Lukas Galke
Zitiert von
Zitiert von
Word embeddings for practical information retrieval
L Galke, A Saleh, A Scherp
Informatik 2017, 2155-2167, 2017
Using deep learning for title-based semantic subject indexing to reach competitive performance to full-text
F Mai, L Galke, A Scherp
Proceedings of the 18th ACM/IEEE on Joint Conference on Digital Libraries …, 2018
Using titles vs. full-text as source for automated semantic document annotation
L Galke, F Mai, A Schelten, D Brunsch, A Scherp
Proceedings of the Knowledge Capture Conference, 1-4, 2017
Linked open citation database: Enabling libraries to contribute to an open and interconnected citation graph
A Lauscher, K Eckert, L Galke, A Scherp, STR Rizvi, S Ahmed, A Dengel, ...
Proceedings of the 18th ACM/IEEE on Joint Conference on Digital Libraries …, 2018
Multi-modal adversarial autoencoders for recommendations of citations and subject labels
L Galke, F Mai, I Vagliano, A Scherp
Proceedings of the 26th conference on user modeling, adaptation and …, 2018
CBOW is not all you need: Combining CBOW with the compositional matrix space model
F Mai, L Galke, A Scherp
arXiv preprint arXiv:1902.06423, 2019
Lifelong learning of graph neural networks for open-world node classification
L Galke, B Franke, T Zielke, A Scherp
2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021
Inductive learning of concept representations from library-scale corpora with graph convolution
L Galke, T Melnychuk, E Seidlmayer, S Trog, KU Frstner, C Schultz, ...
INFORMATIK. Gesellschaft für Informatik, Bonn, 2019
Can Graph Neural Networks Go" Online"? An Analysis of Pretraining and Inference
L Galke, I Vagliano, A Scherp
arXiv preprint arXiv:1905.06018, 2019
Bag-of-words vs. graph vs. sequence in text classification: Questioning the necessity of text-graphs and the surprising strength of a wide MLP
L Galke, A Scherp
Proceedings of the 60th Annual Meeting of the Association for Computational …, 2022
Incremental training of graph neural networks on temporal graphs under distribution shift
L Galke, I Vagliano, A Scherp
Using adversarial autoencoders for multi-modal automatic playlist continuation
I Vagliano, L Galke, F Mai, A Scherp
Proceedings of the ACM Recommender Systems Challenge 2018, 1-6, 2018
Comparing titles vs. full-text for multi-label classification of scientific papers and news articles
L Galke, F Mai, A Schelten, D Brunsch, A Scherp
arXiv preprint arXiv:1705.05311, 2017
Emergent Communication for Understanding Human Language Evolution: What's Missing?
L Galke, Y Ram, L Raviv
arXiv preprint arXiv:2204.10590, 2022
ORCID for Wikidata. Data enrichment for scientometric applications
E Seidlmayer, J Voß, T Melnychuk, L Galke, K Tochtermann, C Schultz, ...
1st Wikidata Workshop (Wikidata 2020), 2020
Take it personally-A Python library for data enrichment for infometrical applications
E Seidlmayer, L Galke, T Melnychuk, C Schultz, K Tochtermann, ...
Posters and Demo Track of the 15th International Conference on Semantic …, 2019
A case study of closed-domain response suggestion with limited training data
L Galke, G Gerstenkorn, A Scherp
International Conference on Database and Expert Systems Applications, 218-229, 2018
Bag-of-Words vs. Sequence vs. Graph vs. Hierarchy for Single-and Multi-Label Text Classification
A Diera, BX Lin, B Khera, T Meuser, T Singhal, L Galke, A Scherp
arXiv preprint arXiv:2204.03954, 2022
Recommendations for item set completion: on the semantics of item co-occurrence with data sparsity, input size, and input modalities
I Vagliano, L Galke, A Scherp
Information Retrieval Journal, 2022
General cross-architecture distillation of pretrained language models into matrix embedding
L Galke, I Cuber, C Meyer, HF Nölscher, A Sonderecker, A Scherp
the IEEE Joint Conference on Neural Networks (IJCNN 2022), part of the IEEE …, 2022
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