6 citations · 25 across the 12 of their papers we have counts for
15 papers
Entity Type Prediction Leveraging Graph Walks and Entity Descriptions
Russa Biswas, Jan Portisch, Heiko Paulheim +2
The entity type information in Knowledge Graphs (KGs) such as DBpedia, Freebase, etc. is often incomplete due to automated generation or human curation. Entity typing is the task o…
The DLCC Node Classification Benchmark for Analyzing Knowledge Graph Embeddings
Jan Portisch, Heiko Paulheim
Knowledge graph embedding is a representation learning technique that projects entities and relations in a knowledge graph to continuous vector spaces. Embeddings have gained a lot…
KERMIT -- A Transformer-Based Approach for Knowledge Graph Matching
Sven Hertling, Jan Portisch, Heiko Paulheim
One of the strongest signals for automated matching of knowledge graphs and ontologies are textual concept descriptions. With the rise of transformer-based language models, text co…
Ontology Matching Through Absolute Orientation of Embedding Spaces
Jan Portisch, Guilherme Costa, Karolin Stefani +3
Ontology matching is a core task when creating interoperable and linked open datasets. In this paper, we explore a novel structure-based mapping approach which is based on knowledg…
Walk this Way! Entity Walks and Property Walks for RDF2vec
Jan Portisch, Heiko Paulheim
RDF2vec is a knowledge graph embedding mechanism which first extracts sequences from knowledge graphs by performing random walks, then feeds those into the word embedding algorithm…
Matching with Transformers in MELT
Sven Hertling, Jan Portisch, Heiko Paulheim
One of the strongest signals for automated matching of ontologies and knowledge graphs are the textual descriptions of the concepts. The methods that are typically applied (such as…
Putting RDF2vec in Order
Jan Portisch, Heiko Paulheim
The RDF2vec method for creating node embeddings on knowledge graphs is based on word2vec, which, in turn, is agnostic towards the position of context words. In this paper, we argue…
Background Knowledge in Schema Matching: Strategy vs. Data
Jan Portisch, Michael Hladik, Heiko Paulheim
The use of external background knowledge can be beneficial for the task of matching schemas or ontologies automatically. In this paper, we exploit six general-purpose knowledge gra…
FinMatcher at FinSim-2: Hypernym Detection in the Financial Services Domain using Knowledge Graphs
Jan Portisch, Michael Hladik, Heiko Paulheim
This paper presents the FinMatcher system and its results for the FinSim 2021 shared task which is co-located with the Workshop on Financial Technology on the Web (FinWeb) in conju…
Knowledge Graphs Evolution and Preservation -- A Technical Report from ISWS 2019
Nacira Abbas, Kholoud Alghamdi, Mortaza Alinam +71
One of the grand challenges discussed during the Dagstuhl Seminar "Knowledge Graphs: New Directions for Knowledge Representation on the Semantic Web" and described in its report is…
Supervised Ontology and Instance Matching with MELT
Sven Hertling, Jan Portisch, Heiko Paulheim
In this paper, we present MELT-ML, a machine learning extension to the Matching and EvaLuation Toolkit (MELT) which facilitates the application of supervised learning for ontology…
RDF2Vec Light -- A Lightweight Approach for Knowledge Graph Embeddings
Jan Portisch, Michael Hladik, Heiko Paulheim
Knowledge graph embedding approaches represent nodes and edges of graphs as mathematical vectors. Current approaches focus on embedding complete knowledge graphs, i.e. all nodes an…
Challenges of Linking Organizational Information in Open Government Data to Knowledge Graphs
Jan Portisch, Omaima Fallatah, Sebastian Neumaier +2
Open Government Data (OGD) is being published by various public administration organizations around the globe. Within the metadata of OGD data catalogs, the publishing organization…
Visual Analysis of Ontology Matching Results with the MELT Dashboard
Jan Portisch, Sven Hertling, Heiko Paulheim
In this demo, we introduce MELT Dashboard, an interactive Web user interface for ontology alignment evaluation which is created with the existing Matching EvaLuation Toolkit (MELT)…
KGvec2go -- Knowledge Graph Embeddings as a Service
Jan Portisch, Michael Hladik, Heiko Paulheim
In this paper, we present KGvec2go, a Web API for accessing and consuming graph embeddings in a light-weight fashion in downstream applications. Currently, we serve pre-trained emb…