A SEmantic Modeling machIne to build Knowledge Graphs with Graph Neural Networks
MOLSIM is an interoperable domain ontology designed to semantically represent platform-agnostic biomolecular simulations as FAIR (Findable, Accessible, Interoperable, and Reusable) datasets. This ontology aims to standardize the representation of molecular simulation data, processes, and methodologies across different platforms and tools.
Aspect-weighted-Cross-Domain-Sentiment-Analysis: A pytorch implementation of cross domain sentiment analysis, using domain ontologies incorporated in a neural architecture
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