New framework enables fuzzy quantification over ontologies and knowledge graphs

Researchers have developed a new framework for fuzzy quantification queries over ontologies and knowledge graphs, supporting both standard and fuzzy versions. This system is designed to retrieve individuals that meet criteria expressed through Type I or Type II fuzzy quantified statements. A notable feature is its independence from the specific quantifier type, evaluation method, or data source, and it includes a publicly available implementation called Q2S2 to facilitate further research. AI

IMPACT Enhances querying capabilities for knowledge graphs and ontologies, potentially improving AI reasoning and data retrieval.

RANK_REASON This is a research paper detailing a new framework and implementation for fuzzy quantification over ontologies and knowledge graphs. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

• alphaXiv
• CatalyzeX
• CORE Recommender
• DagsHub
• Gotit.pub
• Hugging Face
• Influence Flower
• Q2S2
• RDF Schema
• ScienceCast

• paper
• other

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →