New Indicators for the Assessment of Linguistic Summaries Considering a Rough Sets Approach

Abstract:

In this work, different approaches to the evaluation of linguistic summaries are analyzed. In the design of the indicators, elements of rough set theory and the neutrosophic theory are combined. Several of the proposed indicators expand the traditional indicators reported in the bibliography. For comparisons, the authors design a set of 29 test cases that represent different equivalence classes of project management decision-making scenarios. The indicators reported in the bibliography are compared with the new ones proposed in the 29 test cases. For each indicator, the authors present different graphs that allow the indicators to compare their advantages and disadvantages. Finally, the authors present the conclusion of this work and future work.

Año de publicación:

2022

Keywords:

• Artificial Intelligent
• Linguistic summaries assessment
• Linguistic data summarization
• project management

Fuente:

scopus