Logo Lanfrica
  • Accueil
  • Atlas
  • Analyses
  • Documentation
  • Sign in

© 2026 Lanfrica. Tous droits réservés. Tous les droits d'auteur des ressources affichées sur le site Web Lanfrica appartiennent aux détenteurs de droits d'auteur d'origine, sauf indication contraire explicite.

A Conceptual Architecture for Physics-Informed Knowledge Retrieval of the Yoruba Ifá Corpus Using Knowledge Graphs and Graph Neural Networks

Domaine:

natural language processing
Créateur:
Ade
Éditeur:
Elsevier BV
Hôte:
The Yoruba Ifá corpus is one of the oldest and most complete knowledge systems in Africa. For many centuries, it has preserved wisdom about life, health, morality, history, and spirituality through oral tradition. Today, this sacred knowledge faces serious danger: the elders who carry it are passing away, young people are migrating to cities, and the Yoruba language is gradually changing under external pressures. Together, these factors threaten the survival of Ifá knowledge. This study asks a simple but important question: can modern computer science help to preserve and share Ifá knowledge without destroying its deeper meaning? To answer this question, the study proposes a new way of thinking about Ifá knowledge. Rather than treating Ifá verses as ordinary documents in a filing cabinet, it treats them as a living network of connected ideas. Just as a Babaláwo (Ifá priest) never reads a single verse in isolation but connects it to proverbs, rituals, history, and the client’s situation, the proposed computer system connects ideas to one another. The study brings together three modern technologies: Knowledge Graphs, which map the connections between ideas; Graph Neural Networks, which help computers learn from these connections; and physics-informed reasoning, which allows information to flow through the network much as water flows through a system of pipes. This research does not build a working computer program. It does, however, go beyond a purely conceptual sketch: it specifies a concrete technology stack, a formal data schema, a step-by-step retrieval algorithm with a computational complexity analysis, a phased implementation roadmap, and an evaluation framework with measurable success criteria. Together these form a blueprint detailed enough for future researchers to begin building and testing real systems, rather than starting from a blank page. The study is deeply rooted in Yoruba culture. It respects the sacred nature of Ifá and insists that any technology built upon it must serve the tradition rather than replace the Babaláwo.

Visit

doi.org

Tasks

information retrieval

Languages

Yoruba

Licenses

https://creativecommons.org/licenses/by/4.0/

Similaires

deep-sea channel architecture knowledge graph deep-sea channel architecture knowledge graphContextual Graph Attention for Answering Logical Queries over Incomplete Knowledge GraphsTowards Citizen–Expert Knowledge Exchange for Biodiversity Informatics: A Conceptual ArchitectureGracebaytech/Yoruba-Knowledge-and-Cultural-Retrieval-mRAKL: Multilingual Retrieval-Augmented Knowledge Graph Construction for Low-Resourced LanguagesConceptual graph-based knowledge representation for supporting reasoning in African traditional medicine

deep-sea channel architecture knowledge graph deep-sea channel architecture knowledge graph

the data of deep-sea channel architecture knowledge graph for West African Nigeria offshore channel

Contextual Graph Attention for Answering Logical Queries over Incomplete Knowledge Graphs

Recently, several studies have explored methods for using KG embedding to answer logical queries. Th

Towards Citizen–Expert Knowledge Exchange for Biodiversity Informatics: A Conceptual Architecture

This article proposes a conceptual architecture for citizen–expert knowledge exchange in biodiversit

Gracebaytech/Yoruba-Knowledge-and-Cultural-Retrieval-

Development of a Yoruba Linguistic Knowledge Retrieval and Cultural Preservation System Using Retrie

mRAKL: Multilingual Retrieval-Augmented Knowledge Graph Construction for Low-Resourced Languages

Knowledge Graphs represent real-world entities and the relationships between them. Multilingual Know

Conceptual graph-based knowledge representation for supporting reasoning in African traditional medicine

International audience Although African patients use both conventional or modern and