all AI news
Combining Machine Learning and Ontology: A Systematic Literature Review
Feb. 20, 2024, 5:45 a.m. | Sarah Ghidalia, Ouassila Labbani Narsis, Aur\'elie Bertaux, Christophe Nicolle
cs.LG updates on arXiv.org arxiv.org
Abstract: Motivated by the desire to explore the process of combining inductive and deductive reasoning, we conducted a systematic literature review of articles that investigate the integration of machine learning and ontologies. The objective was to identify diverse techniques that incorporate both inductive reasoning (performed by machine learning) and deductive reasoning (performed by ontologies) into artificial intelligence systems. Our review, which included the analysis of 128 studies, allowed us to identify three main categories of hybridization …
abstract articles arxiv cs.ai cs.lg diverse explore identify inductive integration literature machine machine learning ontologies ontology process reasoning review type
More from arxiv.org / cs.LG updates on arXiv.org
Digital Over-the-Air Federated Learning in Multi-Antenna Systems
2 days, 12 hours ago |
arxiv.org
Bagging Provides Assumption-free Stability
2 days, 12 hours ago |
arxiv.org
Jobs in AI, ML, Big Data
Data Architect
@ University of Texas at Austin | Austin, TX
Data ETL Engineer
@ University of Texas at Austin | Austin, TX
Lead GNSS Data Scientist
@ Lurra Systems | Melbourne
Senior Machine Learning Engineer (MLOps)
@ Promaton | Remote, Europe
Research Scientist, Demography and Survey Science, University Grad
@ Meta | Menlo Park, CA | New York City
Computer Vision Engineer, XR
@ Meta | Burlingame, CA