Department of Computer Science Technische Universität München
Room FMI 01.12.057 Office hours: by appointment |
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Student offers:
Open HiWi Position
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Mr. Schopf joined the chair of Software Engineering for Business Information Systems at the Technical University of Munich in September 2020. He holds a master's degree in Information Engineering and Management from Karlsruhe Institute of Technology and wrote his master's thesis at MHP - A Porsche Company about defending adversarial attacks on deep neural networks for autonomous driving by randomization and anomaly detection. He acquired his bachelor's degree in Information Systems from a joint program of the Universities of Hohenheim and Stuttgart. During his studies he also gained work experience as Data Science Intern at Daimler and as student research assistant at Karlsruhe Institute of Technology. |
As one of the organizers, Tim Schopf was responsible for hackaTUM, the official annual TUM hackathon hosted by the Department of Informatics since 2016. Over the last years, it has become one of the biggest hackathons in the EU with over 1700 applications and 900 participants in the last event. If you are interested in sponsoring the event, contact hackatum.in@tum.de. Further information can be found at https://hack.tum.de |
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Natural Language Processing Knowledge Graph (NLP-KG) The NLP knowledge graph is an approach to tackle the information overload challenge of researchers. It aims to help researchers in obtaining an overview of NLP-related topics and find relevant papers more efficiently. More here... |
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CreateData4AI (CD4AI) Estimated zettabytes of data are generated every day, with about 80% of this data being unannotated, unstructured text. An as-of-yet unsolved problem with this type of data is how to make it useful for AI applications. Manual annotation of the data can be very precise and incorporate domain-specific knowledge, but it is costly, inefficient, and not scalable. The so-called "80/20 rule" refers to the fact that data scientists often spend up to 80% of their time sorting, cleaning, and otherwise preparing datasets. This project aims to develop a novel hybrid framework that helps domain experts annotate text using Natural Language Processing algorithms, reducing the process to a fraction of the time. More here... |
Technology Scouting as a Service (TSaaS) Due to the quantity and complexity of data (Big Data), the classical information gathering of engineers, for the search for technologies to solve problems in mechanical and plant engineering, no longer meets the requirements of a modern information society. This project aims to research AI-based processes that offer engineers a completely new possibility to find tailor-made solutions for their problems. For this purpose, natural language processing algorithms will be developed that semantically analyze large amounts of text, extract essential information and transfer it into an information model (knowledge graph) in order to capture and link problems and technologies. By means of matching, solutions for a wide range of problems can then be generated by engineers at the push of a button. More here...
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Knowledge4Retail (K4R) The sebis chair is part of the project "Knowledge4Retail", which is a winning project of the "Künstliche Intelligenz als Treiber für volkswirtschaftlich relevante Ökosysteme" programme and thus funded by the Bundesministerium für Wirtschaft und Energie (BMWi). The goal of Knowledge4Retail is to advance the digitization of retail by developing a data platform that enables the combination of online and stationary retail, serves strategic marketing and makes digital solutions available for individual customer service using a semantic digital twin. More here... |
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Research Institution Knowledge Graph (RIKG) Given that scientific knowledge usually is available in large quantities as unstructured texts, it is very difficult for researchers to obtain an overview of research fields or scientific domains. Similarly, it is difficult for researchers to gain insight into topics being researched at research institutions. Information about conducted research often only exists in unstructured texts on homepages or intranet pages. In addition, the websites are usually designed according to organizational structures of research institutions rather than a logical structure based on research areas. Therefore, a research area based navigation through the instutution websites is hardly possible. This makes exploration and navigation of topics being researched in an institution very difficult for external as well as for internal users. Structuring the scientific knowledge of research institutions and linking semantically related scientific domains offers researchers the potential for enhanced exploration of research areas. More here ... |
Term | Level | Title | Type | Role |
SS 24 | Master | IN2106, IN7106: SEBA Lab Course (NLP) | Lab Course | Advisor |
SS 24 | Master | IN2087: Software Engineering for Business Applications - Web Applications Engineering | Lab Course | Advisor |
SS 24 | Master | IN2107, IN4816: Natural Language Processing - Methods and Applications | Seminar | Advisor |
WS 23/24 | Master | IN2106, IN7106: SEBA Lab Course | Lab Course | Advisor |
WS 23/24 | Bachelor & Master | IN2235: Software Engineering in der industriellen Praxis | Lecture | Organizer |
SS 23 | Master | IN2106, IN7106: SEBA Lab Course (NLP) | Lab Course | Advisor |
SS 23 | Master | IN2107, IN4816: Natural Language Processing - Methods and Applications | Seminar | Advisor |
SS 23 | Master | IN2087: Software Engineering for Business Applications - Web Applications Engineering | Lab Course | Advisor |
WS 22/23 | Master | IN2106, IN7106: SEBA Lab Course | Lab Course | Advisor |
WS 22/23 | Bachelor & Master | IN2235: Software Engineering in der industriellen Praxis | Lecture | Organizer |
WS 22/23 | Master | TUM-DI-LAB | Lab Course | Advisor |
SS 22 | Master | IN2107, IN4816: Natural Language Processing - Methods and Applications | Seminar | Advisor |
SS 22 | Master |
IN2087: Software Engineering for Business Applications - Web Applications Engineering |
Lab Course | Advisor |
WS 21/22 | Master |
IN2106, IN7106: SEBA Lab Course |
Lab Course | Advisor |
WS 21/22 | Bachelor & Master | Lecture | Organizer | |
SS 21 | Master |
IN2087: Software Engineering for Business Applications - Web Applications Engineering |
Lab Course | Advisor |
WS 20/21 | Bachelor & Master | IN2235: Software Engineering in der industriellen Praxis | Lecture | Advisor |
WS 20/21 | Master | IN2106, IN7106: SEBA Lab Course | Lab Course | Advisor |
2024 | |
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[PDF] |
Schopf, Tim; Blatzheim, Alexander; Machner, Nektarios; Matthes, Florian Efficient Few-shot Learning for Multi-label Classification of Scientific Documents with Many Classes, Proceedings of the 7th International Conference on Natural Language and Speech Processing (ICNLSP 2024), pages 186–198, Trento. Association for Computational Linguistics. |
[PDF] |
Meisenbacher, Stephen; Schopf, Tim; Yan, Weixin; Holl, Patrick; Matthes, Florian An Improved Method for Class-specific Keyword Extraction: A Case Study in the German Business Registry, Proceedings of the 20th Conference on Natural Language Processing (KONVENS 2024), pages 159–165, Vienna, Austria. Association for Computational Linguistics. |
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Schopf, Tim; Matthes, Florian NLP-KG: A System for Exploratory Search of Scientific Literature in Natural Language Processing, Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 3: System Demonstrations), pages 127–135, Bangkok, Thailand. Association for Computational Linguistics. |
2023 | |
[PDF] |
Schopf, Tim; Machner, Nektarios; Matthes, Florian A Knowledge Graph Approach for Exploratory Search in Research Institutions, Proceedings of the 15th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - KMIS, Rome, Italy, 2023 |
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Schopf, Tim; Arabi, Karim; Matthes, Florian Exploring the Landscape of Natural Language Processing Research, In Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing (RANLP 23), Varna, Bulgaria, 2023 |
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Schopf, Tim; Gerber, Emanuel; Ostendorff, Malte; Matthes, Florian AspectCSE: Sentence Embeddings for Aspect-based Semantic Textual Similarity using Contrastive Learning and Structured Knowledge, In Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing (RANLP 23), Varna, Bulgaria, 2023 |
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Schopf, Tim; Schneider, Dennis; Matthes, Florian Efficient Domain Adaptation of Sentence Embeddings Using Adapters, In Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing (RANLP 23), Varna, Bulgaria, 2023 |
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Schopf, Tim; Braun, Daniel; Matthes, Florian Semantic Label Representations with Lbl2Vec: A Similarity-Based Approach for Unsupervised Text Classification, In: Marchiori, M., Domínguez Mayo, F.J., Filipe, J. (eds) Web Information Systems and Technologies. WEBIST WEBIST 2020 2021. Lecture Notes in Business Information Processing, vol 469. Springer, Cham. |
2022 | |
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Schopf, Tim; Braun, Daniel; Matthes, Florian Evaluating Unsupervised Text Classification: Zero-shot and Similarity-based Approaches, In 2022 6th International Conference on Natural Language Processing and Information Retrieval (NLPIR), Bangkok, Thailand, 2022 |
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Schopf, Tim; Klimek, Simon; Matthes, Florian PatternRank: Leveraging Pretrained Language Models and Part of Speech for Unsupervised Keyphrase Extraction, In Proceedings of the 14th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - KDIR (IC3K 2022), Valletta, Malta, 2022 |
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Schneider Phillip; Schopf, Tim; Vladika, Juraj; Galkin, Mikhail; Simperl, Elena; Matthes, Florian A Decade of Knowledge Graphs in Natural Language Processing: A Survey, In Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing (AACL-IJCNLP 2022), Online, 2022 |
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Schopf, Tim; Dresse, Kilian; Matthes, Florian Towards AI Platforms for Stationary Retail, 5th International Conference on Artificial Intelligence for Industries (AI4I), Laguna Hills, USA, 2022 |
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Schopf, Tim; Weinberger, Peter; Kinkeldei, Thomas; Matthes, Florian Towards Bilingual Word Embedding Models for Engineering, MSIE 2022, 4th International Conference on Management Science and Industrial Engineering, Chiang Mai, Thailand, 2022 |
2021 | |
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Schopf, Tim; Braun, Daniel; Matthes, Florian Lbl2Vec: An Embedding-Based Approach for Unsupervised Document Retrieval on Predefined Topics, In Proceedings of the 17th International Conference on Web Information Systems and Technologies, Online, 2021 |
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Braun, Daniel; Klymenko, Oleksandra; Schopf, Tim; Akan, Kaan; Matthes, Florian The Language of Engineering: Training a Domain-Specific Word Embedding Model for Engineering, MSIE 2021: 3rd International Conference on Management Science and Industrial Engineering, Osaka, Japan, 2021 |
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