Personal Information
Name: Sandra Schaftner M.Sc.
Room: A13.220.2
Phone: +49 371 531 39319
Email: sandra.schaftner@informatik.tu-chemnitz.de
Publications
Schaftner, S., Gaedke, M. (2026). Deep Semantic Linking of Scientific Knowledge: An Agentic AI Framework for Knowledge Graph Construction. In: Mauri, A., Burgueño, L., Tommasini, R. (eds) Web Engineering. ICWE 2026. Lecture Notes in Computer Science, vol 16625. Springer, Cham. https://doi.org/10.1007/978-3-032-29372-5_22
Sandra Schaftner and Martin Gaedke. 2026. The LOPE Method: Improving Consistent Property Extraction for Scientific Knowledge Graphs Using LLMs. In Companion Proceedings of the ACM Web Conference 2026 (WWW Companion ’26). Association for Computing Machinery, New York, NY, USA, 1001–1008. https://doi.org/10.1145/3774905.3795079
Sandra Schaftner and Martin Gaedke. 2026. ORKG Properties Ontology Consolidated: LLM-Driven Refinement of Crowdsourced Knowledge for Machine-Actionability. In Companion Proceedings of the ACM Web Conference 2026 (WWW Companion ’26). Association for Computing Machinery, New York, NY, USA, 1009–1016. https://doi.org/10.1145/3774905.3795080
Co-Reviewer for Conferences
- WebConf 2026: The ACM Web Conference 2026
Current Project
Current Students
- Pratiksha Gawande: Masterarbeit (2026) “Aligning the Across Federated Knowledge Graph with Standard Vocabularies: An Evaluation of LLM-Based Ontology Matching”.
- Kashfa Sehejat Sezuti: Masterarbeit (2026) “User-Centered Design for the Across eCampus Course Catalog: An Analysis and Prototyping Study Based on State-of-the-Art UX Principles”.
Advised Projects
- Farid Mammadov: Masterarbeit (2026) “Quality Assessment for Federated University Knowledge Graphs Using Machine-Learning-Based Anomaly Detection: A Case Study on the Across Alliance”.
Teaching Activities
- Planspiel (Business Simulation) “Web Engineering”
- Seminar “Web Engineering”