Alleviating item-side cold-start problems in recommender systems using weak supervision

Keyphrases

• Recommender Systems 100%
• Unsupervised Learning 100%
• Cold-start Problem 100%
• Collaborative Filtering 50%
• Mean Absolute Error 33%
• User Side 33%
• New Item 33%
• Accuracy Improvement 16%
• User Access 16%
• Content-based Filtering 16%
• Feature-based 16%
• Lack of Information 16%
• Representative Users 16%
• Identifying Feature 16%
• Neural Collaborative Filtering 16%
• Sparsity Problem 16%
• Representative Reviewers 16%
• Average Rating 16%
• New User 16%

Computer Science

• Recommender Systems 100%
• Cold Start Problem 100%
• Collaborative Filtering 60%
• Mean Absolute Error 40%
• Sparsity 20%
• Representative User 20%
• content-based filtering 20%

Engineering

• Cold Start 100%
• Filtration 66%
• Mean Absolute Error 33%
• Sparsity 16%
• Reviewer 16%
• Core Function 16%