Servicios Personalizados
Revista
Articulo
Indicadores
- Citado por SciELO
- Accesos
Links relacionados
- Similares en SciELO
Compartir
Computación y Sistemas
versión On-line ISSN 2007-9737versión impresa ISSN 1405-5546
Resumen
KRISHNA, Shubham et al. ReIEmb: A Relevance-based Application Embedding for Mobile App Retrieval and Categorization. Comp. y Sist. [online]. 2019, vol.23, n.3, pp.969-978. Epub 09-Ago-2021. ISSN 2007-9737. https://doi.org/10.13053/cys-23-3-3258.
Information Retrieval Systems have revolutionized the organization and extraction of Information. In recent years, mobile applications (apps) have become primary tools of collecting and disseminating information. However, limited research is available on how to retrieve and organize mobile apps on users' devices. In this paper, authors propose a novel method to estimate app-embeddings which are then applied to tasks like app clustering, classification, and retrieval. Usage of app-embedding for query expansion, nearest neighbor analysis enables unique and interesting use cases to enhance end-user experience with mobile apps.
Palabras llave : Information systems and retrieval; mobile applications; application embedding.