Improving recommendation by deep latent factor-based explanation

DC FieldValueLanguage
dc.contributor.authorOuyang, Sixun-
dc.contributor.authorLawlor, Aonghus-
dc.descriptionThe Thirty-Fourth AAAI Conference on Artificial Intelligence: Interactive and Conversational Recommendation Systems (WICRS) Workshop, New York, United States of America, 7-12 February 2020en_US
dc.description.abstractThe latent factor methods and explanation algorithms constitute the foundation of many advanced explainable recommender systems. However, interpreting the high-dimensional latent factors has not been sufficiently addressed and continuously becomes a challenging work. Besides, only a few works have researched the use of explanation to improve recommendations. In this paper, we propose a deep learning method that generates high-quality latent factor-based explanations and efficiently ameliorating recommendations. We conduct top- K items ranking experiment on two real-world datasets and show that our method outperforms nine currently state-of-theart recommender systems in five ranking metrics. Moreover, we conduct a qualitative and quantitative analysis of users’ latent factors and reveal that we continually offer the best latent representations.en_US
dc.description.sponsorshipScience Foundation Irelanden_US
dc.subjectRecommender Systemsen_US
dc.subjectLatent representationen_US
dc.titleImproving recommendation by deep latent factor-based explanationen_US
dc.typeConference Publicationen_US
dc.statusPeer revieweden_US
dc.description.othersponsorshipInsight Research Centreen_US
item.fulltextWith Fulltext-
Appears in Collections:Insight Research Collection
Files in This Item:
File Description SizeFormat 
insight_publication.pdf438.04 kBAdobe PDFDownload
Show simple item record

Page view(s)

Last Week
Last month
checked on Jan 18, 2021


checked on Jan 18, 2021

Google ScholarTM


If you are a publisher or author and have copyright concerns for any item, please email and the item will be withdrawn immediately. The author or person responsible for depositing the article will be contacted within one business day.