Designing intelligent database systems through argumentation
- Autores
- Capobianco, Marcela; Chesñevar, Carlos Iván; García, Alejandro Javier; Simari, Guillermo Ricardo
- Año de publicación
- 2008
- Idioma
- inglés
- Tipo de recurso
- documento de conferencia
- Estado
- versión publicada
- Descripción
- Information systems play an ever-increasing key role in our society. In particular, data intensive applications are in constant demand and there is need of computing environments with much more intelligent capabilities than those present in today’s Data-base Management Systems (DBMS). Nowadays intelligent applications require better reasoning capabilities than those present in older data processing systems[7]. Argumentation frameworks appear to be an excellent starting-point for building such systems. Research in argumentation has provided important results while striving to obtain tools for common sense reasoning. As a result, argumentation systems have substantially evolved in the past few years, and this resulted in a new set of argument-based applications in diverse areas where knowledge representation issues play a major role. Clustering algorithms [6], intelligent web search [3], recommender systems [4, 3], and natural language assessment [2] are the outcome of this evolution. We claim that massive data processing systems can be combined with argumentation to obtain systems that administer and reason with large databases. These would result in a system that can extract and process information from massive databases and exhibit intelligent behavior and common sense reasoning as a by-product of the argumentation system used for the reasoning process. In this work, we present a specialization of the DeLP [5] system, called Database Defeasible Logic Programming (DB DeLP). This framework could be easily integrated with a relational database component to achieve a system capable of massive data processing and intelligent behavior. Next, we formally define this system.
Eje: Agentes y Sistemas Inteligentes
Red de Universidades con Carreras en Informática (RedUNCI) - Materia
-
Ciencias Informáticas
Intelligent agents
Intelligent Database Systems
Argumentation - Nivel de accesibilidad
- acceso abierto
- Condiciones de uso
- http://creativecommons.org/licenses/by-nc-sa/2.5/ar/
- Repositorio
.jpg)
- Institución
- Universidad Nacional de La Plata
- OAI Identificador
- oai:sedici.unlp.edu.ar:10915/20526
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Designing intelligent database systems through argumentationCapobianco, MarcelaChesñevar, Carlos IvánGarcía, Alejandro JavierSimari, Guillermo RicardoCiencias InformáticasIntelligent agentsIntelligent Database SystemsArgumentationInformation systems play an ever-increasing key role in our society. In particular, data intensive applications are in constant demand and there is need of computing environments with much more intelligent capabilities than those present in today’s Data-base Management Systems (DBMS). Nowadays intelligent applications require better reasoning capabilities than those present in older data processing systems[7]. Argumentation frameworks appear to be an excellent starting-point for building such systems. Research in argumentation has provided important results while striving to obtain tools for common sense reasoning. As a result, argumentation systems have substantially evolved in the past few years, and this resulted in a new set of argument-based applications in diverse areas where knowledge representation issues play a major role. Clustering algorithms [6], intelligent web search [3], recommender systems [4, 3], and natural language assessment [2] are the outcome of this evolution. We claim that massive data processing systems can be combined with argumentation to obtain systems that administer and reason with large databases. These would result in a system that can extract and process information from massive databases and exhibit intelligent behavior and common sense reasoning as a by-product of the argumentation system used for the reasoning process. In this work, we present a specialization of the DeLP [5] system, called Database Defeasible Logic Programming (DB DeLP). This framework could be easily integrated with a relational database component to achieve a system capable of massive data processing and intelligent behavior. Next, we formally define this system.Eje: Agentes y Sistemas InteligentesRed de Universidades con Carreras en Informática (RedUNCI)2008-05info:eu-repo/semantics/conferenceObjectinfo:eu-repo/semantics/publishedVersionObjeto de conferenciahttp://purl.org/coar/resource_type/c_5794info:ar-repo/semantics/documentoDeConferenciaapplication/pdf85-89http://sedici.unlp.edu.ar/handle/10915/20526enginfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by-nc-sa/2.5/ar/Creative Commons Attribution-NonCommercial-ShareAlike 2.5 Argentina (CC BY-NC-SA 2.5)reponame:SEDICI (UNLP)instname:Universidad Nacional de La Platainstacron:UNLP2026-01-07T12:39:12Zoai:sedici.unlp.edu.ar:10915/20526Institucionalhttp://sedici.unlp.edu.ar/Universidad públicaNo correspondehttp://sedici.unlp.edu.ar/oai/snrdalira@sedici.unlp.edu.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:13292026-01-07 12:39:12.908SEDICI (UNLP) - Universidad Nacional de La Platafalse |
| dc.title.none.fl_str_mv |
Designing intelligent database systems through argumentation |
| title |
Designing intelligent database systems through argumentation |
| spellingShingle |
Designing intelligent database systems through argumentation Capobianco, Marcela Ciencias Informáticas Intelligent agents Intelligent Database Systems Argumentation |
| title_short |
Designing intelligent database systems through argumentation |
| title_full |
Designing intelligent database systems through argumentation |
| title_fullStr |
Designing intelligent database systems through argumentation |
| title_full_unstemmed |
Designing intelligent database systems through argumentation |
| title_sort |
Designing intelligent database systems through argumentation |
| dc.creator.none.fl_str_mv |
Capobianco, Marcela Chesñevar, Carlos Iván García, Alejandro Javier Simari, Guillermo Ricardo |
| author |
Capobianco, Marcela |
| author_facet |
Capobianco, Marcela Chesñevar, Carlos Iván García, Alejandro Javier Simari, Guillermo Ricardo |
| author_role |
author |
| author2 |
Chesñevar, Carlos Iván García, Alejandro Javier Simari, Guillermo Ricardo |
| author2_role |
author author author |
| dc.subject.none.fl_str_mv |
Ciencias Informáticas Intelligent agents Intelligent Database Systems Argumentation |
| topic |
Ciencias Informáticas Intelligent agents Intelligent Database Systems Argumentation |
| dc.description.none.fl_txt_mv |
Information systems play an ever-increasing key role in our society. In particular, data intensive applications are in constant demand and there is need of computing environments with much more intelligent capabilities than those present in today’s Data-base Management Systems (DBMS). Nowadays intelligent applications require better reasoning capabilities than those present in older data processing systems[7]. Argumentation frameworks appear to be an excellent starting-point for building such systems. Research in argumentation has provided important results while striving to obtain tools for common sense reasoning. As a result, argumentation systems have substantially evolved in the past few years, and this resulted in a new set of argument-based applications in diverse areas where knowledge representation issues play a major role. Clustering algorithms [6], intelligent web search [3], recommender systems [4, 3], and natural language assessment [2] are the outcome of this evolution. We claim that massive data processing systems can be combined with argumentation to obtain systems that administer and reason with large databases. These would result in a system that can extract and process information from massive databases and exhibit intelligent behavior and common sense reasoning as a by-product of the argumentation system used for the reasoning process. In this work, we present a specialization of the DeLP [5] system, called Database Defeasible Logic Programming (DB DeLP). This framework could be easily integrated with a relational database component to achieve a system capable of massive data processing and intelligent behavior. Next, we formally define this system. Eje: Agentes y Sistemas Inteligentes Red de Universidades con Carreras en Informática (RedUNCI) |
| description |
Information systems play an ever-increasing key role in our society. In particular, data intensive applications are in constant demand and there is need of computing environments with much more intelligent capabilities than those present in today’s Data-base Management Systems (DBMS). Nowadays intelligent applications require better reasoning capabilities than those present in older data processing systems[7]. Argumentation frameworks appear to be an excellent starting-point for building such systems. Research in argumentation has provided important results while striving to obtain tools for common sense reasoning. As a result, argumentation systems have substantially evolved in the past few years, and this resulted in a new set of argument-based applications in diverse areas where knowledge representation issues play a major role. Clustering algorithms [6], intelligent web search [3], recommender systems [4, 3], and natural language assessment [2] are the outcome of this evolution. We claim that massive data processing systems can be combined with argumentation to obtain systems that administer and reason with large databases. These would result in a system that can extract and process information from massive databases and exhibit intelligent behavior and common sense reasoning as a by-product of the argumentation system used for the reasoning process. In this work, we present a specialization of the DeLP [5] system, called Database Defeasible Logic Programming (DB DeLP). This framework could be easily integrated with a relational database component to achieve a system capable of massive data processing and intelligent behavior. Next, we formally define this system. |
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2008 |
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2008-05 |
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