Alexander Meier
Last Name
Meier
First name
Alexander
Email
alexander.meier@unisg.ch
5 results
Now showing 1 - 5 of 5
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Item type:Publication, DEVELOPING A HYBRID VECTOR-GRAPH RETRIEVAL SYSTEM FOR ENTITY-PRESERVING AND INSPIRING STORYLINE CREATION OF PRESENTATION SLIDES(2025-06-12); ; 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.Type:conference paperJournal:European Conference on Information Systems (ECIS)Volume:2025 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, BLOCKCHAIN IN CONTINUING EDUCATION – TAXONOMY FOR A NEXT-GENERATION TEACHING PLATFORM(2025) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, An AI Approach for Predicting Audience Reach of Presentation Slides(2024-06-16); ; There is a near overflow of presentation slides on digital platforms, such as SlideShare.net, with 40 million. This presents a challenge in assessing their projected impact due to its high complexity and required expertise. We propose a novel approach using machine learning techniques to predict presentation slide audience reach. We crawled a unique dataset of over 8000 slides and extracted relevant attributes. A model was trained where we are the first to employ both numerical and textual inputs. Initial results with an R² value of 0.579 suggest that the audience reach of presentation slides can be automatically evaluated. Our findings contribute to the current understanding of the assessment of online documents, introducing possibilities for further research, such as focusing on domain-specific applications and incorporating them as tools for decision support in content management systems on sharing platforms.Type:conference paper - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Towards Assisted Excellence: Designing an AI-Based System for Presentation Slide Evaluation(2024-06); ; Creating and disseminating high-quality presentation slides have be come a foundation for effective communication in educational, corporate, and scientific domains. This study addresses the challenge of enhancing the quality of user-generated presentation content amidst the vast quantities of existing re sources. The study is concerned with an ongoing design science research project that focuses on constructing a nascent design theory for a novel AI-based slide evaluation support system (SESS) that aims to assist users, particularly educators, create high-quality presentation slides. The proposed concept leverages recent developments in Generative Artificial Intelligence (genAI) to analyze multi modal user-generated content. Drawing on signaling theory, user-generated online reviews, and expert interviews, this research aims to contribute to deline ating the capabilities of artificial intelligence in digital content evaluation, spe cifically in assisting users to improve the quality of their presentation slides. For practitioners, we offer a set of generalized design principles and design features for the implementation in the development of an AI-based SESS.Type:conference paper - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Beyond Trial and Error: Strategic Assessment of Decentralized Identity in US Healthcare(2024-12); ;