Approximation spaces and information granulation

  • Authors:

  • Andrzej Skowron;Roman Świniarski;Piotr Synak

  • Affiliations:

  • Institute of Mathematics, Warsaw University, Warsaw, Poland;Institute of Computer Science, Polish Academy of Sciences, Warsaw, Poland;Polish-Japanese Institute of Information Technology, Warsaw, Poland

  • Venue:
  • Transactions on Rough Sets III
  • Year:
  • 2005

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Abstract

In this paper, we discuss approximation spaces in a granular computing framework. Such approximation spaces generalise the approaches to concept approximation existing in rough set theory. Approximation spaces are constructed as higher level information granules and are obtained as the result of complex modelling. We present illustrative examples of modelling approximation spaces that include approximation spaces for function approximation, inducing concept approximation, and some other information granule approximations. In modelling of such approximation spaces we use an important assumption that not only objects but also more complex information granules involved in approximations are perceived using only partial information about them.