AI-driven dog training: Exploring solutions for personalized recommendations
Year: 2026
Type: conference-paper
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).
Author: Demian, Andrada
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7161565854
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