Combining different metadata views for better recommendation accuracy
作者：
Highlights：
• Two items representations based on BabelNet concepts extracted from users’ reviews.
• Combination of two item views of features: one statistical and one based on quality.
• Three combination categories: pre, neighborhood and post combination.
• Post combination provides the best results with approach based on machine learning.
• Neighborhood combination has promising results especially with larger neighborhoods.
摘要
•Two items representations based on BabelNet concepts extracted from users’ reviews.•Combination of two item views of features: one statistical and one based on quality.•Three combination categories: pre, neighborhood and post combination.•Post combination provides the best results with approach based on machine learning.•Neighborhood combination has promising results especially with larger neighborhoods.
论文关键词：Recommender systems,Item representation,Unstructured metadata
论文评审过程：Received 24 January 2018, Accepted 18 January 2019, Available online 6 February 2019, Version of Record 13 February 2019.
论文官网地址：https://doi.org/10.1016/j.is.2019.01.008
