Comprehensiveness of Linguistic Data Summaries: A Crucial Role of Protoforms

  • Janusz Kacprzyk
  • Sławomir Zadrożny
Part of the Studies in Computational Intelligence book series (SCI, volume 445)


We show first the essence of our approach to linguistic database summaries, equated with linguistically quantified propositions in Zadeh’s sense and mined through the use of a fuzzy querying interface to a database. We recast the problem from the perspective of comprehensiveness of patterns derived by linguistic data summaries. Motivated by Michalski’s [21] seminal approach to the comprehensiveness of data mining and machine learning results in which he advocates the use of natural language, we advocate the use of linguistic summaries which provide a new quality and an exceptional human consistency and comprehensiveness. We illustrate our analysis by two examples related to the linguistic summarization of both static and dynamic data in the area of analysis of innovativeness of companies and of Web server log files.


Fuzzy Logic Association Rule Linguistic Term Data Mining Algorithm Truth Degree 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Systems Research InstitutePolish Academy of SciencesWarsawPoland
  2. 2.Warsaw School of Information TechnologyWarszawaPoland

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