ORSUM - Workshop on Online Recommender Systems and User Modeling

• Tipo: Artigo em Livro de Atas de Conferência Internacional
• Data: 2020

Autores

Vinagre, J (Autor) Outra; Jorge, AM (Autor) FCUP; Ghossein, MA (Autor) Outra; Bifet, A (Autor) Outra

Ata de Conferência Internacional

Título: RecSys 2020: Fourteenth ACM Conference on Recommender Systems, Virtual Event, Brazil, September 22-26, 2020

Páginas: 619-620

14th ACM Conference on Recommender Systems, RecSys 2020

22 September 2020 through 26 September 2020

Indexação

Scopus - 4 Citações

Outras Informações

ID Authenticus: P-00S-T8E

DOI: 10.1145/3383313.3411531

Abstract (EN): Modern online web-based systems continuously generate data at very fast rates. This continuous flow of data encompasses web content - e.g. posts, news, products, comments -, but also user feedback - e.g. ratings, views, reads, clicks, thumbs up -, as well as context information - device used, geographic info, social network, current user activity, weather. This is potentially overwhelming for systems and algorithms design to train in offline batches, given the continuous and potentially fast change of content, context and user preferences. Therefore it is important to investigate online methods to be able to transparently adapt to the inherent dynamics of online systems. Incremental models that learn from data streams are gaining attention in the recommender systems community, given their natural ability to deal with data generated in dynamic, complex environments. User modeling and personalization can particularly benefit from algorithms capable of maintaining models incrementally and online, as data is generated. The objective of this workshop is to foster contributions and bring together a growing community of researchers and practitioners interested in online, adaptive approaches to user modeling, recommendation and personalization, as well as other related tasks, such as evaluation, reproducibility, privacy and explainability. © 2020 Owner/Author.

Idioma: Inglês

Tipo (Avaliação Docente): Científica