Linguistic Summarization of Processes – a research agenda

Abstract

Linguistic summarization offers novel ways of gaining insight into large amounts of data by extracting their main properties and representing them linguistically. Various linguistic summarization techniques have been proposed for data sets consisting of attribute-value pairs. However, many application domains are characterized by structured and relational data, where explicit relations amongst data elements exist. Process data, in which business activities are ordered sequentially, is one example. Linguistic summarization for such data has been considered only sparsely in the literature. In this paper, we consider the challenges for obtaining linguistic summaries from process data and propose a research agenda.

A Formal Analysis of Generalized Peterson’s Syllogisms Related to Graded Peterson’s Cube

“…Later, these methods were improved in [27] and implemented by Kasprzyk and Zadro żny [28]. Another linguistic summarization of process data was proposed in [29].…”