Potential factors-embedding group recommendation for online education
Q Yang, Y Wang, Z Wu, J Zhang, L Liu, J Zhang - Discover Computing, 2024 - Springer
Online education platform urgently needs recommendation methods to service learning
groups. The existing group recommendation methods rely on member preference …
groups. The existing group recommendation methods rely on member preference …
Hybrid regret minimization: a submodular approach
Regret minimization queries are important methods to extract representative tuples from
databases. They have been extensively investigated in the last decade due to wide …
databases. They have been extensively investigated in the last decade due to wide …
Towards strong regret minimization sets: Balancing freshness and diversity in data selection
Multi-criteria decision-making typically requires selecting a concise, representative set from
large databases. Regret minimization set (RMS) queries have emerged as a solution to …
large databases. Regret minimization set (RMS) queries have emerged as a solution to …
Fair Top-k Query on Alpha-Fairness
The traditional top-k query was proposed to obtain a small subset from the database
according to the user preference, which is explicitly expressed as a ranking scheme (ie …
according to the user preference, which is explicitly expressed as a ranking scheme (ie …
Identifying Rank-Happiness Maximizing Sets Under Group Fairness Constraints
K Zhu, J Zheng, Z Yang, J Dong - Asia-Pacific Web (APWeb) and Web …, 2024 - Springer
The happiness or regret based query has been another important tool in multi-dimensional
decision-making besides the top-k and skyline queries. To avoid the happiness ratio being …
decision-making besides the top-k and skyline queries. To avoid the happiness ratio being …