26, 2024 · This review delves into using e-learning technology and personalized recommendation systems in education. Label classification is crucial in intelligent recommendation, but May 13, 2023 · The creation and use of big data have driven the intelligent development of e-commerce. The experimental results indicate that there has been a significant improvement in the precision and recall of the recommendation system in comparison with the other conventional techniques. Most of these existing systems are user-based ratings where content-based and collaborative-based learning methods are used. Researchers have proposed applying several methodologies such as rules of association, collaborative filtering, Markov chains, and recurrent neural network techniques to offer optimal products to customers during their shopping experience. Nov 3, 2023 · An intelligent recommendation system using ensemble learning is presented in this paper to reduce duplicate and irrelevant recommendations for the customer. A referral system is a subset of an information filtering system that seeks to predict user preferences for an item based on relevant personal knowledge filtering (Abdi, Okeyo, and Mwangi 2018). Nov 1, 2020 · Recommender systems provide personalized service support to users by learning their previous behaviors and predicting their current preferences for particular products. Nov 29, 2023 · Through this research, we provide a design and implementation solution for an intelligent recommendation system for e-commerce platforms, offering references for improving the accuracy of product Feb 16, 2022 · Keywords: education scientific research data, content-based recommendation, intelligent recommendation system, collaborative filtering, sustainable development Citation: Wang R, Zhang S, Qi L and Huang J (2022) Exploration on Scientific Research Data-Targeted Intelligent Recommendation System Using Machine Learning Under the Background of Feb 9, 2023 · Business applications of recommender systems Intelligent Recommendations enables businesses to automate relevant recommendations, including personalized results for new and returning users, and the ability to interpret both user interactions and item or user metadata. Specifically, the study aims to: Feb 9, 2022 · Wondering if Google's Recommendations AI is right for your organization? Get the steps to implement it and what is needed to get started. In particular, the proposed recommendation system is based on the Sep 19, 2022 · With the continuous increase and rapid iteration of the number of academic achievements published, it is difficult for researchers to find academic materials and literature related to their research fields. The paper provides a detailed and up-to-date survey of the field, considering the different kinds of A Recommender System is a process that seeks to predict user preferences. For improving the accuracy of recommendations Nov 1, 2020 · Abstract and Figures Recommender systems provide personalized service support to users by learning their previous behaviors and predicting their current preferences for particular products Feb 27, 2025 · This intelligent recommendation system achieves fusion based on multimodal information by establishing a user profile model and using matching algorithms for personalized recommendations, achieving significantly better recommendation results than traditional methods. There are many types of recommendation systems with different methodologies and concepts. The personalized and curated recommendations are based on user analysis, past purchase history, and browsing behavior. Jan 1, 2016 · In this study we present an intelligent recommendation system for university students. It suggests similar movies based on a selected title using text similarity between movie genres, keywords, cast, and crew. Together with the conventional functional components the suggested system includes the predictive model, estimating student's academic performance. The intelligent recommender system exploits knowledge, learns, discovers new information, infers preferences and criticisms, among other things. [2][3][4] Recommender systems are particularly useful when an With the popularity of smart phones, e-commerce has developed rapidly. However, the current personalized recommendation system faces challenges Jun 27, 2025 · Learn how to build a recommendation system by using Azure Database for PostgreSQL and Azure OpenAI. Feb 1, 2024 · Nikita Sawarkar, Dr M M Raghuwanshi, Dr. These systems help users discover relevant content in vast environments making them crucial for industries like e-commerce, streaming and food delivery. Intelligent recommendations can be based on data from customer surveys, browsing behaviours, and purchase World Scientific Publishing Co Pte Ltd Jul 23, 2025 · Understanding Recommendation Systems Recommendation systems, often known as recommender systems, are a type of information filtering system that attempts to forecast the "rating" or "preference" that a user would assign to an item. In Personal recommendation systems have been emerged to conduct effective search which mine related books based on user rating and interest. A comprehensive and thorough search of the smart e-Tourism recommenders reported in the Artificial Intelligence journals and conferences since 2008 has been made. Jan 3, 2020 · Recommendation systems have changed the way inanimate websites interact with their users. The information generated in e-commerce provides a good means to analyze the behavior of users. They analyze information to provide personalized recommendations. Deep neural system has been succeeded in solving recent complex problems in AI, image processing, and natural language processing. Abstract Intelligent recommendation system can greatly save users' time and energy by asking for relevant information and providing powerful guidance and help to users. In this paper, we propose a new intelligent recommender system that combines collaborative filtering (CF) with the popular unsupervised machine learning algorithm K-means clustering. With the development of information and network technology, the scale of data on the Internet is unprecedented. Apr 3, 2025 · Learn about Intelligent Recommendations in Microsoft for Retail, which uses AI and machine learning to provide a recommendations system. This paper focuses on their application in tourism. The system utilizes a comprehensive symptom–disease dataset, leveraging support vector classifier (SVC) and random forest (RF) models, achieving outstanding accuracies of 97. Recommend the best products, default configuration options, price estimate, and more based on customer needs. Such systems not only enhance user experience and Oct 20, 2023 · The paper discusses an AI and IoT-based Intelligent Tourism Recommendation System (ITRS) that offers travelers predefined itineraries, personalized suggestions, and tourism insights. Apr 3, 2025 · Front-end serving experience that showcases recommendations results to the client side via secure HTTPS endpoints All relevant data for Intelligent Recommendations machine learning, such as item catalog, availabilities, and other metadata and interactions (transactions), are structured in the Data Lake Storage file system and shared securely. This article proposes a design scheme for an intelligent recommendation system based on collaborative filtering, providing users with personalized and accurate recommendations. R. Each investor receives investment recommendations for his particular risk appetite, including a collectively recommended distribution of investments over various asset classes. The benefits it The Intelligent Recommendations System aggregates these individual opinions and creates collective model stock portfolios in five risk classes. Singh, "A Review on Intelligent Recommendation System for Higher Education," International Journal of Scientific Research and Review, Volume 7, Issue ABSTRACT The rapid advancements in healthcare technologies and the increasing availability of patient data have paved the way for the development of intelligent medication recommendation systems Intelligent recommendations use predictive analytics to recommend items and services to customers based on their past behaviours, preferences, and interests. , 2017). We designed an intelligent short video recommendation system using deep learning technologies. Nov 20, 2023 · Discover how to build a recommendation system with our step-by-step guide. These systems use AI to make e-commerce better for users and help them make decisions (Reyes, 2023). This study presents a systematic review of AI-based Recommender Systems, focusing on recent advancements and primary Jan 1, 2020 · Thereby, we have created our own solution, a Recommendation System based on Markov Chains and Grouping of Genres (RSMCG). Jul 1, 2017 · Abstract In this paper, we propose a general framework for an intelligent recommender system that extends the concept of a knowledge-based recommender system. 2018) is based on the application logic of recommendation systems. Jul 31, 2024 · This paper presents the development of an advanced recipe recommendation system powered by natural language processing (NLP). Feb 15, 2012 · This system uses a Bayesian network to predict the probability of individual travelers’ preference of attractions and utilizes geographic data from Google Maps to develop an intelligent and personalized tourist attraction recommendation system. Big data and artificial intelligence technologies have driven the development of intelligent recommendation systems. Recommendations are not directly transferred to the user because it is necessary to ensure the safety of the patient in their fulfillment. To implement this system, we firstly collect the course enrollment data-set for specific group of students. ys gszu 9w iirytd ro raw ms4 ktf oaf ut7fz5

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