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Knowledge graphs: A practical review of the research landscape
Knowledge graphs (KGs) have rapidly emerged as an important area in AI over the last ten
years. Building on a storied tradition of graphs in the AI community, a KG may be simply …
years. Building on a storied tradition of graphs in the AI community, a KG may be simply …
BERTMap: a BERT-based ontology alignment system
Ontology alignment (aka ontology matching (OM)) plays a critical role in knowledge
integration. Owing to the success of machine learning in many domains, it has been applied …
integration. Owing to the success of machine learning in many domains, it has been applied …
LearningToAdapt with word embeddings: Domain adaptation of Named Entity Recognition systems
Abstract The task of Named Entity Recognition (NER) is aimed at identifying named entities
in a given text and classifying them into pre-defined domain entity types such as persons …
in a given text and classifying them into pre-defined domain entity types such as persons …
Ontology engineering: Current state, challenges, and future directions
In the last decade, ontologies have become widely adopted in a variety of fields ranging
from biomedicine, to finance, engineering, law, and cultural heritage. The ontology …
from biomedicine, to finance, engineering, law, and cultural heritage. The ontology …
Ontology embedding: a survey of methods, applications and resources
Ontologies are widely used for representing domain knowledge and meta data, playing an
increasingly important role in Information Systems, the Semantic Web, Bioinformatics and …
increasingly important role in Information Systems, the Semantic Web, Bioinformatics and …
Augmenting ontology alignment by semantic embedding and distant supervision
Ontology alignment plays a critical role in knowledge integration and has been widely
investigated in the past decades. State of the art systems, however, still have considerable …
investigated in the past decades. State of the art systems, however, still have considerable …
Machine learning-friendly biomedical datasets for equivalence and subsumption ontology matching
Ontology Matching (OM) plays an important role in many domains such as bioinformatics
and the Semantic Web, and its research is becoming increasingly popular, especially with …
and the Semantic Web, and its research is becoming increasingly popular, especially with …
Medto: Medical data to ontology matching using hybrid graph neural networks
Medical ontologies are widely used to describe and organize medical terminologies and to
support many critical applications on healthcare databases. These ontologies are often …
support many critical applications on healthcare databases. These ontologies are often …
SMAT: An attention-based deep learning solution to the automation of schema matching
Schema matching aims to identify the correspondences among attributes of database
schemas. It is frequently considered as the most challenging and decisive stage existing in …
schemas. It is frequently considered as the most challenging and decisive stage existing in …
Adnev: Cross-domain schema matching using deep similarity matrix adjustment and evaluation
Schema matching is a process that serves in integrating structured and semi-structured data.
Being a handy tool in multiple contemporary business and commerce applications, it has …
Being a handy tool in multiple contemporary business and commerce applications, it has …