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Universidad de Lima

Matching system for Animal-assisted therapy based on the Levenshtein and Gale-Shapley algorithms

Abstract

dc:description.abstract

This current research is based on the implementation of an algorithm that assigns pets, cats, or dogs to persons with depressive disorders such as low self-esteem. We found that even though different institutions have made the assignments of pets to patients, we were not able to found one that uses an IT tool for this task. Because of this situation, we decided to adapt to the well-known Gale-Shapley algorithm that has been used successfully in different situations in which it needs a perfect match between two parties. The results obtained have been validated by experts in the field of animal and person psychology. Because the Gale-Shapley algorithm needs a preference array between the parts involved and due that an animal cannot establish this set of preferences, we aimed to use a string similarity-based algorithm for obtaining preferences arrays based on the behavioral traits of an animal or person.

Degree

thesis:*
Name thesis:degree_name
Ingeniero de sistemas
Level thesis:degree_level
Título Profesional
Discipline thesis:degree_discipline
Ingeniería de sistemas
Grantor dc:publisher
Universidad de Lima
Year dc:date.issued
2020

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Gutierrez Rondon, Carmen Giuliana
Advisor dc:contributor.advisor
  • Gutiérrez Cárdenas, Juan Manuel

Subjects

dc:subject × 6

Rights

dc:rights
Statement dc:rights
  • info:eu-repo/semantics/restrictedAccess
Language dc:language.iso
eng

Identifiers

dc:identifier.*
OAI identifier oai:identifier
oai:repositorio.ulima.edu.pe:20.500.12724/12723

Chain of custody

source
Harvested from
Universidad de Lima
Base URL
repositorio.ulima.edu.pe/oai/request
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Gutierrez Rondon, Carmen Giuliana. Matching system for Animal-assisted therapy based on the Levenshtein and Gale-Shapley algorithms. Título Profesional thesis, Universidad de Lima, 2020. https://hdl.handle.net/20.500.12724/12723