Extraction of Basic-Level Categories Using Dendrogram and Multidendrogram

  • Mariusz MulkaEmail author
  • Wojciech Lorkiewicz
  • Radosław P. Katarzyniak
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 1074)


Cognitive agents should be equipped with computational methods enabling autonomous extraction of internal cognitive structures, i.e., supporting organization of large datasets and facilitating interaction with human users. In this research, we focus solely on the extraction of basic-level categories. We propose a computational approach that allows the agent to develop, through individual interaction with the external world, provisional clusters (using hierarchal clustering techniques) and filter them, using predefined measures of basic-levelness (inspired by psycholinguistic research). We focus on analysing the behaviour of two proposed computational approaches, namely dendrogram and multidendrogram, to establishing provisional clusters. Further, the approach is extensively studied through an array of simulations. Obtained results highlight that the proposed methods can be used to extract basic-level categories.


Basic-level categories Cognitive computing 



This research was carried out at Wrocław University of Science and Technology (Poland) under Grant 0401/0190/18 titled Models and Methods of Semantic Communication in Cyber-Physical Systems.


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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • Mariusz Mulka
    • 1
    Email author
  • Wojciech Lorkiewicz
    • 1
  • Radosław P. Katarzyniak
    • 1
  1. 1.Faculty of Computer Science and ManagementWrocław University of Science and TechnologyWrocławPoland

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