A novel approach for classifying customer complaints through graphs similarities in argumentative dialogues

Autores
Galitsky, Boris; González, María Paula; Chesñevar, Carlos Iván
Año de publicación
2009
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Automating customer complaints processing is a major issue in the context of knowledge management technologies for most companies nowadays. Automated decision-support systems are important for complaint processing, integrating human experience in understanding complaints and the application of machine learning techniques. In this context, a major challenge in complaint processing involves assessing the validity of a customer complaint on the basis of the emerging dialogue between a customer and a company representative. This paper presents a novel approach for modelling and classifying complaint scenarios associated with customer-company dialogues. Such dialogues are formalized as labelled graphs, in which both company and customer interact through communicative actions, providing arguments that support their points. We show that such argumentation provides a complement to perform machine learning reasoning on communicative actions, improving the resulting classification accuracy.
Fil: Galitsky, Boris. University of London; Reino Unido
Fil: González, María Paula. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras; Argentina
Fil: Chesñevar, Carlos Iván. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras; Argentina
Materia
ARGUMENTATIVE DIALOGUES
AUTOMATED COMPLAINT PROCESSING
AUTOMATED DECISION MAKING
PATTERN MATCHING
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/75391
Acceder
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network_name_str CONICET Digital (CONICET)
spelling A novel approach for classifying customer complaints through graphs similarities in argumentative dialoguesGalitsky, BorisGonzález, María PaulaChesñevar, Carlos IvánARGUMENTATIVE DIALOGUESAUTOMATED COMPLAINT PROCESSINGAUTOMATED DECISION MAKINGPATTERN MATCHINGhttps://purl.org/becyt/ford/1.2https://purl.org/becyt/ford/1Automating customer complaints processing is a major issue in the context of knowledge management technologies for most companies nowadays. Automated decision-support systems are important for complaint processing, integrating human experience in understanding complaints and the application of machine learning techniques. In this context, a major challenge in complaint processing involves assessing the validity of a customer complaint on the basis of the emerging dialogue between a customer and a company representative. This paper presents a novel approach for modelling and classifying complaint scenarios associated with customer-company dialogues. Such dialogues are formalized as labelled graphs, in which both company and customer interact through communicative actions, providing arguments that support their points. We show that such argumentation provides a complement to perform machine learning reasoning on communicative actions, improving the resulting classification accuracy.Fil: Galitsky, Boris. University of London; Reino UnidoFil: González, María Paula. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras; ArgentinaFil: Chesñevar, Carlos Iván. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras; ArgentinaElsevier Science2009-02-25info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/75391Galitsky, Boris; González, María Paula; Chesñevar, Carlos Iván; A novel approach for classifying customer complaints through graphs similarities in argumentative dialogues; Elsevier Science; Decision Support Systems; 46; 3; 25-2-2009; 717-7290167-9236CONICET DigitalCONICETenginfo:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S016792360800208Xinfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.dss.2008.11.015info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2026-08-25T15:31:46Zoai:ri.conicet.gov.ar:11336/75391instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982026-08-25 15:31:47.614CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A novel approach for classifying customer complaints through graphs similarities in argumentative dialogues
title A novel approach for classifying customer complaints through graphs similarities in argumentative dialogues
spellingShingle A novel approach for classifying customer complaints through graphs similarities in argumentative dialogues
Galitsky, Boris
ARGUMENTATIVE DIALOGUES
AUTOMATED COMPLAINT PROCESSING
AUTOMATED DECISION MAKING
PATTERN MATCHING
title_short A novel approach for classifying customer complaints through graphs similarities in argumentative dialogues
title_full A novel approach for classifying customer complaints through graphs similarities in argumentative dialogues
title_fullStr A novel approach for classifying customer complaints through graphs similarities in argumentative dialogues
title_full_unstemmed A novel approach for classifying customer complaints through graphs similarities in argumentative dialogues
title_sort A novel approach for classifying customer complaints through graphs similarities in argumentative dialogues
dc.creator.none.fl_str_mv Galitsky, Boris
González, María Paula
Chesñevar, Carlos Iván
author Galitsky, Boris
author_facet Galitsky, Boris
González, María Paula
Chesñevar, Carlos Iván
author_role author
author2 González, María Paula
Chesñevar, Carlos Iván
author2_role author
author
dc.subject.none.fl_str_mv ARGUMENTATIVE DIALOGUES
AUTOMATED COMPLAINT PROCESSING
AUTOMATED DECISION MAKING
PATTERN MATCHING
topic ARGUMENTATIVE DIALOGUES
AUTOMATED COMPLAINT PROCESSING
AUTOMATED DECISION MAKING
PATTERN MATCHING
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.2
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Automating customer complaints processing is a major issue in the context of knowledge management technologies for most companies nowadays. Automated decision-support systems are important for complaint processing, integrating human experience in understanding complaints and the application of machine learning techniques. In this context, a major challenge in complaint processing involves assessing the validity of a customer complaint on the basis of the emerging dialogue between a customer and a company representative. This paper presents a novel approach for modelling and classifying complaint scenarios associated with customer-company dialogues. Such dialogues are formalized as labelled graphs, in which both company and customer interact through communicative actions, providing arguments that support their points. We show that such argumentation provides a complement to perform machine learning reasoning on communicative actions, improving the resulting classification accuracy.
Fil: Galitsky, Boris. University of London; Reino Unido
Fil: González, María Paula. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras; Argentina
Fil: Chesñevar, Carlos Iván. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras; Argentina
description Automating customer complaints processing is a major issue in the context of knowledge management technologies for most companies nowadays. Automated decision-support systems are important for complaint processing, integrating human experience in understanding complaints and the application of machine learning techniques. In this context, a major challenge in complaint processing involves assessing the validity of a customer complaint on the basis of the emerging dialogue between a customer and a company representative. This paper presents a novel approach for modelling and classifying complaint scenarios associated with customer-company dialogues. Such dialogues are formalized as labelled graphs, in which both company and customer interact through communicative actions, providing arguments that support their points. We show that such argumentation provides a complement to perform machine learning reasoning on communicative actions, improving the resulting classification accuracy.
publishDate 2009
dc.date.none.fl_str_mv 2009-02-25
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/75391
Galitsky, Boris; González, María Paula; Chesñevar, Carlos Iván; A novel approach for classifying customer complaints through graphs similarities in argumentative dialogues; Elsevier Science; Decision Support Systems; 46; 3; 25-2-2009; 717-729
0167-9236
CONICET Digital
CONICET
url http://hdl.handle.net/11336/75391
identifier_str_mv Galitsky, Boris; González, María Paula; Chesñevar, Carlos Iván; A novel approach for classifying customer complaints through graphs similarities in argumentative dialogues; Elsevier Science; Decision Support Systems; 46; 3; 25-2-2009; 717-729
0167-9236
CONICET Digital
CONICET
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/https://www.sciencedirect.com/science/article/pii/S016792360800208X
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.dss.2008.11.015
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier Science
publisher.none.fl_str_mv Elsevier Science
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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score 13.364332

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