Journal article

DEVELOPING A HYBRID VECTOR-GRAPH RETRIEVAL SYSTEM FOR ENTITY-PRESERVING AND INSPIRING STORYLINE CREATION OF PRESENTATION SLIDES



Publication Details
Authors:
Meier, A.; Rietsche, R.; Li, M.

Publication year:
2025
Journal:
European Conference on Information Systems
Pages range :
16
Journal acronym:
ECIS
Volume number:
2025
Languages:
English


Abstract

Effective presentation slide creation is crucial for impactful communication, yet fully automating this task with AI is insufficient. Hybrid human-AI solutions often perform worse than pure AI or human creation due to overreliance on AI. To address this, we develop design principles for configuring human-AI hybrid systems in complex knowledge tasks using a design science research approach. Our prototype, NarrativeNet Weaver, leverages an underutilized corpus of existing presentation slides, applying generative AI advances in hybrid dense embedding and graph-based retrieval techniques. Evaluated through 15 think-aloud sessions and 73 user trials, users with NarrativeNet Weaver exhibit greater engagement and achieve equal or improved slide quality compared to those using a ChatGPT-based chatbot with a vector database. We contribute design knowledge for human-AI systems for complex multimodal content and offer a new approach to retrieving and visualizing existing slides, enhancing the utilization of valuable but underused resources.



Keywords
Graph-based Retrieval, Narrative Structuring, Overreliance, Presentation Slide Creation

Last updated on 2025-20-06 at 09:02