Interval-valued linguistic summaries of databases

The so-called linguistic summaries of databases are the semi-natural language sentences that enable distilling the most relevant information from large numbers of tuples, and present it in the human consistent forms. Recently, the methods of constructing and evaluating linguistic summaries have been based on Zadeh's fuzzy sets, which are used for modeling of the uncertain data. The main aim of the paper is to enhance and generalize the Yager's approach to linguistic summarization of data. This enhancement is based on interval-valued fuzzy sets. The newly presented methods enable handling of fuzzy concepts, whose membership degrees are not given by real values explicitly, but are approximated by intervals in [0,1]. Therefore, the Yager's approach can be viewed as a special case of the method presented in this paper.