research
∙
06/19/2023
Fine-Tuning Language Models for Scientific Writing Support
We support scientific writers in determining whether a written sentence ...
share
research
∙
06/15/2023
The Split Matters: Flat Minima Methods for Improving the Performance of GNNs
When training a Neural Network, it is optimized using the available trai...
research
∙
12/07/2022
A Study on Extracting Named Entities from Fine-tuned vs. Differentially Private Fine-tuned BERT Models
Privacy preserving deep learning is an emerging field in machine learnin...
research
∙
11/30/2022
Transformers are Short Text Classifiers: A Study of Inductive Short Text Classifiers on Benchmarks and Real-world Datasets
Short text classification is a crucial and challenging aspect of Natural...
research
∙
11/24/2022
Reducing a Set of Regular Expressions and Analyzing Differences of Domain-specific Statistic Reporting
Due to the large amount of daily scientific publications, it is impossib...
research
∙
11/05/2022
Semantic Metadata Extraction from Dense Video Captioning
Annotation of multimedia data by humans is time-consuming and costly, wh...
research
∙
04/12/2022
Single-Purpose Algorithms vs. a Generic Graph Summarizer for Computing k-Bisimulations on Large Graphs
We investigate whether a generic graph summarization approach BRS can ou...
research
∙
04/08/2022
Bag-of-Words vs. Sequence vs. Graph vs. Hierarchy for Single- and Multi-Label Text Classification
Graph neural networks have triggered a resurgence of graph-based text cl...
research
∙
03/11/2022
Graph Summarization with Graph Neural Networks
The goal of graph summarization is to represent large graphs in a struct...
research
∙
12/20/2021
Lifelong Learning in Evolving Graphs with Limited Labeled Data and Unseen Class Detection
Large-scale graph data in the real-world are often dynamic rather than s...
research
∙
11/24/2021
Time and Memory Efficient Parallel Algorithm for Structural Graph Summaries and two Extensions to Incremental Summarization and k-Bisimulation for Long k-Chaining
We developed a flexible parallel algorithm for graph summarization based...
research
∙
09/17/2021
New Students on Sesame Street: What Order-Aware Matrix Embeddings Can Learn from BERT
Large-scale pretrained language models (PreLMs) are revolutionizing natu...
research
∙
09/08/2021
Forget me not: A Gentle Reminder to Mind the Simple Multi-Layer Perceptron Baseline for Text Classification
Graph neural networks have triggered a resurgence of graph-based text cl...
research
∙
05/19/2021
Analysis of GraphSum's Attention Weights to Improve the Explainability of Multi-Document Summarization
Modern multi-document summarization (MDS) methods are based on transform...
research
∙
05/18/2021
rx-anon – A Novel Approach on the De-Identification of Heterogeneous Data based on a Modified Mondrian Algorithm
Traditional approaches for data anonymization consider relational data a...
research
∙
05/10/2021
Recommendations for Item Set Completion: On the Semantics of Item Co-Occurrence With Data Sparsity, Input Size, and Input Modalities
We address the problem of recommending relevant items to a user in order...
research
∙
03/25/2021
A Machine Learning Pipeline for Automatic Extraction of Statistic Reports and Experimental Conditions from Scientific Papers
A common writing style for statistical results are the recommendations o...
research
∙
06/25/2020
Incremental Training of Graph Neural Networks on Temporal Graphs under Distribution Shift
Current graph neural networks (GNNs) are promising, especially when the ...
research
∙
06/12/2020
Indexing Data on the Web: A Comparison of Schema-level Indices for Data Search – Extended Technical Report
Indexing the Web of Data offers many opportunities, in particular, to fi...
research
∙
08/05/2019
FLuID: A Meta Model to Flexibly Define Schema-level Indices for the Web of Data
Schema-level indices are vital for summarizing large collections of grap...
research
∙
07/22/2019
Multi-Modal Adversarial Autoencoders for Recommendations of Citations and Subject Labels
We present multi-modal adversarial autoencoders for recommendation and e...
research
∙
05/15/2019
Can Graph Neural Networks Go "Online"? An Analysis of Pretraining and Inference
Large-scale graph data in real-world applications is often not static bu...
research
∙
02/18/2019
CBOW Is Not All You Need: Combining CBOW with the Compositional Matrix Space Model
Continuous Bag of Words (CBOW) is a powerful text embedding method. Due ...
research
∙
01/20/2018
Using Deep Learning For Title-Based Semantic Subject Indexing To Reach Competitive Performance to Full-Text
For (semi-)automated subject indexing systems in digital libraries, it i...
research
∙
09/30/2017
Towards Understanding the Evolution of Vocabulary Terms in Knowledge Graphs
Vocabularies are used for modeling data in Knowledge Graphs (KG) like th...
research
∙
09/28/2017
Content Recommendation through Semantic Annotation of User Reviews and Linked Data - An Extended Technical Report
Nowadays, most recommender systems exploit user-provided ratings to infe...
research
∙
05/15/2017
