From the course: Data Preparation, Feature Engineering, and Augmentation for AI Models
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Ontologies, taxonomies, and knowledge graph tools and techniques
From the course: Data Preparation, Feature Engineering, and Augmentation for AI Models
Ontologies, taxonomies, and knowledge graph tools and techniques
- [Instructor] Ont ologies, taxonomies and knowledge graphs provide formal knowledge representation. Now, ontologies are formal explicit specifications of concepts, properties, and relationships. Now, it also includes additional constraints and rules that use formal logic. The advantage of representing these constraints and rules using formal logic is that that brings with it certain guarantees that we can assume regarding how we make inferences and how we draw conclusions. Now, taxonomies are lighter weight. They are hierarchical classification systems that are useful for organizing concepts into categories and subcategories. Now, knowledge graphs are most flexible in the sense that they are just network structures, and they can represent arbitrary entities and their relationships. Now, LLMs can benefit from all of these different kinds of knowledge representation schemes because they represent knowledge that has been essentially curated by humans. We're not depending on the…
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