The effect of the linguistic (L-) summarization mined from a given dataset D by a human-
made method M strongly depends on the fuzzy sets constructed to represent the L-words of …

We introduce an approach called PLENARY (exPlaining bLack-box modEls in Natural
lAnguage thRough fuzzY linguistic summaries), which is an explainable classifier based on …

Smartphones enable to collect large data streams about phone calls that, once combined
with Computational Intelligence techniques, bring great potential for improving the …

This work presents a new perspective on how Zadeh's ideas related to fuzzy logic and
computing with words have influenced the crucial issue of information aggregation and have …

Forecasting CO 2 emission is the one of most important issues for the “30⋅ 60” CO 2
emission target in China. Due to unbalanced socio-economic developments of regions in …

Data from National Statistical Institutes is generally considered an important source of
credible evidence for a variety of users. Summarization and dissemination via traditional …

One of the current limitations of fuzzy linguistic descriptions of data is the lack of diversity of
protoforms that can be used to linguistically summarize data. Despite an important effort in …

The novelty of this research is to use linguistically quantified sentences, the so called
linguistic summaries, to improve time series forecasting. The proposed Forecasting with …

Although plenty of techniques such as link prediction, clustering, and position analysis have
been proposed to analyze social and economic networks and patterns of social and …

Diagnosing autism spectrum disorder (ASD) in children poses significant challenges due to
its complex nature and impact on social communication development. While numerous data …