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Learning of Conversational Systems Based on Linguistic Data Summarization Applications in BIM Environments

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Data Analytics and Computational Intelligence: Novel Models, Algorithms and Applications

Part of the book series: Studies in Big Data ((SBD,volume 132))

Abstract

In this work, the authors identified opportunities for improvements in conversational systems. In order to solve the conversational systems learning problems, this investigation proposes a new architectural model for the conversational system “BRasa,” consisting of two subsystems. The first, “BRasa_Assistant,” is oriented to direct communication with users, and the second “BRasa_LDS” is oriented to conversational system learning inspired by Linguistic Data Summarization techniques. BRasa_LDS generates summaries in natural language, which incorporate new knowledge into the conversational system database. In addition, is proposed a system of indicators for the self-assessment of the human–computer interaction of the conversational system. In the analysis results section, three sets of tests were designed to measure the quality of conversational system responses. The proposal is validated based on the criteria applicability and adequacy of the conversational system responses. It is shown that the application of linguistic data summarization techniques for learning conversational systems improves the behavior of these systems significantly.

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Author information

Authors and Affiliations

  1. Grupo de Inteligencia Artificial para el Desarrollo Sostenible, BusinessRedmine, IADES SRL, Company, Havana, 10400, Cuba

    Yuniesky Orlando Vasconcelo Mir, Iliana Pérez Pupo & Pedro Y. Piñero Pérez

  2. Departamento de Ingeniería de la Construcción, Universidad Católica del Norte, Antofagasta, Chile

    Luis Alvarado Acuña

  3. Centro de Gestión del Conocimiento, Comercio Interior, Havana, Cuba

    Aimee Graffo Pozo

Authors
  1. Yuniesky Orlando Vasconcelo Mir
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  2. Iliana Pérez Pupo
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  3. Pedro Y. Piñero Pérez
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  4. Luis Alvarado Acuña
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  5. Aimee Graffo Pozo
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Corresponding author

Correspondence to Iliana Pérez Pupo .

Editor information

Editors and Affiliations

  1. División Multidisciplinaria de Ciudad Universitaria, Universidad Autónoma de Ciudad Juárez, Chihuahua, Mexico

    Gilberto Rivera

  2. Tecnológico Nacional de México/Instituto Tecnológico de Ciudad Madero, Ciudad Madero, Tamaulipas, Mexico

    Laura Cruz-Reyes

  3. School of Engineering, Universidad de Cádiz, Cadiz, Spain

    Bernabé Dorronsoro

  4. Universidad Tecnológica de La Habana “José Antonio Echeverría”, La Habana, Cuba

    Alejandro Rosete

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Vasconcelo Mir, Y.O., Pérez Pupo, I., Piñero Pérez, P.Y., Alvarado Acuña, L., Graffo Pozo, A. (2023). Learning of Conversational Systems Based on Linguistic Data Summarization Applications in BIM Environments. In: Rivera, G., Cruz-Reyes, L., Dorronsoro, B., Rosete, A. (eds) Data Analytics and Computational Intelligence: Novel Models, Algorithms and Applications. Studies in Big Data, vol 132. Springer, Cham. https://doi.org/10.1007/978-3-031-38325-0_11

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