Bipolar linguistic summaries: A novel fuzzy querying driven approach

The concept of bipolar linguistic summaries of data, introduced by Dziedzic, Zadrożny and Kacprzyk [1], is further developed. These summaries are meant as an extension of the “classical” linguistic summarization [2], [3], a human-consistent data mining technique, making it possible to express more complex patterns present in data. The focus of the paper is to provide a deeper insight into the very concept of these summaries and illustrating them with some practical examples. Results of preliminary computational experiments are included.