Results 1 to 10 of about 7,593,003 (291)
Mitigating Cold Start Problem in Serverless Computing with Function Fusion [PDF]
Sensors, 2021 As Artificial Intelligence (AI) is becoming ubiquitous in many applications, serverless computing is also emerging as a building block for developing cloud-based AI services.
Seungjun Lee +3 more
doaj +7 more sources
User Cold Start Problem in Recommendation Systems: A Systematic Review
IEEE Access, 2023 The recommendation system makes recommendations based on the preferences of the users. These user preferences usually come from the user’s basic information, item rating, historical data, and so on.
Hongli Yuan, Alexander A. Hernandez
doaj +3 more sources
Alleviating Item-Side Cold-Start Problems in Recommender Systems Using Weak Supervision
IEEE Access, 2020 Recently, recommender systems have been used in various fields. However, they are still plagued by many issues, including cold-start and sparsity problems.
Sang-Min Choi +4 more
doaj +3 more sources
Active learning algorithm for alleviating the user cold start problem of recommender systems [PDF]
Scientific ReportsA key challenge in recommender systems is how to profile new users. A popular solution for this problem is to use active learning strategies. These strategies request ratings for a small set of carefully selected items to reveal the preferences of new ...
Toon De Pessemier +2 more
doaj +2 more sources
Frontiers in Computer ScienceThis article introduces a recommendation system that merges a knowledge-based (attribute-based) approach with collaborative filtering, specifically addressing the challenges of the pure-cold start scenario in personalized e-learning. The system generates
Hala Butmeh, Abdallatif Abu-Issa
doaj +3 more sources
Cross-domain Recommendation Based on Review Aspect-level User Preference Transfer [PDF]
Jisuanji kexue, 2022 In order to solve the user cold-start problem caused by data-sparse in recommender system,this paper proposes a cross-domain recommendation algorithm based on aspect-level user preference transfer,named CAUT.CAUT is devised to learn aspect transfer ...
ZHANG Jia, DONG Shou-bin
doaj +1 more source
Real Estate Recommendation Approach for Solving the Item Cold-Start Problem
IEEE Access, 2021 The item cold-start problem occurs when a recommendation system cannot recommend new items owing to record deficiencies and new listing omissions. When searching for real estate, users can register a concurrent interest in recent and prior projects. Thus,
Jirut Polohakul +3 more
doaj +1 more source
Information, 2022 Recommender systems are tools that help users in the decision-making process of choosing items that may be relevant for them among a vast amount of other items.
Julio Herce-Zelaya +4 more
doaj +1 more source
Algorithms, 2022 A domain that has gained popularity in the past few years is personalized advertisement. Researchers and developers collect user contextual attributes (e.g., location, time, history, etc.) and apply state-of-the-art algorithms to present relevant ads.
Iosif Viktoratos, Athanasios Tsadiras
doaj +1 more source
IEEE Access, 2022 The cold-start problem is one of the main challenges in recommender systems and specifically in collaborative filtering methods. Such methods, albeit effective, typically can not handle new items or users that do not have any prior interaction activity ...
Alireza Gharahighehi +2 more
doaj +1 more source