Dr. Jorge Martinez-Gil
Details
Dr. Jorge Martinez-Gil is a Spanish-born computer scientist working in the Data & Knowledge Engineering field. He got his PhD in Computer Science from University of Malaga (Spain) in 2010. He has held a number of research positions across some European countries (Austria, Germany, Spain). He currently holds a senior researcher position within the area of Data Analysis Systems from the Software Competence Center Hagenberg (SCCH) in Austria where he is involved in several applied and fundamental research projects related to knowledge-based technologies. Before joining SCCH, he was an acting professor within the Department of Computer Science from the University of Extremadura, Spain.
Dr. Martinez-Gil has published more than 50 peer-reviewed scientific papers, including those published in prestigious journals like SIGMOD Record, Knowledge and Information Systems, Information Systems Frontiers, Knowledge-Based Systems, Knowledge Engineering Review, Cognitive Systems Research, Online Information Review, Journal of Universal Computer Science, Journal of Computer Science & Technology, Artificial Intelligence Review, Journal of Information and Knowledge Management, and so on.
He has been involved in the evaluation of many scientific manuscripts in academic journals (Knowledge and Information Systems, Knowledge Based Systems, Expert Systems with Applications, Artificial Intelligence Review, and so on), evaluation of research project proposals (FP7 FET, H2020 Flagship, German BMBF, Belgish FNRS, Polish NBCR, etc.), startup mentoring (Spain and Serbia), and creation of study programs in ICT related fields (Spain).
Publikationen
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2024
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Source Code Clone Detection Using Unsupervised Similarity Measures
Martinez-Gil, J. (2024). Source Code Clone Detection Using Unsupervised Similarity Measures. Lecture Notes in Business Information Processing, 21–37.
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2023
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Examining the Adoption of Knowledge Graphs in the Manufacturing Industry: A Comprehensive Review
Martinez-Gil, J., Hoch, T., Pichler, M., Heinzl, B., Moser, B., Kurniawan, K., Kiesling, E., & Krause, F. (2023). Examining the Adoption of Knowledge Graphs in the Manufacturing Industry: A Comprehensive Review. Artificial Intelligence in Manufacturing, 55–70.
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Leveraging Semantic Representations via Knowledge Graph Embeddings
Krause, F., Kurniawan, K., Kiesling, E., Martinez-Gil, J., Hoch, T., Pichler, M., Heinzl, B., & Moser, B. (2023). Leveraging Semantic Representations via Knowledge Graph Embeddings. Artificial Intelligence in Manufacturing, 71–85.
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Multi-Stakeholder Perspective on Human-AI Collaboration in Industry 5.0
Hoch, T., Martinez-Gil, J., Pichler, M., Silvina, A., Heinzl, B., Moser, B., Eleftheriou, D., Estrada-Lugo, H. D., & Leva, M. C. (2023). Multi-Stakeholder Perspective on Human-AI Collaboration in Industry 5.0. Artificial Intelligence in Manufacturing, 407–421.
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A Survey on Legal Question Answering Systems
Martinez-Gil, J. (2023). A survey on legal question–answering systems. Computer Science Review, 48, 100552.
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Transfer Learning for Semantic Similarity Measures based on Symbolic Regression
Martinez-Gil, J., & Chaves-Gonzalez, J. M. (2023). Transfer learning for semantic similarity measures based on symbolic regression. Journal of Intelligent & Fuzzy Systems, 45(1), 37–49.
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Neurofuzzy Semantic Similarity Measurement
Martinez-Gil, J., Mokadem, R., Küng, J., & Hameurlain, A. (2023). Neurofuzzy semantic similarity measurement. Data & Knowledge Engineering, 145, 102155.
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Optimising Manufacturing Process with Bayesian Learning and Knowledge Graphs
Chhetri, T. R., Aghaei, S., Fensel, A., Göhner, U., Gül-Ficici, S., & Martinez-Gil, J. (2022). Optimising Manufacturing Process with Bayesian Structure Learning and Knowledge Graphs. Lecture Notes in Computer Science, 594–602.
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Representing Technical Standards as Knowledge Graph to Guide the Design of Industrial Systems
Illescas, J., Buchgeher, G., Ehrlinger, L., Gabauer, D., & Martinez-Gil, J. (2022). Representing Technical Standards as Knowledge Graph to Guide the Design of Industrial Systems. Lecture Notes in Computer Science, 603–610.
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Optimizing Readability Using Genetic Algorithms
Martinez-Gil, J. (2024). Optimizing readability using genetic algorithms. Knowledge-Based Systems, 284, 111273.
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2022
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A Comparative Study of Ensemble Techniques Based on Genetic Programming: A Case Study in Semantic Similarity Assessment
Martinez-Gil, J. (2022). A Comparative Study of Ensemble Techniques Based on Genetic Programming: A Case Study in Semantic Similarity Assessment. International Journal of Software Engineering and Knowledge Engineering, 33(02), 289–312.
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Multi-Cloud Query Optimisation with Accurate and Efficient Quoting
Wojtowicz, D. T., Yin, S., Martinez-Gil, J., Morvan, F., & Hameurlain, A. (2022). Multi-Cloud Query Optimisation with Accurate and Efficient Quoting. 2022 IEEE International Conference on Big Data (Big Data).
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A Digital Platform to Facilitate the Resilience of Rural Territories
Martinez-Gil, J., Pichler, M., Lentini, G., Mazzeschi, V., Doukhan, G., & Belet, C. (2022). A Digital Platform to Facilitate the Resilience of Rural Territories. Journal of Information & Knowledge Management, 21(03).
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Sustainable semantic similarity assessment
Martinez-Gil, J., & Chaves-Gonzalez, J. M. (2022). Sustainable semantic similarity assessment. Journal of Intelligent & Fuzzy Systems, 43(5), 6163–6174.
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Database and Expert Systems Applications - DEXA 2022 Workshops, 33rd International Conference, DEXA 2022, Vienna, Austria, August 22–24, 2022
Kotsis, G., Tjoa, A. M., Khalil, I., Moser, B., Taudes, A., Mashkoor, A., Sametinger, J., Martinez-Gil, J., Sobieczky, F., Fischer, L., Ramler, R., Khan, M., & Czech, G. (Eds.). (2022). Database and Expert Systems Applications - DEXA 2022 Workshops. Communications in Computer and Information Science.
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Matching Large Biomedical Ontologies Using Symbolic Regression -Extended Version-
Martinez-Gil, J., Yin, S., Kung, J., & Morvan, F. (2022). Matching Large Biomedical Ontologies Using Symbolic Regression Using Symbolic Regression. Journal of Data Intelligence, 3(3), 316–332.
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Admission Certification for Digital Pilots in Public Traffic
Nessler, B., Fischer, L., Martinez-Gil, J., Holom, R.-M., Bosa, K., Kastner, K.-H., Tatschl-Unterberger, E., Watzinger, H., Weissenböck, J., Doms, T., & Schwald, C. (2022) Admission Certification for Digital Pilots in Public Traffic. IJCAI Workshop AI4AD
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Special Issue on Machine Learning and Knowledge Graphs
Alam, M., Fensel, A., Martinez-Gil, J., Moser, B., Recupero, D. R., & Sack, H. (2022). Special Issue on Machine Learning and Knowledge Graphs. Future Generation Computer Systems, 129, 50–53.
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Root Cause Analysis in the Industrial Domain using Knowledge Graphs: A Case Study on Power Transformers
Martinez-Gil, J., Buchgeher, G., Gabauer, D., Freudenthaler, B., Filipiak, D., & Fensel, A. (2022). Root Cause Analysis in the Industrial Domain using Knowledge Graphs: A Case Study on Power Transformers. Procedia Computer Science, 200, 944–953.
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Interpretable ontology meta-matching in the biomedical domain using Mamdani fuzzy inference
Martinez-Gil, J., & Chaves-Gonzalez, J. M. (2022). Interpretable ontology meta-matching in the biomedical domain using Mamdani fuzzy inference. Expert Systems with Applications, 188, 116025.
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2021
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Matching Large Biomedical Ontologies Using Symbolic Regression
Martinez-Gil, J., Yin, S., Küng, J., & Morvan, F. (2021). Matching Large Biomedical Ontologies Using Symbolic Regression. The 23rd International Conference on Information Integration and Web Intelligence.
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Semantic similarity controllers: On the trade-off between accuracy and interpretability
Martinez-Gil, J., & Chaves-Gonzalez, J. M. (2021). Semantic similarity controllers: On the trade-off between accuracy and interpretability. Knowledge-Based Systems, 234, 107609.
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Indirect Mass Flow Estimation based on Power Measurements of Conveyor Belts in Mineral Processing Applications
Heinzl, B., Martinez-Gil, J., Himmelbauer, J., Rosbory, M., Hinterdorfer, C., & Hinterreiter, C. (2021). Indirect Mass Flow Estimation based on Power Measurements of Conveyor Belts in Mineral Processing Applications. 2021 IEEE 19th International Conference on Industrial Informatics (INDIN).
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Deep Learning Rule for Efficient ChangepointDetection in the Presence of non-linear Trends
Mahmoud, S., Martinez-Gil, J., Praher, P., Freudenthaler, B., & Girkinger, A. (2021). Deep Learning Rule for Efficient Changepoint Detection in the Presence of Non-Linear Trends. Database and Expert Systems Applications - DEXA 2021 Workshops, 184–191.
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Interpretable entity meta-alignment in knowledge graphs using penalized regression: a case study in the biomedical domain
Martinez-Gil, J., Mokadem, R., Morvan, F., Küng, J., & Hameurlain, A. (2021). Interpretable entity meta-alignment in knowledge graphs using penalized regression: a case study in the biomedical domain. Progress in Artificial Intelligence, 11(1), 93–104.
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Knowledge Graphs in Manufacturing and Production: A Systematic Literature Review
Buchgeher, G., Gabauer, D., Martinez-Gil, J., & Ehrlinger, L. (2021) Knowledge Graphs in Manufacturing and Production: A Systematic Literature Review. IEEE Access, vol. 9, pp. 55537-55554.
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Decay-parameter Diagnosis in Industrial Domains by Robustness through Isotonic Regression
Mahmoud, S., Sobieczky, F., Martinez-Gil, J., Praher, P., & Freudenthaler, B. (2021). Decay-parameter Diagnosis in Industrial Domains by Robustness through Isotonic Regression. Procedia Computer Science, 180, 466–475.
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A Novel Neurofuzzy Approach for Semantic Similarity Measurement
Martinez-Gil, J., Mokadem, R., Küng, J., & Hameurlain, A. (2021). A Novel Neurofuzzy Approach for Semantic Similarity Measurement. Lecture Notes in Computer Science, 192–203.
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Towards Reusable Ontology Alignment for Manufacturing Maintenance
Kainzner, M., Klösch, C., Filipiak, D., Chhetri, T. R., Fensel, A., & Martinez-Gil, J. (2021) Towards Reusable Ontology Alignment for Manufacturing Maintenance. SEMANTiCS.
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2020
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A novel method based on symbolic regression for interpretable semantic similarity measurement
Martinez-Gil, J., & Chaves-Gonzalez, J. M. (2020). A novel method based on symbolic regression for interpretable semantic similarity measurement. Expert Systems with Applications, 160, 113663.
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Database and Expert Systems Applications DEXA 2020 International Workshops BIOKDD, IWCFS and MLKgraphs, Bratislava, Slovakia, September 14–17, 2020, Proceedings
Kotsis, G., Tjoa, A. M., Khalil, I., Fischer, L., Moser, B., Mashkoor, A., Sametinger, J., Fensel, A., & Martinez-Gil, J. (Eds.). (2020). Database and Expert Systems Applications. Communications in Computer and Information Science.
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Framework for data analysis in the context of the smart villages
Martinez-Gil, J., Pichler, M., Turkanović, M., Beranič, T., Gradišnik, M., Lentini, G., Lué, A., Vitale, A. C., Doukhan, G., & Belet, C. (2020). Framework for Data Analysis in the Context of the Smart Villages. Lecture Notes in Computer Science, 31–45.
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General model for tracking manufacturing products using graph databases
Martinez-Gil, J., Stumptner, R., Lettner, C., Pichler, M., Mahmoud, S., Praher, P., & Freudenthaler, B. (2020). General Model for Tracking Manufacturing Products Using Graph Databases. Data-Driven Process Discovery and Analysis, 86–100.
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2019
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Optimal selection of training courses for unemployed people based on stable marriage model
Martinez-Gil, J., & Freudenthaler, B. (2019). Optimal Selection of Training Courses for Unemployed People based on Stable Marriage Model. Proceedings of the 21st International Conference on Information Integration and Web-Based Applications & Services.
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A general framework for multiple choice question answering based on mutual information and reinforced co-occurrence
Martinez-Gil, J., Freudenthaler, B., & Tjoa, A. M. (2019). A General Framework for Multiple Choice Question Answering Based on Mutual Information and Reinforced Co-occurrence. Lecture Notes in Computer Science, 91–110.
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Automatic design of semantic similarity controllers based on fuzzy logics
Martinez-Gil, J., & Chaves-Gonzalez, J. M. (2019). Automatic design of semantic similarity controllers based on fuzzy logics. Expert Systems with Applications, 131, 45–59.
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Facilitating the digital transformation of villages
Beranič, T., Zamuda, A., Brezočnik, L., Lentini, G., Polettini, F., Lue, A., Colorni Vitale, A., Martinez-Gil, J., Pichler, M., & Turkanović, M. (2019) Facilitating the digital transformation of villages. Proceedings of the Central European Conference on Information and Intelligent Systems (CECIIS 2019), pages 281-288, October 2019.
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Design and implementation of a graph-based solution for tracking manufacturing products
Martinez-Gil, J., Stumpner, R., Lettner, C., Pichler, M., & Fragner, W. (2019). Design and Implementation of a Graph-Based Solution for Tracking Manufacturing Products. New Trends in Databases and Information Systems, 417–423.
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Framework for assessing the smartness maturity level of villages
Martinez-Gil, J., Pichler, M., Beranič, T., Brezočnik, L., Turkanović, M., Lentini, G., Polettini, F., Lué, A., Vitale, A. C., Doukhan, G., & Belet, C. (2019). Framework for Assessing the Smartness Maturity Level of Villages. New Trends in Databases and Information Systems, 501–512.
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An efficient design for a multi-objective evolutionary algorithm to generate DNA libraries suitable for computation
Chaves-González, J. M., & Martínez-Gil, J. (2018). An Efficient Design for a Multi-objective Evolutionary Algorithm to Generate DNA Libraries Suitable for Computation. Interdisciplinary Sciences: Computational Life Sciences, 11(3), 542–558.
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Multiple choice question answering in the legal domain using reinforced co-occurrence
Martinez-Gil, J., Freudenthaler, B., & Tjoa, A. M. (2019). Multiple Choice Question Answering in the Legal Domain Using Reinforced Co-occurrence. Database and Expert Systems Applications, 138–148.
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Towards a data-driven approach for fraud detection in the social insurance field: A case study in Upper Austria
Himmelbauer, J., Martinez-Gil, J., Ksen, M., Linner, K., & Plakolm, S. (2019). Towards a Data-Driven Approach for Fraud Detection in the Social Insurance Field: A Case Study in Upper Austria. Lecture Notes in Computer Science, 70–84.
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A novel approach for learning how to automatically match job offers and candidate profiles
Martinez-Gil, J., Paoletti, A. L., & Pichler, M. (2019). A Novel Approach for Learning How to Automatically Match Job Offers and Candidate Profiles. Information Systems Frontiers, 22(6), 1265–1274.
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Semantic similarity aggregators for very short textual expressions: A case study on landmarks and points of interest
Martinez-Gil, J. (2019). Semantic similarity aggregators for very short textual expressions: a case study on landmarks and points of interest. Journal of Intelligent Information Systems, 53(2), 361–380.