AI-driven dog training: Exploring solutions for personalized recommendations

While technology has advanced dog training systems, many existing solutions remain expensive and focus primarily on the dog, without adequately considering the influence of the owner. This research presents a hybrid recommendation system that combines classical machine learning and generative AI to provide personalized training strategies based on both dog and owner characteristics. By accounting for the dynamics of the human-dog relationship, the system offers a more holistic and accessible alternative to existing tools. A comparative evaluation of both approaches, supported by user feedback, demonstrates their effectiveness and usability. The study proposes a dual-model framework that enhances personalization and interactivity in dog training, highlighting the potential of AI-based systems to improve the human–dog bond. Presented at the SCSS Student Conference 2025, Babeș-Bolyai University (not formally published in proceedings).

Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-05-18
DOI
https://doi.org/10.5281/zenodo.20266800
Primary Topic
Human-Animal Interaction Studies
Type
article
Field-Weighted Citation Impact
0.00
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article

AI-driven dog training: Exploring solutions for personalized recommendations

Andrada Demian
Zenodo (CERN European Organization for Nuclear Research)
Human-Animal Interaction Studies
article

AI-driven dog training: Exploring solutions for personalized recommendations

Andrada Demian
article en

Abstract

While technology has advanced dog training systems, many existing solutions remain expensive and focus primarily on the dog, without adequately considering the influence of the owner. This research presents a hybrid recommendation system that combines classical machine learning and generative AI to provide personalized training strategies based on both dog and owner characteristics. By accounting for the dynamics of the human-dog relationship, the system offers a more holistic and accessible alternative to existing tools. A comparative evaluation of both approaches, supported by user feedback, demonstrates their effectiveness and usability. The study proposes a dual-model framework that enhances personalization and interactivity in dog training, highlighting the potential of AI-based systems to improve the human–dog bond. Presented at the SCSS Student Conference 2025, Babeș-Bolyai University (not formally published in proceedings).

Zenodo (CERN European Organization for Nuclear Research)
Openalex Percentile: Top 6%
Human-Animal Interaction Studies
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