Search Results for author:
Found 15 papers, 6 papers with code
Entity Type Prediction Leveraging Graph Walks and Entity Descriptions
Entity typing is the task of assigning or inferring the semantic type of an entity in a KG.
The DLCC Node Classification Benchmark for Analyzing Knowledge Graph Embeddings
To demonstrate the use of DLCC, we compare multiple embedding approaches using the gold standards.
KERMIT - A Transformer-Based Approach for Knowledge Graph Matching
One of the strongest signals for automated matching of knowledge graphs and ontologies are textual concept descriptions.
Ontology Matching Through Absolute Orientation of Embedding Spaces
Ontology matching is a core task when creating interoperable and linked open datasets.
Walk this Way! Entity Walks and Property Walks for RDF2vec
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 word2vec for computing vector representations for entities.
Matching with Transformers in MELT
One of the strongest signals for automated matching of ontologies and knowledge graphs are the textual descriptions of the concepts.
Putting RDF2vec in Order
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.
Background Knowledge in Schema Matching: Strategy vs. Data
The use of external background knowledge can be beneficial for the task of matching schemas or ontologies automatically.
FinMatcher at FinSim-2: Hypernym Detection in the Financial Services Domain using Knowledge Graphs
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 conjunction with The Web Conference.
Knowledge Graphs Evolution and Preservation -- A Technical Report from ISWS 2019
Although linked open data (LOD) is one knowledge graph, it is the closest realisation (and probably the only one) to a public FAIR Knowledge Graph (KG) of everything.
Supervised Ontology and Instance Matching with MELT
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 and instance matching.
RDF2Vec Light -- A Lightweight Approach for Knowledge Graph Embeddings
Knowledge graph embedding approaches represent nodes and edges of graphs as mathematical vectors.
Challenges of Linking Organizational Information in Open Government Data to Knowledge Graphs
Open Government Data (OGD) is being published by various public administration organizations around the globe.
Visual Analysis of Ontology Matching Results with the MELT Dashboard
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
In this paper, we present KGvec2go, a Web API for accessing and consuming graph embeddings in a light-weight fashion in downstream applications.
