Finding a pet that matches an individual’s lifestyle is a significant challenge, as potential adopters differ in their habits, living conditions, and expectations, while pets vary in their temperament, behavior, and specific needs. Mismatches can lead to adopter dissatisfaction and the return of pets to shelters, negatively affecting the well-being of all involved.
This thesis addresses the problem of matching pets with adopters and proposes a recommendation system that suggests the most suitable matches based on the characteristics of both pets and users. The model considers key animal attributes, such as activity level, need for space, compatibility with children and other animals, and potential health conditions, while also incorporating user preferences and lifestyle.
The proposed system enables more informed decision-making in the adoption process and contributes to reducing unsuitable matches, thereby increasing the likelihood of successful and long-term adoptions and improving animal welfare.
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