Developing a Multidisciplinary Expert System in Ethnonymics

Expert systems (ESs) are urgently needed to complete complicated scientific problems that are impossible for human experts to complete alone. The identification of the origins of 22 Oghuz ethnonyms (names of tribes) on M. Kashgari’s list is a scientific challenge. A multidisciplinary approach to the etymological study of ethnonyms was not considered by the authors of the existing etymologies for one of the 22 ethnonyms included in this study as the sample. They did not present any Historical, Geographical, or other outside Linguistics facts to confirm their hypotheses. The development of the multidisciplinary ES is presented in this research as the best solution to this issue. The ES comprises two linked parts: the Rule-based Sub-ES to develop etymons-sources for 22 target ethnonyms and the Fuzzy Sub-ES to estimate etymons. It gathers and processes expert information from interdisciplinary sciences in addition to linguistics, taking advantage of AI techniques. The Rule-based Sub-ES was developed using Java and Prolog programming languages with jpl.jar library. The Fuzzy Sub-ES was developed using Java programming languages with jFuzzyLogic.jar library. The results of the etymologization of the sample ethnonym suggested by ES were compared with the solutions suggested by the human - authors. In contrast to them, the hypothetical etymon suggested by ES has non-linguistic facts and is hence close to the genuine etymon. The ES can be modified further for the etymologization of ethnonyms of other origins. The application can be used by ethnonymicians.