no code implementations • 7 Nov 2023 • Ananjan Nandi, Navdeep Kaur, Parag Singla, Mausam
We consider two popular approaches to Knowledge Graph Completion (KGC): textual models that rely on textual entity descriptions, and structure-based models that exploit the connectivity structure of the Knowledge Graph (KG).
no code implementations • 15 May 2023 • Ishaan Singh, Navdeep Kaur, Garima Gaur, Mausam
While Knowledge Graph Completion (KGC) on static facts is a matured field, Temporal Knowledge Graph Completion (TKGC), that incorporates validity time into static facts is still in its nascent stage.
no code implementations • 13 Mar 2020 • Navdeep Kaur, Gautam Kunapuli, Sriraam Natarajan
In this work, we propose a novel knowledge graph alignment technique based upon string edit distance that exploits the type information between entities and can find similarity between relations of any arity
no code implementations • 9 Jan 2020 • Navdeep Kaur, Gautam Kunapuli, Sriraam Natarajan
We consider the problem of discriminatively learning restricted Boltzmann machines in the presence of relational data.
1 code implementation • 28 Aug 2019 • Navdeep Kaur, Gautam Kunapuli, Saket Joshi, Kristian Kersting, Sriraam Natarajan
While deep networks have been enormously successful over the last decade, they rely on flat-feature vector representations, which makes them unsuitable for richly structured domains such as those arising in applications like social network analysis.