Results 21 to 30 of about 72,713 (317)
Rule Learning over Knowledge Graphs: A Review [PDF]
Transactions on Graph Data and Knowledge, 2023 Compared to black-box neural networks, logic rules express explicit knowledge, can provide human-understandable explanations for reasoning processes, and have found their wide application in knowledge graphs and other downstream tasks.
Wu, Hong +4 more
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المنطق الماصدقي: تاريخه وخصائصه وتطبيقاته [PDF]
Maǧallaẗ Kulliyyaẗ Al-ādāb Ǧāmiʿaẗ Būrsaʿīd, 2022 لم يُعرف التمييز بين حدي القضية - المفهوم والماصدق - بشکلٍ انفصالي کلٌ على حدة إلاَّ في وقتٍ متأخر؛ فکل قضية تتکون من حدين هما المفهوم والماصدق، والعلاقة بينهما عکسية کما نعلم؛ کلما زاد المفهوم قل الماصدق والعکس، لکن هذا لا يعني القول بأحدهما فقط دون ...
محمد سيد محمد أبوالعلا
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Extending Coinductive Logic Programming with Co-Facts [PDF]
Electronic Proceedings in Theoretical Computer Science, 2017 We introduce a generalized logic programming paradigm where programs, consisting of facts and rules with the usual syntax, can be enriched by co-facts, which syntactically resemble facts but have a special meaning.
Davide Ancona +2 more
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Knowledge discovery from structured mammography reports using inductive logic programming. [PDF]
AMIA Annu Symp Proc, 2005 Burnside ES +6 more
europepmc +2 more sources
Program Logics for Homogeneous Generative Run-Time Meta-Programming [PDF]
Logical Methods in Computer Science, 2015 This paper provides the first program logic for homogeneous generative run-time meta-programming---using a variant of MiniML by Davies and Pfenning as its underlying meta-programming language.
Martin Berger, Laurence Tratt
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Induction of Non-monotonic Logic Programs To Explain Statistical Learning Models [PDF]
Electronic Proceedings in Theoretical Computer Science, 2019 We present a fast and scalable algorithm to induce non-monotonic logic programs from statistical learning models. We reduce the problem of search for best clauses to instances of the High-Utility Itemset Mining (HUIM) problem.
Farhad Shakerin
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NUML International Journal of Engineering and Computing, 2023 Industries widely use three-phase inductive loads, such as induction motors, due to their cost-effectiveness, low maintenance, reliability, and durability.
Amir Hamza +4 more
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A History of Probabilistic Inductive Logic Programming
Frontiers in Robotics and AI, 2014 The field of Probabilistic Logic Programming (PLP) has seen significant advances in the last 20 years, with many proposals for languages that combine probability with logic programming.
Fabrizio eRiguzzi +2 more
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Symbolic AI for XAI: Evaluating LFIT Inductive Programming for Explaining Biases in Machine Learning
Computers, 2021 Machine learning methods are growing in relevance for biometrics and personal information processing in domains such as forensics, e-health, recruitment, and e-learning.
Alfonso Ortega +6 more
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Probabilistic Inductive Logic Programming [PDF]
, 2004 Probabilistic inductive logic programming, sometimes also called statistical relational learning, addresses one of the central questions of artificial intelligence: the integration of probabilistic reasoning with first order logic representations and machine learning.
De Raedt, Luc, Kersting, Kristian
openaire +3 more sources