What are the key challenges and opportunities for applying recommendation system techniques to novel domains and applications beyond traditional e-commerce and media platforms?

Jun 29, 2023 ... A recommender system uses artificial intelligence (AI), machine learning, and big data to suggest items a user might be interested in. May 1, 2024 ... Summer 2024: Reinforcement Learning in Recommendation Systems (Withdrawn). Affiliations: STEM EDUCATION Research Leadership. Project Leader ... Aug 9, 2023 ... We design a recommender system that suggests suitable crops for a specific land area for cultivation in the next season. Apr 22, 2025 ... Recommendation engines in this category rely on machine learning algorithms, such as clustering models, regression, user-based k-nearest ... May 18, 2023 ... A portfolio recommendation system that utilizes machine learning techniques to generate profitable {portfolios for users is proposed. The system ... The proposed livestreaming e-commerce recommendation system (LERS) enhances the exploration of new items by incorporating uncertainty into neural networks. machine learning recommender system jobs · Remote- Paid Search Strategist · $55,000 - $85,000 · Transportation Pricing and Data Analyst · From $70,000 · Machine ... Most of these existing systems are user-based ratings where content-based and collaborative-based learning methods are used. These systems' irrationality is ... Feb 13, 2023 ... The proposed collaborative filtering (CF) method categorizes active learners into one learner group. The proposed model has experimented on ... Sep 17, 2019 ... Recommender systems are a underlying technology. Platforms such as salesforce and cloudsense maintain customer history data and can use recommendation ...