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
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/76373
Ver los metadatos del registro completo
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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 |
dc.type.none.fl_str_mv |
info:eu-repo/semantics/conferenceObject info:eu-repo/semantics/publishedVersion Objeto de conferencia http://purl.org/coar/resource_type/c_5794 info:ar-repo/semantics/documentoDeConferencia |
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eng |
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eng |
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info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nd/3.0/ Creative Commons Attribution-NoDerivs 3.0 Unported (CC BY-ND 3.0) |
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openAccess |
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http://creativecommons.org/licenses/by-nd/3.0/ Creative Commons Attribution-NoDerivs 3.0 Unported (CC BY-ND 3.0) |
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