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 …

In this paper we provide a general approach for the concepts and processes related to the
generation of linguistic descriptions of time series. As we will see, this approach consists of …

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

In this paper, we propose a framework for the automatic generation of natural language
descriptions of healthcare processes using quantitative and qualitative data and medical …

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 …

This paper investigates the question of the interpretability of fuzzy linguistic summaries, both
at the sentence level and at the summary level, seen as a set of sentences. The individual …

Summarizing data with linguistic statements is a crucial and topical issue that has been
largely addressed by the soft computing community. The goal of summarization is to …

The completion of missing values is a prevalent problem in many domains of pattern
recognition and signal processing. Analyzing data with incompleteness may lead to a loss of …

In this paper we experimentally assess, from both algorithmic and pragmatic perspectives,
the adequacy of linguistic descriptions of real data generated by two metaheuristics …

In this paper we present a model based on computational intelligence and natural language
generation for the automatic generation of textual summaries from numerical data series …