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New framework enables fuzzy quantification over ontologies and knowledge graphs

By PulseAugur Editorial · [1 sources] ·

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 →

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

New framework enables fuzzy quantification over ontologies and knowledge graphs

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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]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Umberto Straccia ·

    Fuzzy Quantification over OWL Ontologies and Knowledge Graphs

    This paper presents a versatile framework for evaluating fuzzy quantification queries over both standard and fuzzy ontologies as well as knowledge graphs. The primary objective is the retrieval of individuals that satisfy queries articulated via Type I or Type II fuzzy quantified…

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