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Found 5 papers, 2 papers with code
Document Structure aware Relational Graph Convolutional Networks for Ontology Population
Ontologies comprising of concepts, their attributes, and relationships are used in many knowledge based AI systems.
Document Structure Measure for Hypernym discovery
Hypernym discovery is the problem of finding terms that have is-a relationship with a given term.
Fine Grained Classification of Personal Data Entities
Entity Type Classification can be defined as the task of assigning category labels to entity mentions in documents.
FSCNMF: Fusing Structure and Content via Non-negative Matrix Factorization for Embedding Information Networks
In this work, we propose a nonnegative matrix factorization based optimization framework, namely FSCNMF which considers both the network structure and the content of the nodes while learning a lower dimensional vector representation of each node in the network.
Social and Information Networks
Fusing Structure and Content via Non-negative Matrix Factorization for Embedding Information Networks
It is not straightforward to integrate the content of each node in the current state-of-the-art network embedding methods.
