Recommendation to Groups
By Anthony David Jameson, Barry Smyth. The Adaptive Web, 2007
440 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Information Systems, Signal Processing
View Paper: https://www.semanticscholar.org/paper/7fe73dd079d14520224af718c12ab3e224d40cbb
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
- Fernando Ortega
- Antonio Hernando
- Juan A. Recio-García
- Belén Díaz-Agudo
- Jesús Bobadilla
- Jie Lu
- Yue Shi
- Abraham Gutiérrez
In Information Systems
- Yue Shi
- Charu C. Aggarwal
- Martha A. Larson
- Alan Hanjalic
- Linas Baltrunas
- Fernando Ortega
- Antonio Hernando
- Jie Lu
In Signal Processing
- Yue Shi
- Martha A. Larson
- Alan Hanjalic
- Juan A. Recio-García
- Belén Díaz-Agudo
- Jesús Bobadilla
- Jie Lu
- Fernando Ortega
Citations in the corpus
- Group Recommender Systems: Combining Individual Models (2011, background): “An overview of how users’ decisions can be aided is provided in [8].”
- Recommender system application developments: A survey (2015, background): “Group recommender systems (GRS) are proposed to produce a group of user suggestions when group members are unable to gather for face-to-face negotiation, or their preferences are not clear in spite of meeting each other [66, 67].”
- Group recommendations with rank aggregation and collaborative filtering (2010, methodology): “In such case, we would compute nDCG on the ranked list [1, 4, 8, 7, 9].”
- Collaborative Filtering beyond the User-Item Matrix (2014, background): “Because the recommendation needs of groups are complex and go beyond the sum of the needs of the individual group members, group recommendation has been identified as a research challenge in recommender systems [Jameson and Smyth 2007].”
- Make it personal: A social explanation system applied to group recommendations (2017, background): “Depending on the number of users that will employ the product, we can speak of individual recommenders (Ricci et al., 2015) or group recommenders (Jameson and Smyth, 2007).”
- Recommender systems survey (2013, background): “RS that consider groups of users [108] are starting to expand and to be used in different areas: tourism [14], music [55], TV [238], web [176].”
- User Models for Adaptive Hypermedia and Adaptive Educational Systems (2007, neutral): “More information about group modeling is provided in Chapter 20 of this book [92].”
- Recommender Systems (2016, positive): “Detailed surveys on the subject may be found in [45, 271, 407].”