Automatic Induction of First-Order Logic Descriptors Type Domains from Observations
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It is still a major challenge to choose appropriate mode declarations.
“Although there is some work on learning mode declarations (McCreath & Sharma, 1995; Ferilli et al., 2004; Picado et al., 2017), it is still a major challenge to choose appropriate ones.”
From Inductive Logic Programming At 30: A New Introduction (2022) · cites this paper as Ferilli et al., 2004
Although there is some work on mode learning and identifying suitable metarules, this area of research is largely under-researched.
“Although there is some work on mode learning (McCreath & Sharma, 1995; Ferilli et al., 2004; Picado et al., 2017) and work on identifying suitable metarules (Cropper & Tourret, 2020), this area of research is largely under-researched.”
From Inductive Logic Programming At 30: A New Introduction (2022) · cites this paper as Ferilli et al., 2004
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Inductive Logic Programming At 30: A New Introduction
Cropper, A., & Dumančić, S. (2022) · Journal of Artificial Intelligence Research · doi:10.1613/jair.1.13507 · Cited by 83 · see citing works
“Although there is some work on learning mode declarations (McCreath & Sharma, 1995; Ferilli et al., 2004; Picado et al., 2017), it is still a major challenge to choose appropriate ones.”
BackgroundTowards Automatically Setting Language Bias in Relational Learning
Picado, J., Termehchy, A., Fern, A., & Pathak, S. (2017) · Proceedings of the 1st Workshop on Data Management for End-to-End Machine Learning · doi:10.1145/3076246.3076249 · Cited by 4 · see citing works
- Authors
- Ferilli, S., Esposito, F., Basile, T. M. A., & Di Mauro, N.
- Affiliations
- University of Bari Aldo Moro (IT)
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer Berlin Heidelberg
- Published
- 2004
- Pages
- 116-131
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W1557869917
- Cited by
- 8
- References
- 0
- Citations by year
- 2025: 1 · 2023: 1 · 2022: 1 · 2021: 1 · 2017: 1
- FWCI
- 0.43
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- Lecture notes in computer science (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Logic, Reasoning, and Knowledge
- Physical Sciences › Computer Science › Information Systems › Data Mining Algorithms and Applications
- Physical Sciences › Computer Science › Artificial Intelligence › Semantic Web and Ontologies
- Keywords
- inductive logic programming, first-order logic, metadata, search space pruning, incomplete observations, relational learning
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
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