19 citations · 40 across the 6 of their papers we have counts for
7 papers
Specialized Document Embeddings for Aspect-based Similarity of Research Papers
Malte Ostendorff, Till Blume, Terry Ruas +2
Document embeddings and similarity measures underpin content-based recommender systems, whereby a document is commonly represented as a single generic embedding. However, similarit…
Scaling R-GCN Training with Graph Summarization
Alessandro Generale, Till Blume, Michael Cochez
Training of Relational Graph Convolutional Networks (R-GCN) is a memory intense task. The amount of gradient information that needs to be stored during training for real-world grap…
Time and Memory Efficient Parallel Algorithm for Structural Graph Summaries and two Extensions to Incremental Summarization and -Bisimulation for Long -Chaining
Till Blume, Jannik Rau, David Richerby +1
We developed a flexible parallel algorithm for graph summarization based on vertex-centric programming and parameterized message passing. The base algorithm supports infinitely man…
Aspect-based Document Similarity for Research Papers
Malte Ostendorff, Terry Ruas, Till Blume +2
Traditional document similarity measures provide a coarse-grained distinction between similar and dissimilar documents. Typically, they do not consider in what aspects two document…
Indexing Data on the Web: A Comparison of Schema-level Indices for Data Search -- Extended Technical Report
Till Blume, Ansgar Scherp
Indexing the Web of Data offers many opportunities, in particular, to find and explore data sources. One major design decision when indexing the Web of Data is to find a suitable i…
Towards an Open Platform for Legal Information
Malte Ostendorff, Till Blume, Saskia Ostendorff
Recent advances in the area of legal information systems have led to a variety of applications that promise support in processing and accessing legal documents. Unfortunately, thes…
FLUID: A Common Model for Semantic Structural Graph Summaries Based on Equivalence Relations
Till Blume, David Richerby, Ansgar Scherp
Summarization is a widespread method for handling very large graphs. The task of structural graph summarization is to compute a concise but meaningful synopsis of the key structura…