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An Elephant in the Dark: Creating Semantic Representations of Perceived Data with Conceptual Spaces

EasyChair Preprint 343

7 pagesDate: July 14, 2018

Abstract

This paper discusses the task of creating semantic representations to describe numerical observations using conceptual spaces. The theory of conceptual spaces is considered as a semantic representation to conceptualise the perceived numerical information and to infer linguistic descriptions. We propose a data-driven approach to construct conceptual spaces from numerical data automatically. First, the elements of a conceptual space are derived based on a set of numerical observations in order to semantically represent the concepts of a given data set. This data-driven conceptual space is then employed for the task of semantic inference, in order to linguistically describe unknown perceived observations.

Keyphrases: concept formation, conceptual spaces, semantic representation

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@booklet{EasyChair:343,
  author    = {Hadi Banaee and Erik Schaffernicht and Amy Loutfi},
  title     = {An Elephant in the Dark: Creating Semantic Representations of Perceived Data with Conceptual Spaces},
  doi       = {10.29007/twv9},
  howpublished = {EasyChair Preprint 343},
  year      = {EasyChair, 2018}}
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