Alemany-Bordera, J.; Heras Barberá, SM.; Palanca Cámara, J.; Julian Inglada, VJ. (2016). Bargaining agents based system for automatic classification of potential allergens in recipes. ADCAIJ : Advances in Distributed Computing and Artificial Intelligence Journal. 5(2):43-51. https://doi.org/10.14201/ADCAIJ2016524351
Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/81837
Title:
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Bargaining agents based system for automatic classification of potential allergens in recipes
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Author:
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Alemany-Bordera, José
Heras Barberá, Stella María
Palanca Cámara, Javier
Julian Inglada, Vicente Javier
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UPV Unit:
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Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació
Universitat Politècnica de València. Escola Tècnica Superior d'Enginyeria Informàtica
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Issued date:
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Abstract:
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[EN] The automatic recipe recommendation which take into account the dietary restrictions of users (such as allergies or intolerances) is a complex and open problem. Some of the limitations of the problem is the lack of ...[+]
[EN] The automatic recipe recommendation which take into account the dietary restrictions of users (such as allergies or intolerances) is a complex and open problem. Some of the limitations of the problem is the lack of food databases correctly labeled with its potential allergens and non-unification of this information by companies in the food sector. In the absence of an appropriate solution, people affected by food restrictions cannot use recommender systems, because this recommend them inappropriate recipes. In order to resolve this situation, in this article we propose a solution based on a collaborative multi-agent
system, using negotiation and machine learning techniques, is able to detect and label potential allergens in recipes. The proposed system is being employed in receteame.com, a recipe recommendation system which includes persuasive technologies, which are interactive technologies aimed at changing users’ attitudes or behaviors through persuasion and social influence, and social information to improve the recommendations
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Subjects:
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Recommendation system
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Food allergy
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Multi-agent system
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Copyrigths:
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Reconocimiento - No comercial - Sin obra derivada (by-nc-nd)
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Source:
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ADCAIJ : Advances in Distributed Computing and Artificial Intelligence Journal. (issn:
2255-2863
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DOI:
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10.14201/ADCAIJ2016524351
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Publisher:
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Ediciones Universidad de Salamanca
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Publisher version:
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https://dx.doi.org/10.14201/ADCAIJ2016524351
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Project ID:
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info:eu-repo/grantAgreement/MINECO//TIN2015-65515-C4-1-R/ES/ARQUITECTURA PERSUASIVA PARA EL USO SOSTENIBLE E INTELIGENTE DE VEHICULOS EN FLOTAS URBANAS/
info:eu-repo/grantAgreement/UPV//PAID-10-14/
info:eu-repo/grantAgreement/MINECO//TIN2014-55206-R/ES/PRIVACIDAD EN ENTORNOS SOCIALES EDUCATIVOS DURANTE LA INFANCIA Y LA ADOLESCENCIA/
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Thanks:
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This work was supported by the projects TIN2015-65515-C4-1-R and TIN2014-55206-R of the Spanish government and by the grant program for the recruitment of doctors for the Spanish system of science and technology (PAID-10-14) ...[+]
This work was supported by the projects TIN2015-65515-C4-1-R and TIN2014-55206-R of the Spanish government and by the grant program for the recruitment of doctors for the Spanish system of science and technology (PAID-10-14) of the Universitat Politecnica de Valencia.
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Type:
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Artículo
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