On recommendation problems beyond points of interest
作者：
Highlights：
• We model query relaxation and adjust recommendation in the context of recommendation systems.
• We study two decision problems to decide whether query relaxations or adjustments to the data can be made to obtain recommendations.
• We examine the impact of various parameters on the complexity of these decision problems.
• Matching upper and lower bounds are established for the general case and a variety of special cases, both for data and combined complexity.
摘要
Highlights•We model query relaxation and adjust recommendation in the context of recommendation systems.•We study two decision problems to decide whether query relaxations or adjustments to the data can be made to obtain recommendations.•We examine the impact of various parameters on the complexity of these decision problems.•Matching upper and lower bounds are established for the general case and a variety of special cases, both for data and combined complexity.
论文关键词：Recommendation problems,Query relaxation,Adjustment,Complexity
论文评审过程：Received 27 February 2013, Revised 27 August 2014, Accepted 31 August 2014, Available online 16 September 2014.
论文官网地址：https://doi.org/10.1016/j.is.2014.08.002
