[HTML][HTML] Ontology-based decision support systems for diabetes nutrition therapy: A systematic literature review
D Spoladore, M Tosi, EC Lorenzini - Artificial Intelligence in Medicine, 2024 - Elsevier
Diabetes is a non-communicable disease that has reached epidemic proportions, affecting
537 million people globally. Artificial Intelligence can support patients or clinicians in …
537 million people globally. Artificial Intelligence can support patients or clinicians in …
A simple standard for sharing ontological mappings (SSSOM)
Despite progress in the development of standards for describing and exchanging scientific
information, the lack of easy-to-use standards for mapping between different representations …
information, the lack of easy-to-use standards for mapping between different representations …
Knowledge graphs for the life sciences: Recent developments, challenges and opportunities
The term life sciences refers to the disciplines that study living organisms and life processes,
and include chemistry, biology, medicine, and a range of other related disciplines. Research …
and include chemistry, biology, medicine, and a range of other related disciplines. Research …
Olala: Ontology matching with large language models
S Hertling, H Paulheim - Proceedings of the 12th Knowledge Capture …, 2023 - dl.acm.org
Ontology (and more generally: Knowledge Graph) Matching is a challenging task where
information in natural language is one of the most important signals to process. With the rise …
information in natural language is one of the most important signals to process. With the rise …
DeepOnto: A Python package for ontology engineering with deep learning
Integrating deep learning techniques, particularly language models (LMs), with knowledge
representation techniques like ontologies has raised widespread attention, urging the need …
representation techniques like ontologies has raised widespread attention, urging the need …
Matching multiple ontologies to build a knowledge graph for personalized medicine
A rich biomedical knowledge graph can support the multi-domain data integration necessary
for the application of Artificial Intelligence models in personalised medicine. Constructing …
for the application of Artificial Intelligence models in personalised medicine. Constructing …
Integrating heterogeneous ontologies in Asian languages through compact genetic algorithm with annealing re-sample inheritance mechanism
X Xue, W Liu - ACM Transactions on Asian and Low-Resource …, 2023 - dl.acm.org
An ontology is a state-of-the-art knowledge modeling technique in the natural language
domain, which has been widely used to overcome the linguistic barriers in Asian and …
domain, which has been widely used to overcome the linguistic barriers in Asian and …
Toward the multilingual semantic web: Multilingual ontology matching and assessment
The amount of multilingual data on the Web proliferates; therefore, developing ontologies in
various natural languages is attracting considerable attention. In order to achieve semantic …
various natural languages is attracting considerable attention. In order to achieve semantic …
[HTML][HTML] Kae: A property-based method for knowledge graph alignment and extension
D Shi, X Li, F Giunchiglia - Journal of Web Semantics, 2024 - Elsevier
A common solution to the semantic heterogeneity problem is to perform knowledge graph
(KG) extension exploiting the information encoded in one or more candidate KGs, where the …
(KG) extension exploiting the information encoded in one or more candidate KGs, where the …
KGrEaT: a framework to evaluate knowledge graphs via downstream tasks
In recent years, countless research papers have addressed the topics of knowledge graph
creation, extension, or completion in order to create knowledge graphs that are larger, more …
creation, extension, or completion in order to create knowledge graphs that are larger, more …