Synopsis
Research Paper (postgraduate) from the year 2018 in the subject Computer Science - Applied, grade: A, National University of Modern Languages, Islamabad (Institute of Management Sciences), course: IT, language: English, abstract: Bearing in mind the increasing need for access to personalized news, the current research study aims at developing an online news recommendation system that could offer an optimum online news reading experience in a highly personalized fashion. The study considers major methodologies and perspectives, such as reinforced learning, Q-Learning, Collaborative Filtering and User Profiling, within this domain in order to implement the ONRS system. Online news reading has gained more attention in recent years than ever, particularly based on the increasing dependence of users on smartphones and the internet. Leading a busy lifestyle, end-users find it hard to search for relevant news articles online, and require tools that could provide them with the most needed news feed on the go. Although legacy news recommendation systems do exist, yet they do not offer optimum efficiency and accuracy.
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Online News Recommendation Systems in Machine Learning
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Online News Recommendation Systems in Machine Learning
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Research Paper (postgraduate) from the year 2018 in the subject Computer Science - Applied, grade: A, National University of Modern Languages, Islamabad (Institute of Management Sciences), course: IT, language: English, abstract: Bearing in mind the increasing need for access to personalized news, the current research study aims at developing an online news recommendation system that could offer an optimum online news reading experience in a highly personalized fashion. The study considers major methodologies and perspectives, such as reinforced learning, Q-Learning, Collaborative Filtering and User Profiling, within this domain in order to implement the ONRS system. Online news reading has gained more attention in recent years than ever, particularly based on the increasing dependence of users on smartphones and the internet. Leading a busy lifestyle, end-users find it hard to search for relevant news articles online, and require tools that could provide them with the most needed news feed on the go. Although legacy news recommendation systems do exist, yet they do not offer optimum efficiency and accuracy. 36 pp. Englisch. N° de réf. du vendeur 9783346820839
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Online News Recommendation Systems in Machine Learning
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GRIN Verlag, GRIN Verlag Feb 2023, 2023
ISBN 10 : 3346820831
ISBN 13 : 9783346820839
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Research Paper (postgraduate) from the year 2018 in the subject Computer Science - Applied, grade: A, National University of Modern Languages, Islamabad (Institute of Management Sciences), course: IT, language: English, abstract: Bearing in mind the increasing need for access to personalized news, the current research study aims at developing an online news recommendation system that could offer an optimum online news reading experience in a highly personalized fashion. The study considers major methodologies and perspectives, such as reinforced learning, Q-Learning, Collaborative Filtering and User Profiling, within this domain in order to implement the ONRS system. Online news reading has gained more attention in recent years than ever, particularly based on the increasing dependence of users on smartphones and the internet. Leading a busy lifestyle, end-users find it hard to search for relevant news articles online, and require tools that could provide them with the most needed news feed on the go. Although legacy news recommendation systems do exist, yet they do not offer optimum efficiency and accuracy.Books on Demand GmbH, Überseering 33, 22297 Hamburg 36 pp. Englisch. N° de réf. du vendeur 9783346820839
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Online News Recommendation Systems in Machine Learning
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Taschenbuch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - Research Paper (postgraduate) from the year 2018 in the subject Computer Science - Applied, grade: A, National University of Modern Languages, Islamabad (Institute of Management Sciences), course: IT, language: English, abstract: Bearing in mind the increasing need for access to personalized news, the current research study aims at developing an online news recommendation system that could offer an optimum online news reading experience in a highly personalized fashion. The study considers major methodologies and perspectives, such as reinforced learning, Q-Learning, Collaborative Filtering and User Profiling, within this domain in order to implement the ONRS system. Online news reading has gained more attention in recent years than ever, particularly based on the increasing dependence of users on smartphones and the internet. Leading a busy lifestyle, end-users find it hard to search for relevant news articles online, and require tools that could provide them with the most needed news feed on the go. Although legacy news recommendation systems do exist, yet they do not offer optimum efficiency and accuracy. N° de réf. du vendeur 9783346820839
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Online News Recommendation Systems in Machine Learning
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Taschenbuch. Etat : Neu. Online News Recommendation Systems in Machine Learning | Anonymous | Taschenbuch | Englisch | 2023 | GRIN Verlag | EAN 9783346820839 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. N° de réf. du vendeur 126666231
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