Defeasible argumentation over relational databases
Defeasible argumentation has been applied successfully in several real-world domains in which it is necessary to handle incomplete and contradictory information. In recent years, there have been interesting attempts to carry out argumentation processes supported by massive repositories develop...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IOS Press
2017-05-01
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| Series: | Argument & Computation |
| Online Access: | https://doi.org/10.3233/AAC-170017 |
| _version_ | 1797860908192497664 |
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| author | Cristhian Ariel David Deagustini Santiago Emanuel Fulladoza Dalibón Sebastián Gottifredi Marcelo Alejandro Falappa Carlos Iván Chesñevar Guillermo Ricardo Simari |
| author_facet | Cristhian Ariel David Deagustini Santiago Emanuel Fulladoza Dalibón Sebastián Gottifredi Marcelo Alejandro Falappa Carlos Iván Chesñevar Guillermo Ricardo Simari |
| author_sort | Cristhian Ariel David Deagustini |
| collection | DOAJ |
| description |
Defeasible argumentation has been applied successfully in several real-world domains in which it is necessary to handle incomplete and contradictory information. In recent years, there have been interesting attempts to carry out argumentation processes supported by massive repositories developing argumentative reasoning applications. One of such efforts builds arguments by retrieving information from relational databases using the DBI-DeLP framework; this article presents eDBI-DeLP, which extends the original DBI-DeLP framework by providing two novel aspects which refine the interaction between DeLP programs and relational databases. First, we expand the expressiveness of dbi-delp programs by providing ways of controlling how the information in databases is recovered; this is done by introducing filters that enable an improved fine-grained control on the argumentation processes which become useful in applications, providing the semantics and the implementation of such filters. Second, we introduce an argument comparison criterion which can be adjusted at the level of literals to model particular features such as credibility and topic expertise, among others. These new tools can be particularly useful in environments such as medical diagnosis expert systems, decision support systems, or recommender systems based on argumentation, where datasets are often provided in the form of relational databases. |
| first_indexed | 2024-04-09T21:54:39Z |
| format | Article |
| id | doaj.art-cc0bae8992804b32b5af8882542bce4c |
| institution | Directory Open Access Journal |
| issn | 1946-2166 1946-2174 |
| language | English |
| last_indexed | 2024-04-09T21:54:39Z |
| publishDate | 2017-05-01 |
| publisher | IOS Press |
| record_format | Article |
| series | Argument & Computation |
| spelling | doaj.art-cc0bae8992804b32b5af8882542bce4c2023-03-24T09:48:02ZengIOS PressArgument & Computation1946-21661946-21742017-05-0181355910.3233/AAC-170017Defeasible argumentation over relational databasesCristhian Ariel David Deagustini0Santiago Emanuel Fulladoza Dalibón1Sebastián Gottifredi2Marcelo Alejandro Falappa3Carlos Iván Chesñevar4Guillermo Ricardo Simari5AI R&D Lab., Institute for Computer Science and Engineering (ICIC), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Alem 1253, (B8000CPB), Bahía Blanca Bs. As., Argentina. E-mails: cadd@cs.uns.edu.ar, sef@cs.uns.edu.ar, sg@cs.uns.edu.ar, mfalappa@cs.uns.edu.ar, cic@cs.uns.edu.ar, grs@cs.uns.edu.arAI R&D Lab., Institute for Computer Science and Engineering (ICIC), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Alem 1253, (B8000CPB), Bahía Blanca Bs. As., Argentina. E-mails: cadd@cs.uns.edu.ar, sef@cs.uns.edu.ar, sg@cs.uns.edu.ar, mfalappa@cs.uns.edu.ar, cic@cs.uns.edu.ar, grs@cs.uns.edu.arAI R&D Lab., Institute for Computer Science and Engineering (ICIC), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Alem 1253, (B8000CPB), Bahía Blanca Bs. As., Argentina. E-mails: cadd@cs.uns.edu.ar, sef@cs.uns.edu.ar, sg@cs.uns.edu.ar, mfalappa@cs.uns.edu.ar, cic@cs.uns.edu.ar, grs@cs.uns.edu.arAI R&D Lab., Institute for Computer Science and Engineering (ICIC), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Alem 1253, (B8000CPB), Bahía Blanca Bs. As., Argentina. E-mails: cadd@cs.uns.edu.ar, sef@cs.uns.edu.ar, sg@cs.uns.edu.ar, mfalappa@cs.uns.edu.ar, cic@cs.uns.edu.ar, grs@cs.uns.edu.arAI R&D Lab., Institute for Computer Science and Engineering (ICIC), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Alem 1253, (B8000CPB), Bahía Blanca Bs. As., Argentina. E-mails: cadd@cs.uns.edu.ar, sef@cs.uns.edu.ar, sg@cs.uns.edu.ar, mfalappa@cs.uns.edu.ar, cic@cs.uns.edu.ar, grs@cs.uns.edu.arAI R&D Lab., Institute for Computer Science and Engineering (ICIC), Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Alem 1253, (B8000CPB), Bahía Blanca Bs. As., Argentina. E-mails: cadd@cs.uns.edu.ar, sef@cs.uns.edu.ar, sg@cs.uns.edu.ar, mfalappa@cs.uns.edu.ar, cic@cs.uns.edu.ar, grs@cs.uns.edu.ar Defeasible argumentation has been applied successfully in several real-world domains in which it is necessary to handle incomplete and contradictory information. In recent years, there have been interesting attempts to carry out argumentation processes supported by massive repositories developing argumentative reasoning applications. One of such efforts builds arguments by retrieving information from relational databases using the DBI-DeLP framework; this article presents eDBI-DeLP, which extends the original DBI-DeLP framework by providing two novel aspects which refine the interaction between DeLP programs and relational databases. First, we expand the expressiveness of dbi-delp programs by providing ways of controlling how the information in databases is recovered; this is done by introducing filters that enable an improved fine-grained control on the argumentation processes which become useful in applications, providing the semantics and the implementation of such filters. Second, we introduce an argument comparison criterion which can be adjusted at the level of literals to model particular features such as credibility and topic expertise, among others. These new tools can be particularly useful in environments such as medical diagnosis expert systems, decision support systems, or recommender systems based on argumentation, where datasets are often provided in the form of relational databases.https://doi.org/10.3233/AAC-170017 |
| spellingShingle | Cristhian Ariel David Deagustini Santiago Emanuel Fulladoza Dalibón Sebastián Gottifredi Marcelo Alejandro Falappa Carlos Iván Chesñevar Guillermo Ricardo Simari Defeasible argumentation over relational databases Argument & Computation |
| title | Defeasible argumentation over relational databases |
| title_full | Defeasible argumentation over relational databases |
| title_fullStr | Defeasible argumentation over relational databases |
| title_full_unstemmed | Defeasible argumentation over relational databases |
| title_short | Defeasible argumentation over relational databases |
| title_sort | defeasible argumentation over relational databases |
| url | https://doi.org/10.3233/AAC-170017 |
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