Visualization of Explanations in Recommender Systems

By Mohammed Al-Taie, Seifedine Nimer Kadry. 2014

19 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Signal Processing

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Vision and Pattern Recognition

1. Yongfeng Zhang
2. Xu Chen
3. Juan A. Recio-García
4. Belén Díaz-Agudo
5. Christian Severin Sauer
6. Lara Quijano Sánchez
7. Xiangnan He

In Signal Processing

1. Juan A. Recio-García
2. Belén Díaz-Agudo
3. Yongfeng Zhang
4. Christian Severin Sauer
5. Lara Quijano Sánchez
6. Xu Chen

Citations in the corpus

• Explainable Recommendation: A Survey and New Perspectives (2018, background): “[2014a] generated (personalized) textual sentences as recommendation explanation to help users understand each recommendation result; McAuley and Leskovec [2013], Zhang [2015], Al-Taie and Kadry [2014] provided topical word cloud or clus-”
• Make it personal: A social explanation system applied to group recommendations (2017, result): “These are not surprising results as they go along with Al-Taie and Kadry (2014) and Tintarev (2007) findings that concluded that “users don’t have a clear preference for textual or graphical explanations”.”