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Developing a smart Archival Assistant with conversational features and linguistic abilities : the Ask_ArchiLab initiative

Makhlouf Shabou, Basma; Friha, Lamia; Ramli, Wassila
2025
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This article describes Ask_ArchiLab project, a recent project conducted at ArchiLab_Geneva School of Business Administration. The project aims to modernize archival practices using conversational AI. It addresses challenges in digital archiving through a multi-agent system that enables fast, contextual queries. The current focus is on delivering professional archival knowledge via semantic technologies like RDF using advanced RAG techniques. The project fosters international collaboration to enhance access and usability in archival science.

Titre
Developing a smart Archival Assistant with conversational features and linguistic abilities : the Ask_ArchiLab initiative
Auteur(s)/ trice(s)
Makhlouf Shabou, Basma (Haute école de gestion de Genève, HES-SO, Haute Ecole Spécialisée de Suisse Occidentale)
Friha, Lamia (R&D Cell, Research and Information Science, DiSTIC, University of Geneva, Geneva, Switzerland)
Ramli, Wassila (Corporate analytics and Digital project officer Contexa SA, University of Geneva, geneva, Switzerland)
Date
2025-12
Publié dans
Proceedings of the 13th IEEE International Conference on Big Data (IEEE Big Data 2025), 10th Computational Archival Science Workshop
Volume
To be published
Pagination & équivalents
7 p.
Présenté à
13th IEEE International Conference on Big Data (IEEE Big Data 2025), 10th Computational Archival Science (CAS) Workshop, Macau SAR, China, 2025-12-09, 2025-12-09
Mots-clés (libres)
generative AI ; RDF ; Open Linked Data ; GraphRAG ; Agentics ; knowledge engineering ; advanced archival knowledge ; PIAf ; ICA
Type de papier
published full paper
Domaine
Economie et Services
Ecole
HEG - Genève
Institut
CRAG - Centre de Recherche Appliquée en Gestion
Le document apparaît dans
Documents de conférences
Global
Ressource(s) externe(s)
Online version