DEVELOPING A HYBRID VECTOR-GRAPH RETRIEVAL SYSTEM FOR ENTITY-PRESERVING AND INSPIRING STORYLINE CREATION OF PRESENTATION SLIDES
Journal
European Conference on Information Systems (ECIS)
Type
conference paper
Date Issued
2025-06-12
Author(s)
Research Team
IWI6
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.
Language
English
Keywords
Overreliance
Presentation Slide Creation
Graph-based Retrieval
Narrative Structuring
HSG Classification
contribution to scientific community
Refereed
Yes
Volume
2025
Pages
16
Event Title
European Conference on Information Systems (ECIS)
Event Location
Amman, Jordan
Event Date
12.06.2025
Subject(s)
Division(s)
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Name
JML_1023.pdf
Size
816.66 KB
Format
Adobe PDF
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