Language-Agnostic Knowledge Representation for a Truly Multilingual Semantic Web

Sarika Jain and Anastasiia Kysliak
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Sarika Jain: National Institute of Technology, Kurukshetra, India
Anastasiia Kysliak: Georg-August-Universität, Göttingen, Germany

International Journal of Information System Modeling and Design (IJISMD), 2022, vol. 13, issue 1, 1-21

Abstract: As the Internet users’ communities and the information on the web are increasing exponentially, that too associated with a wide range of different cultures and languages; meaningful search in a multilingual setting is required. It is crucial to develop a simple to use, granular, and adaptable knowledge representation system that could constitute the core of Semantic Web. It should be well-prepared for multilingual and multicultural settings by virtue of internationalizing the code. In this work, a model for ontology-based language-agnostic Semantic Web application architecture is offered which is independent of today’s heterogeneous encoding of language resources and provides smooth exploitation. The suggested system architecture enables a quick and meaningful search for information independent of the end user’s preferred language and cultural conventions, an easy extension of the application with new information, as well as its easy localization for new language contexts. The model’s usability is proven by a prototype application simulation in the domain of Indian biodiversity.

Date: 2022
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