243 citations · 694 across the 14 of their papers we have counts for
5 papers · 1 filter
EmbAssi: Embedding Assignment Costs for Similarity Search in Large Graph Databases
Franka Bause, Erich Schubert, Nils M. Kriege
The graph edit distance is an intuitive measure to quantify the dissimilarity of graphs, but its computation is NP-hard and challenging in practice. We introduce methods for answer…
Metric Indexing for Graph Similarity Search
Franka Bause, David B. Blumenthal, Erich Schubert +1
Finding the graphs that are most similar to a query graph in a large database is a common task with various applications. A widely-used similarity measure is the graph edit distanc…
MESS: Manifold Embedding Motivated Super Sampling
Erik Thordsen, Erich Schubert
Many approaches in the field of machine learning and data analysis rely on the assumption that the observed data lies on lower-dimensional manifolds. This assumption has been verif…
Accelerating Spherical k-Means
Erich Schubert, Andreas Lang, Gloria Feher
Spherical k-means is a widely used clustering algorithm for sparse and high-dimensional data such as document vectors. While several improvements and accelerations have been introd…
A Triangle Inequality for Cosine Similarity
Erich Schubert
Similarity search is a fundamental problem for many data analysis techniques. Many efficient search techniques rely on the triangle inequality of metrics, which allows pruning part…