14 citations · 38 across the 13 of their papers we have counts for
13 papers
RAILD: Towards Leveraging Relation Features for Inductive Link Prediction In Knowledge Graphs
Genet Asefa Gesese, Harald Sack, Mehwish Alam
Due to the open world assumption, Knowledge Graphs (KGs) are never complete. In order to address this issue, various Link Prediction (LP) methods are proposed so far. Some of these…
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…
A Knowledge Graph Embeddings based Approach for Author Name Disambiguation using Literals
Cristian Santini, Genet Asefa Gesese, Silvio Peroni +3
Scholarly data is growing continuously containing information about the articles from a plethora of venues including conferences, journals, etc. Many initiatives have been taken to…
MigrationsKB: A Knowledge Base of Public Attitudes towards Migrations and their Driving Factors
Yiyi Chen, Harald Sack, Mehwish Alam
With the increasing trend in the topic of migration in Europe, the public is now more engaged in expressing their opinions through various platforms such as Twitter. Understanding…
Steps towards a Dislocation Ontology for Crystalline Materials
Ahmad Zainul Ihsan, Danilo Dessì, Mehwish Alam +2
The field of Materials Science is concerned with, e.g., properties and performance of materials. An important class of materials are crystalline materials that usually contain ``di…
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…
Entity Type Prediction in Knowledge Graphs using Embeddings
Russa Biswas, Radina Sofronova, Mehwish Alam +1
Open Knowledge Graphs (such as DBpedia, Wikidata, YAGO) have been recognized as the backbone of diverse applications in the field of data mining and information retrieval. Hence, t…
Semantic Entity Enrichment by Leveraging Multilingual Descriptions for Link Prediction
Genet Asefa Gesese, Mehwish Alam, Harald Sack
Most Knowledge Graphs (KGs) contain textual descriptions of entities in various natural languages. These descriptions of entities provide valuable information that may not be expli…
Is Aligning Embedding Spaces a Challenging Task? A Study on Heterogeneous Embedding Alignment Methods
Russa Biswas, Mehwish Alam, Harald Sack
Representation Learning of words and Knowledge Graphs (KG) into low dimensional vector spaces along with its applications to many real-world scenarios have recently gained momentum…
A Survey on Knowledge Graph Embeddings with Literals: Which model links better Literal-ly?
Genet Asefa Gesese, Russa Biswas, Mehwish Alam +1
Knowledge Graphs (KGs) are composed of structured information about a particular domain in the form of entities and relations. In addition to the structured information KGs help in…
Linked Open Data Validity -- A Technical Report from ISWS 2018
Tayeb Abderrahmani Ghor, Esha Agrawal, Mehwish Alam +68
Linked Open Data (LOD) is the publicly available RDF data in the Web. Each LOD entity is identfied by a URI and accessible via HTTP. LOD encodes globalscale knowledge potentially a…
Scheduling Refresh Queries for Keeping Results from a SPARQL Endpoint Up-to-Date (Extended Version)
Magnus Knuth, Olaf Hartig, Harald Sack
Many datasets change over time. As a consequence, long-running applications that cache and repeatedly use query results obtained from a SPARQL endpoint may resubmit the queries reg…
Collaboratively Patching Linked Data
Magnus Knuth, Johannes Hercher, Harald Sack
Today's Web of Data is noisy. Linked Data often needs extensive preprocessing to enable efficient use of heterogeneous resources. While consistent and valid data provides the key t…