4 citations · 16 across the 7 of their papers we have counts for
9 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…
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…