Modelling the Thematic Space of Article Proximity using the Fuzzy Approach

Abstract:

Comparing the scientific achievements of researchers is necessary for many purposes, for example, to estimate the achievements of institutions or researchers in order to prepare rankings. One way to do this comparison is to evaluate their publications. Instead of reading all articles, we can compare their keywords, citations of selected articles or publications referenced by the selected publications. We therefore propose two factors to reach the chosen one with a set of other publications. One measure is based on commonly used keywords, while the other takes articles that the selected person cites or are cited by. We apply these factors to create a thematic proximity space, showing some distance from the chosen publication. Moreover, we define a type of Takagi-Sugeno fuzzy inference system for the publications' classifcation.