A Recommender System Based on Cohorts’ Similarity

Use este enlace para citar
http://hdl.handle.net/2183/25936
A non ser que se indique outra cousa, a licenza do ítem descríbese como Atribución-NoComercial 4.0 España
Coleccións
- Investigación (FIC) [1656]
Metadatos
Mostrar o rexistro completo do ítemTítulo
A Recommender System Based on Cohorts’ SimilarityData
2020-06-16Cita bibliográfica
Almeida JR, Monteiro E, Silva LB, Pazos A, Oliveira JL. A Recommender System Based on Cohorts’ Similarity: 2020; 270:1183-1184
Resumo
[Abstract]
Aiming to better understand the genetic and environmental associations of Alzheimer's disease, many clinical trials and scientific studies have been conducted. However, these studies are often based on a small number of participants. To address this limitation, there is an increasing demand of multi-cohorts studies, which can provide higher statistical power and clinical evidence. However, this data integration implies dealing with the diversity of cohorts structures and the wide variability of concepts. Moreover, discovering similar cohorts to extend a running study is typically a demanding task. In this paper, we present a recommendation system to allow finding similar cohorts based on profile interests. The method uses collaborative filtering mixed with context-based retrieval techniques to find relevant cohorts on scientific literature about Alzheimer's diseases. The method was validated in a set of 62 cohorts.
Palabras chave
Alzheimer cohorts
Cohort catalogue
Recommendation systems
Cohort catalogue
Recommendation systems
Versión do editor
Dereitos
Atribución-NoComercial 4.0 España
ISSN
18798365