Mining pure linguistic associations from numerical data

New results on redundancies of fuzzy/linguistic IF-THEN rules

“…In [19], the authors have shown that this exploration may be done with help of linguistic associations mining, particularly, with a fuzzy variant of the GUHA method originally proposed by P. Hájek [20]. However, the fuzzy GUHA method [10,21] necessarily produces lots of approved yet redundant implicative associations that may be viewed as fuzzy IF-THEN rules. Obviously, an efficient method that significantly decreases the number of fuzzy rules in the generated linguistic descriptions but without any influence on their behavior, is highly desirable.…”

“…But, for our so-called linguistic approach originated by V. Novák [6] these questions were not adequately investigated. We were able to successfully apply our linguistic approach in analysis and forecasting of time series [7,8], decision making [9] or data mining [10]. We found out that this approach has distinct advantages in good interpretability, great robustness, foundations in a strong formal logical system etc.…”

Fuzzy region assignment for visual tracking

“…A more detailed analysis of approaches to data association based on this paradigm is presented in the next section. In the same way as this work, a research line in data mining extends the semantics of associations to deal with uncertainty and imprecision, including knowledge representation with generalized concepts and linguistic expressions (Novak et al 2008).…”

“…It differs from the general association problem in data mining, which refers to the search of semantic linkages between attributes of data instances, such as the relations discovered in basket analysis. The a priori algorithm (Agrawal 1996) is one of the original association methods in data mining, from which many efforts have continued to develop association methods with capabilities to generalize with uncertainty conditions and integrate high-level knowledge (Novak et al 2008).…”

Some dependencies among attributes given by fuzzy confirmation measures

“…In a recent paper [14] a theoretical background and also mining of associations that are expressible in natural language (i.e. associations of the form "IF the area of the base of a cylinder is big AND the height of this cylinder is also big THEN the volume of this cylinder is big.")…”