An Experience Report on using the EDON Method for Building a Team Recommender System

Autores
Ayub, María Celeste; Cian, Ayelén N.; Caliusco, María Laura; Reynares, Emiliano
Año de publicación
2013
Idioma
inglés
Tipo de recurso
documento de conferencia
Estado
versión publicada
Descripción
Team Recommender Systems (TRS) have become extremely common in recent years because they are software tools and techniques that helps to organizations to composite team needed to carry out a task requiring multiple skills. TRS have two important problems: (1) managing semantic heterogeneity that occurs when the data describing the same entities related to the real world is represented in different ways, and (2) specialization excess leading to display the objects of highest similarity with the user specified instead of a wide range of options leaving out of consideration the highest possible user interest information. On the other hand, recently, the ontology-based information systems have gained the attention of the researchers and practitioners since they handle the semantic heterogeneity problem. In this paper we report our experience in using the EDON methodology to build a TRS that analyses human resource information to recommend a work team for a software development project.
Sociedad Argentina de Informática e Investigación Operativa (SADIO)
Materia
Ciencias Informáticas
team recommender systems
ontology-based information system
Nivel de accesibilidad
acceso abierto
Condiciones de uso
http://creativecommons.org/licenses/by-nd/3.0/
Repositorio
SEDICI (UNLP)
Institución
Universidad Nacional de La Plata
OAI Identificador
oai:sedici.unlp.edu.ar:10915/76373

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spelling An Experience Report on using the EDON Method for Building a Team Recommender SystemAyub, María CelesteCian, Ayelén N.Caliusco, María LauraReynares, EmilianoCiencias Informáticasteam recommender systemsontology-based information systemTeam Recommender Systems (TRS) have become extremely common in recent years because they are software tools and techniques that helps to organizations to composite team needed to carry out a task requiring multiple skills. TRS have two important problems: (1) managing semantic heterogeneity that occurs when the data describing the same entities related to the real world is represented in different ways, and (2) specialization excess leading to display the objects of highest similarity with the user specified instead of a wide range of options leaving out of consideration the highest possible user interest information. On the other hand, recently, the ontology-based information systems have gained the attention of the researchers and practitioners since they handle the semantic heterogeneity problem. In this paper we report our experience in using the EDON methodology to build a TRS that analyses human resource information to recommend a work team for a software development project.Sociedad Argentina de Informática e Investigación Operativa (SADIO)2013-09info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf16-25http://sedici.unlp.edu.ar/handle/10915/76373enginfo:eu-repo/semantics/altIdentifier/issn/1850-2792info:eu-repo/semantics/reference/hdl/10915/135233info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nd/3.0/Creative Commons Attribution-NoDerivs 3.0 Unported (CC BY-ND 3.0)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2025-09-29T11:13:25Zoai:sedici.unlp.edu.ar:10915/76373Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292025-09-29 11:13:26.045SEDICI (UNLP) - Universidad Nacional de La Platafalse
dc.title.none.fl_str_mv An Experience Report on using the EDON Method for Building a Team Recommender System
title An Experience Report on using the EDON Method for Building a Team Recommender System
spellingShingle An Experience Report on using the EDON Method for Building a Team Recommender System
Ayub, María Celeste
Ciencias Informáticas
team recommender systems
ontology-based information system
title_short An Experience Report on using the EDON Method for Building a Team Recommender System
title_full An Experience Report on using the EDON Method for Building a Team Recommender System
title_fullStr An Experience Report on using the EDON Method for Building a Team Recommender System
title_full_unstemmed An Experience Report on using the EDON Method for Building a Team Recommender System
title_sort An Experience Report on using the EDON Method for Building a Team Recommender System
dc.creator.none.fl_str_mv Ayub, María Celeste
Cian, Ayelén N.
Caliusco, María Laura
Reynares, Emiliano
author Ayub, María Celeste
author_facet Ayub, María Celeste
Cian, Ayelén N.
Caliusco, María Laura
Reynares, Emiliano
author_role author
author2 Cian, Ayelén N.
Caliusco, María Laura
Reynares, Emiliano
author2_role author
author
author
dc.subject.none.fl_str_mv Ciencias Informáticas
team recommender systems
ontology-based information system
topic Ciencias Informáticas
team recommender systems
ontology-based information system
dc.description.none.fl_txt_mv Team Recommender Systems (TRS) have become extremely common in recent years because they are software tools and techniques that helps to organizations to composite team needed to carry out a task requiring multiple skills. TRS have two important problems: (1) managing semantic heterogeneity that occurs when the data describing the same entities related to the real world is represented in different ways, and (2) specialization excess leading to display the objects of highest similarity with the user specified instead of a wide range of options leaving out of consideration the highest possible user interest information. On the other hand, recently, the ontology-based information systems have gained the attention of the researchers and practitioners since they handle the semantic heterogeneity problem. In this paper we report our experience in using the EDON methodology to build a TRS that analyses human resource information to recommend a work team for a software development project.
Sociedad Argentina de Informática e Investigación Operativa (SADIO)
description Team Recommender Systems (TRS) have become extremely common in recent years because they are software tools and techniques that helps to organizations to composite team needed to carry out a task requiring multiple skills. TRS have two important problems: (1) managing semantic heterogeneity that occurs when the data describing the same entities related to the real world is represented in different ways, and (2) specialization excess leading to display the objects of highest similarity with the user specified instead of a wide range of options leaving out of consideration the highest possible user interest information. On the other hand, recently, the ontology-based information systems have gained the attention of the researchers and practitioners since they handle the semantic heterogeneity problem. In this paper we report our experience in using the EDON methodology to build a TRS that analyses human resource information to recommend a work team for a software development project.
publishDate 2013
dc.date.none.fl_str_mv 2013-09
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