TN-MR: topic-aware neural network-based mobile application recommendation
International Journal of Web Information Systems
ISSN: 1744-0084
Article publication date: 6 February 2024
Issue publication date: 23 February 2024
Abstract
Purpose
With the increasing number of mobile applications, efficiently recommending mobile applications to users has become a challenging problem. Although existing mobile application recommendation approaches based on user attributes and behaviors have achieved notable effectiveness, they overlook the diffusion patterns and interdependencies of topic-specific mobile applications among user groups. mobile applications among user groups. This paper aims to capture the diffusion patterns and interdependencies of mobile applications among user groups. To achieve this, a topic-aware neural network-based mobile application recommendation method, referred to as TN-MR, is proposed.
Design/methodology/approach
In this method, first, the user representations are enhanced by introducing a topic-aware attention layer, which captures both the topic context and the diffusion history context. Second, it exploits a time-decay mechanism to simulate changes in user interest. Multitopic user representations are aggregated by the time decay module to output the user representations of cascading representations under multiple topics. Finally, user scores that are likely to download the mobile application are predicted and ranked.
Findings
Experimental comparisons and analyses were conducted on the actual 360App data set, and the results demonstrate that the effectiveness of mobile application recommendations can be significantly improved by using TN-MR.
Originality/value
In this paper, the authors propose a mobile application recommendation method based on topic-aware attention networks. By capturing the diffusion patterns and dependencies of mobile applications, it effectively assists users in selecting their applications of interest from thousands of options, significantly improving the accuracy of mobile application recommendations.
Keywords
Acknowledgements
The work of this paper is supported by the National Natural Science Foundation of China with Grant no. 62376062 and 62177014, the National Key R&D Program of China with Grant no. 2018YFB1402800, Hunan Provincial Natural Science Foundation of China with Grant no. 2022JJ30020 and the Science and Technology Innovation Program of Hunan Province with Grant No. 2023sk2081.
Citation
Chen, J., Cao, B., Peng, Z., Xie, Z., Liu, S. and Peng, Q. (2024), "TN-MR: topic-aware neural network-based mobile application recommendation", International Journal of Web Information Systems, Vol. 20 No. 2, pp. 159-175. https://doi.org/10.1108/IJWIS-10-2023-0205
Publisher
:Emerald Publishing Limited
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