The paper is focused on self-contained linguistic problems based on text corpora. We argue that corpus-based problems differ from traditional linguistic problems because they make it possible to represent language variation. Furthermore, they often require basic statistical thinking from the students. The practical value of using data obtained from text corpora for teaching linguistics through ...

The intuitionistic linguistic set (ILS) is an extension of linguisitc variable. To overcome the drawback of using single real number to represent membership degree and non-membership degree for ILS, the concept of interval-valued intuitionistic linguistic set (IVILS) is introduced through representing the membership degree and non-membership degree with intervals for ILS in this paper. The oper...

Uncertainty in real world decision making problems not always has probabilistic nature, in such cases the use of linguistic information to model and manage such an uncertainty has given good results. The adoption of linguistic information implies the accomplishment of processes of computing with words to solve linguistic decision making problems. In the specialized literature, several computati...

Most group decision making (GDM) problems based on linguistic approaches use symmetrically and uniformly distributed linguistic term sets to express experts’ opinions. However, there exist problems whose assessments need to be represented by means of unbalanced linguistic term sets, i.e. using term sets that are not uniformly and symmetrically distributed. The aim of this paper is to present a ...

In Group Decision Making (GDM) the automatic consensus models are guided by different consensus measures which usually are obtained by aggregating similarities observed among experts’ opinions. Most GDM problems based on linguistic approaches use symmetrically and uniformly distributed linguistic term sets to express experts’ opinions. However, there exist problems whose assessments need to be ...