SciELO - Scientific Electronic Library Online

 
vol.23 número3Relation between Titles and Keywords in Japanese Academic Papers using Quantitative Analysis and Machine LearningScript Independent Morphological Segmentation for Arabic Maghrebi Dialects: An Application to Machine Translation índice de autoresíndice de assuntospesquisa de artigos
Home Pagelista alfabética de periódicos  

Serviços Personalizados

Journal

Artigo

Indicadores

Links relacionados

  • Não possue artigos similaresSimilares em SciELO

Compartilhar


Computación y Sistemas

versão On-line ISSN 2007-9737versão impressa ISSN 1405-5546

Resumo

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.

Palavras-chave : Information systems and retrieval; mobile applications; application embedding.

        · texto em Inglês     · Inglês ( pdf )