Results 41 to 50 of about 26,996,454 (309)
Community-Based User Domain Model Collaborative Recommendation Algorithm
Tsinghua Science and Technology, 2013 Collaborative Filtering (CF) is a commonly used technique in recommendation systems. It can promote items of interest to a target user from a large selection of available items.
Fulan Qian +3 more
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Image Recommendation System Based on Environmental and Human Face Information
Sensors, 2023 With the advancement of computer hardware and communication technologies, deep learning technology has made significant progress, enabling the development of systems that can accurately estimate human emotions. Factors such as facial expressions, gender,
Hye-min Won, Yong Seok Heo, Nojun Kwak
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Multi Clustering Recommendation System for Fashion Retail
Multimedia tools and applications, 2022 Fashion retail has a large and ever-increasing popularity and relevance, allowing customers to buy anytime finding the best offers and providing satisfactory experiences in the shops.
P. Bellini +3 more
semanticscholar +1 more source
Deep learning based semantic personalized recommendation system
Int. J. Inf. Manag. Data Insights, 2021 The past decade has seen significant development in the number of personalized recommendation applications on the World Wide Web. It aims to assist users to retrieve relevant items from a large repository of contents by providing items or services of ...
Sunny Sharma, V. Rana, Vivek Kumar
semanticscholar +1 more source
Recommending Sources in News Recommender Systems
Proceedings of the 11th International Conference on Web Information Systems and Technologies, 2015 Recommender systems aim to deliver the most suitable item to the user without the manual effort of the user. It is possible to see the applications of recommender systems in a lot of different domains like music, movies, shopping and news. Recommender system development have many challenges.
Özlem Özgöbek +2 more
openaire +2 more sources
Quantum Recommendation Systems
CoRR, 2016 A recommendation system uses the past purchases or ratings of n products by a group of m users, in order to provide personalized recommendations to individual users. The information is modeled as an m \times n preference matrix which is assumed to have a good rank-k approximation, for a small constant k. In this work, we present a quantum algorithm for
Kerenidis, Iordanis, Prakash, Anupam
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An Adaptive Genetic Algorithm for Personalized Itinerary Planning
IEEE Access, 2020 Traveling as a very popular leisure activity enjoyed by many people all over the world. Typically, tourists have different kinds of preferences about their itineraries, limited time budgets, unfamiliar with the wide range of Points-of-Interest (POIs) in ...
Phatpicha Yochum +3 more
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Intelligent Recommendation System Based on Mathematical Modeling in Personalized Data Mining
Mathematical Problems in Engineering, 2021 With the advent of the era of big data, data mining has become one of the key technologies in the field of research and business. In order to improve the efficiency of data mining, this paper studies data mining based on the intelligent recommendation ...
Yimin Cui
semanticscholar +1 more source
Trustworthy Recommender Systems
CoRR, 2022 Recommender systems (RSs) aim to help users to effectively retrieve items of their interests from a large catalogue. For a quite long period of time, researchers and practitioners have been focusing on developing accurate RSs. Recent years have witnessed an increasing number of threats to RSs, coming from attacks, system and user generated noise ...
Shoujin Wang +4 more
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Recommendation System for Thesis Topics Using Content-based Filtering
IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2021 When pursuing their bachelor degree, every students are required to pursue a thesis in order to graduate from the major that they take. However, during the process, students got several difficulty regarding chosing their thesis topics.
Hans Satria Kusuma, Aina Musdholifah
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