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Computación y Sistemas

On-line version ISSN 2007-9737Print version ISSN 1405-5546

Abstract

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 Aug 09, 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.

Keywords : Information systems and retrieval; mobile applications; application embedding.

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