4 citations · 9 across the 3 of their papers we have counts for
7 papers
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…
Semantic Role Labeling for Knowledge Graph Extraction from Text
Mehwish Alam, Aldo Gangemi, Valentina Presutti +1
This paper introduces TakeFive, a new semantic role labeling method that transforms a text into a frame-oriented knowledge graph. It performs dependency parsing, identifies the wor…