publications
Discover the list of the publications.
Scholarly Wikidata: Population and Exploration of Conference Data in Wikidata using LLMs
Mihindukulasooriya, N., Tiwari, S., Dobriy, D., Nielsen, F. Å., Chhetri, T. R., & Polleres, A. (2025). Alam, M., Rospocher, M., van Erp, M., Hollink, L., & Gesese, G. A. (Eds.). Scholarly wikidata: population and exploration of conference data in wikidata using llms. Knowledge Engineering and Knowledge Management (pp. 243–259). Cham: Springer Nature Switzerland.
Code DOIEnabling privacy-aware interoperable and quality IoT data sharing with context
Chhetri, T. R., Dehury, C. K., Varghese, B., Fensel, A., Srirama, S. N., & DeLong, R. J. (2024). Enabling privacy-aware interoperable and quality iot data sharing with context. Future Generation Computer Systems. URL: https://www.sciencedirect.com/science/article/pii/S0167739X24001109, doi:https://doi.org/10.1016/j.future.2024.03.039
Code DOIEnd-to-End Multimodal Sensor Dataset Collection Framework for Autonomous Vehicles
Gu, J., Lind, A., Chhetri, T. R., Bellone, M., & Sell, R. (2023 , Jul). End-to-end multimodal sensor dataset collection framework for autonomous vehicles. Sensors, 23(15), 6783. URL: http://dx.doi.org/10.3390/s23156783, doi:10.3390/s23156783
Code DOITowards Improving Prediction Accuracy and User-Level Explainability Using Deep Learning and Knowledge Graphs: A Study on Cassava Disease
Chhetri, T. R., Hohenegger, A., Fensel, A., Kasali, M. A., & Adekunle, A. A. (2023). Towards improving prediction accuracy and user-level explainability using deep learning and knowledge graphs: a study on cassava disease. Expert Systems with Applications, 233, 120955. URL: https://www.sciencedirect.com/science/article/pii/S0957417423014574, doi:https://doi.org/10.1016/j.eswa.2023.120955
Code DOIThe smashHitCore ontology for GDPR-compliant sensor data sharing in smart cities
Kurteva, A., Chhetri, T. R., Tauqeer, A., Hilscher, R., Fensel, A., Nagorny, K., … Demidova, E. (2023). The smashhitcore ontology for gdpr-compliant sensor data sharing in smart cities. Sensors. doi:https://doi.org/10.3390/s23136188
DOIQuestion answering over knowledge graphs: a graph-driven approach
Aghaei, S., Masoudi, S., Chhetri, T. R., & Fensel, A. (2022). Question answering over knowledge graphs: a graph-driven approach. 2022 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT) (pp. 296–302). doi:10.1109/WI-IAT55865.2022.00050
DOIOptimising Manufacturing Process with Bayesian Structure Learning and Knowledge Graphs
Chhetri, T. R., Aghaei, S., Fensel, A., Göhner, U., Gül-Ficici, S., & Martinez-Gil, J. (2022). Moreno-Díaz, R., Pichler, F., & Quesada-Arencibia, A. (Eds.). Optimising manufacturing process with bayesian structure learning and knowledge graphs. Computer Aided Systems Theory – EUROCAST 2022 (pp. 594–602). Cham: Springer Nature Switzerland.
Code Video DOIData Protection by Design Tool for Automated GDPR Compliance Verification Based on Semantically Modeled Informed Consent
Chhetri, T. R., Kurteva, A., DeLong, R. J., Hilscher, R., Korte, K., & Fensel, A. (2022). Data protection by design tool for automated gdpr compliance verification based on semantically modeled informed consent. Sensors, 22(7). URL: https://www.mdpi.com/1424-8220/22/7/2763, doi:10.3390/s22072763
Code DOIA Combined System Metrics Approach to Cloud Service Reliability Using Artificial Intelligence (Editor's Choice)
Chhetri, T. R., Dehury, C. K., Lind, A., Srirama, S. N., & Fensel, A. (2022). A combined system metrics approach to cloud service reliability using artificial intelligence. Big Data and Cognitive Computing, 6(1). URL: https://www.mdpi.com/2504-2289/6/1/26, doi:10.3390/bdcc6010026
Code DOIKnowledge Graph Based Hard Drive Failure Prediction
Chhetri, T. R., Kurteva, A., Adigun, J. G., & Fensel, A. (2022 , Jan). Knowledge graph based hard drive failure prediction. Sensors, 22(3), 985. URL: http://dx.doi.org/10.3390/s22030985, doi:10.3390/s22030985
DOITowards Reusable Ontology Alignment for Manufacturing Maintenance
Kainzner, M., Klösch, C., Filipiak, D., Chhetri, Tek Raj, Fensel, A., & Martinez-Gil, J. (2021 , September). Towards reusable ontology alignment for manufacturing maintenance. CEUR workshop proceedings series (Vol-2941). Amsterdam, the Netherlands: SEMANTiCS 2021 EU. URL: http://ceur-ws.org/Vol-2941/paper9.pdf
Code Video DOIConsent through the lens of semantics: State of the art survey and best practices
Kurteva, A., Chhetri, T. R., Pandit, H. J., & Fensel, A. (2021). Consent through the lens of semantics: state of the art survey and best practices. Semantic Web, Preprint, 1-27. Preprint. URL: https://doi.org/10.3233/SW-210438, doi:10.3233/SW-210438
DOIImproving Decision Making Using Semantic Web Technologies
Chhetri, T. R. (2021). Verborgh, R., Dimou, A., Hogan, A., d'Amato, C., Tiddi, I., Bröring, A., … Alam, M. (Eds.). Improving decision making using semantic web technologies. The Semantic Web: ESWC 2021 Satellite Events (pp. 165–175). Cham: Springer International Publishing.
DOIRange Sensor Overview and Blind-Zone Reduction of Autonomous Vehicle Shuttles
Gu, J., & Chhetri, T. R. (2021 , may). Range sensor overview and blind-zone reduction of autonomous vehicle shuttles. IOP Conference Series: Materials Science and Engineering, 1140(1), 012006. URL: https://doi.org/10.1088/1757-899x/1140/1/012006, doi:10.1088/1757-899x/1140/1/012006
DOICCoDaMiC: A framework for Coherent Coordination of Data Migration and Computation platforms
Dehury, C. K., Srirama, S. N., & Chhetri, T. R. (2020). Ccodamic: a framework for coherent coordination of data migration and computation platforms. Future Generation Computer Systems, 109, 1-16. URL: https://www.sciencedirect.com/science/article/pii/S0167739X19330924, doi:https://doi.org/10.1016/j.future.2020.03.029
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