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image of Device Recommendation Based on Inference Using Big-Five Personality Trait

Abstract

Introduction

A device collaboration system provides services through the cooperation of nearby sharable devices. Therefore, such a system can be applied even to small personal devices with limited resources, such as smartwatches. Previous work proposed methods for device collaboration and recommendation. It also identified two key challenges: reducing inference time for collaboration among a large number of devices, and addressing the cold-start problem when introducing new devices. This paper proposes an approach to address both of these issues.

Methods

To reduce the time required for device recommendation, this paper proposes a preprocessing method based on the Big Five personality traits. A prototype system implementing the proposed collaboration method is developed on a mobile device and evaluated.

Results

The proposed method achieved faster device recommendation and higher user satisfaction compared to the previous approach.

Discussion

This study demonstrates that personality-based preprocessing enables the implementation of real-time recommendation services, even on devices with limited computing resources.

Conclusion

The proposed method can be applied not only to device collaboration in IoT environments but also to context-aware recommendation systems. The results of this study are expected to contribute to both the fields of psychology and computer science.

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2025-08-28
2025-11-07

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Device Recommendation Based on Inference Using Big-Five Personality Trait
Bentham Science Publishers ; https://doi.org/10.2174/0122103279392276250801011829
/content/journals/swcc/10.2174/0122103279392276250801011829
/content/journals/swcc/10.2174/0122103279392276250801011829
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  • Article Type:     Research Article
Keywords: device recommendation ; collaboration system ; Big five personality trait ; user personality

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