What strategies can be used to recommend new items with few or no ratings?

Collaborative filtering. Collaborative filtering is a machine-learning technique for identifying relationships between data. It is frequently used in ... Implementation of Knowledge based Collaborative Filtering and Machine Learning for E-Commerce Recommendation System, Singh, Mahesh Kumar, Rishi, Om Prakash, ... Dec 29, 2022 ... The collaborative filtering (CF) mechanism was used in this work. Singhal et al. [3] focused on the role of deep learning in the e-Learning ... Feb 9, 2020 ... ... Machine Learning: Concepts and Techniques. The workshop covered ... Also, his work on deep collaborative filtering, anomaly detection ... Collaborative filtering; deep learning; generative adversarial networks; recommender systems. Issue Date: 2019-03. Publisher: IEEE-INST ELECTRICAL ELECTRONICS ... In this paper we introduce SVDFeature, a machine learning toolkit for feature-based collaborative filtering. SVDFeature is designed to efficiently solve the ... Feb 2, 2019 ... We develop a novel and effective approach, named CFRL, which seamlessly integrates the ideas of both collaborative filtering (CF) and reinforcement learning ( ... Mar 21, 2024 ... A collaborative filtering algorithm compares user's provided ratings for each book. By identifying similar users or items based on those ratings ... Feb 18, 2025 ... With collaborative filtering, recommender systems—often powered by machine learning, deep learning, and artificial intelligence—can use ... Nov 4, 2023 ... Collaborative filtering is a common method of personalized recommender system which filters information such as interactions data from other ...