An Argumentative Recommendation Approach Based on Contextual Aspects

  • Juan Carlos Lionel TezeEmail author
  • Lluis Godo
  • Guillermo Ricardo Simari
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11142)


Argumentation-based recommender systems constitute an interesting tool to provide reasoned recommendations in complex domains with unresolved contradictory information situations and incomplete information. In these systems, the use of contextual information becomes a central issue in order to come up with personalized recommendations. An argumentative recommender system that offers mechanisms to handle contextual aspects of the recommendation domain provides an important ability that can be exploited by the user. However, in most of existing works, this issue has not been extensively studied. In this work, we propose an argumentation-based formalization for dealing with this issue. We present a general framework that allows the design of recommender systems capable of handling queries that can include (possibly inconsistent) contextual information under which recommendations should be computed. To answer a query, in the proposed argumentation-based approach, the system first selects alternative instances according to the user’s supplied contextual information, and then makes recommendations, in both cases through a defeasible argumentative analysis.


Recommenders Argumentation Contextual information 



This work has been partially supported by EU H2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 690974 for the project MIREL: MIning and REasoning with Legal texts, and by funds provided by CONICET, Universidad Nacional del Sur by PGI-UNS (grant 24/N040), and Universidad Nacional de Entre Ríos. Godo acknowledges the Spanish FEDER/MINECO project TIN2015-71799- C2-1-P.


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Copyright information

© Springer Nature Switzerland AG 2018

Authors and Affiliations

  • Juan Carlos Lionel Teze
    • 1
    • 2
    • 3
    Email author
  • Lluis Godo
    • 4
  • Guillermo Ricardo Simari
    • 1
  1. 1.Institute for Computer Science and Engineering (ICIC), Departamento de Ciencias e Ing. de la ComputaciónUniversidad Nacional del SurBahía Blanca, Buenos AiresArgentina
  2. 2.Agents and Intelligent Systems Area, Faculty of Management SciencesUniversidad Nacional de Entre RíosConcordiaArgentina
  3. 3.Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET)Buenos AiresArgentina
  4. 4.Artificial Intelligence Research Institute (IIIA-CSIC)BarcelonaSpain

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