Time-aware recommender systems: a comprehensive survey and analysis of existing evaluation protocols

By Pedro G. Campos, Fernando Díez, Iván Cantador. User modeling and user-adapted interaction, 2013

449 citations recorded by the source corpus.

How researchers see this paper

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

Recommender Systems (2016, unknown): “A recent survey [130] points to the significant importance of evaluation methods in disambiguating the contradictory findings of the recent results and also proposes a number of evaluation metrics for temporal recommender systems.”
Sequential User-based Recurrent Neural Network Recommendations (2017, unknown): “important contextual dimension also in RS [4].”
Sequence-Aware Recommender Systems (2018, methodology): “Time-aware recommender systems (TARS) usually consider time information that is associated with past user actions to adapt the recommendations accordingly, see [17] for an overview.”
Artificial intelligence in recommender systems (2020, background): “Time-aware recommender systems were developed to address this issue [202].”
Latent Cross: Making Use of Context in Recurrent Recommender Systems (2018, background): “For example, temporal dynamics in recommendation have been explored widely [6].”