RelEmb: A Relevance-based Application Embedding for Mobile App Retrieval and Categorization

被引：0

作者：

Krishna, Shubham ^{[1
]}

Bajaj, Ahsaas ^{[1
]}

Rungta, Mukund ^{[1
]}

Tiwari, Hemant ^{[1
]}

Vala, Vanraj ^{[1
]}

机构：

[1] Samsung R&D Inst, Bengaluru, India

来源：

COMPUTACION Y SISTEMAS | 2019年 / 23卷 / 03期

关键词：

Information systems and retrieval; mobile applications; application embedding;

D O I：

10.13053/CyS-23-3-3258

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页码：969 / 978

页数：10

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