Work

Developing a Hybrid Vector-graph Retrieval System for Entity-preserving and Inspiring Storyline Creation of Presentation Slides

Year: 2025

Type: article

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.

Source: Journal of the Association for Information Systems

Authors: Meier, Alexander, Li, Mahei Manhai, Rietsche, Roman

Institutions: University of St.Gallen, Bern University of Applied Sciences

Language: English

Topic: Recommender Systems and Techniques

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

Open Access status: green

Funder: Innosuisse - Schweizerische Agentur für Innovationsförderung

Award: G8503654337

OpenAlex ID: W7046641981