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Tim Schopf
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2020 – today
- 2024
- [c13]Stephen Meisenbacher, Tim Schopf, Weixin Yan, Patrick Holl, Florian Matthes:
An Improved Method for Class-specific Keyword Extraction: A Case Study in the German Business Registry. BBBBBBBBBB 2024: 159-165 - [i12]Phillip Schneider, Tim Schopf, Juraj Vladika, Florian Matthes:
Enterprise Use Cases Combining Knowledge Graphs and Natural Language Processing. CoRR abs/2404.01443 (2024) - [i11]Tim Schopf, Florian Matthes:
NLP-KG: A System for Exploratory Search of Scientific Literature in Natural Language Processing. CoRR abs/2406.15294 (2024) - [i10]Stephen Meisenbacher, Tim Schopf, Weixin Yan, Patrick Holl, Florian Matthes:
An Improved Method for Class-specific Keyword Extraction: A Case Study in the German Business Registry. CoRR abs/2407.14085 (2024) - [i9]Tim Schopf, Alexander Blatzheim, Nektarios Machner, Florian Matthes:
Efficient Few-shot Learning for Multi-label Classification of Scientific Documents with Many Classes. CoRR abs/2410.05770 (2024) - 2023
- [c12]Tim Schopf, Nektarios Machner, Florian Matthes:
A Knowledge Graph Approach for Exploratory Search in Research Institutions. KMIS 2023: 265-270 - [c11]Tim Schopf, Karim Arabi, Florian Matthes:
Exploring the Landscape of Natural Language Processing Research. RANLP 2023: 1034-1045 - [c10]Tim Schopf, Dennis N. Schneider, Florian Matthes:
Efficient Domain Adaptation of Sentence Embeddings Using Adapters. RANLP 2023: 1046-1053 - [c9]Tim Schopf, Emanuel Gerber, Malte Ostendorff, Florian Matthes:
AspectCSE: Sentence Embeddings for Aspect-Based Semantic Textual Similarity Using Contrastive Learning and Structured Knowledge. RANLP 2023: 1054-1065 - [i8]Tim Schopf, Dennis N. Schneider, Florian Matthes:
Efficient Domain Adaptation of Sentence Embeddings using Adapters. CoRR abs/2307.03104 (2023) - [i7]Tim Schopf, Emanuel Gerber, Malte Ostendorff, Florian Matthes:
AspectCSE: Sentence Embeddings for Aspect-based Semantic Textual Similarity using Contrastive Learning and Structured Knowledge. CoRR abs/2307.07851 (2023) - [i6]Tim Schopf, Karim Arabi, Florian Matthes:
Exploring the Landscape of Natural Language Processing Research. CoRR abs/2307.10652 (2023) - [i5]Tim Schopf, Nektarios Machner, Florian Matthes:
A Knowledge Graph Approach for Exploratory Search in Research Institutions. CoRR abs/2311.15688 (2023) - 2022
- [c8]Tim Schopf, Kilian Dresse, Florian Matthes:
Towards AI Platforms for Stationary Retail. AI4I 2022: 22 - [c7]Tim Schopf, Simon Klimek, Florian Matthes:
PatternRank: Leveraging Pretrained Language Models and Part of Speech for Unsupervised Keyphrase Extraction. KDIR 2022: 243-248 - [c6]Phillip Schneider, Tim Schopf, Juraj Vladika, Michael Galkin, Elena Simperl, Florian Matthes:
A Decade of Knowledge Graphs in Natural Language Processing: A Survey. AACL/IJCNLP (1) 2022: 601-614 - [c5]Tim Schopf, Peter Weinberger, Thomas Kinkeldei, Florian Matthes:
Towards Bilingual Word Embedding Models for Engineering: Evaluating Semantic Linking Capabilities of Engineering-Specific Word Embeddings Across Languages. MSIE 2022: 407-413 - [c4]Tim Schopf, Daniel Braun, Florian Matthes:
Evaluating Unsupervised Text Classification: Zero-shot and Similarity-based Approaches. NLPIR 2022: 6-15 - [i4]Phillip Schneider, Tim Schopf, Juraj Vladika, Mikhail Galkin, Elena Simperl, Florian Matthes:
A Decade of Knowledge Graphs in Natural Language Processing: A Survey. CoRR abs/2210.00105 (2022) - [i3]Tim Schopf, Simon Klimek, Florian Matthes:
PatternRank: Leveraging Pretrained Language Models and Part of Speech for Unsupervised Keyphrase Extraction. CoRR abs/2210.05245 (2022) - [i2]Tim Schopf, Daniel Braun, Florian Matthes:
Lbl2Vec: An Embedding-Based Approach for Unsupervised Document Retrieval on Predefined Topics. CoRR abs/2210.06023 (2022) - [i1]Tim Schopf, Daniel Braun, Florian Matthes:
Evaluating Unsupervised Text Classification: Zero-shot and Similarity-based Approaches. CoRR abs/2211.16285 (2022) - 2021
- [c3]Daniel Braun, Oleksandra Klymenko, Tim Schopf, Yusuf Kaan Akan, Florian Matthes:
The Language of Engineering: Training a Domain-Specific Word Embedding Model for Engineering. MSIE 2021: 8-12 - [c2]Tim Schopf, Daniel Braun, Florian Matthes:
Semantic Label Representations with Lbl2Vec: A Similarity-Based Approach for Unsupervised Text Classification. WEBIST (Revised Selected Papers) 2021: 59-73 - [c1]Tim Schopf, Daniel Braun, Florian Matthes:
Lbl2Vec: An Embedding-based Approach for Unsupervised Document Retrieval on Predefined Topics. WEBIST 2021: 124-132
Coauthor Index
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