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Cited by 235Data Mining Algorithms and ApplicationsLogic, Reasoning, and KnowledgeBayesian Modeling and Causal Inference

Clausal Discovery

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De Raedt, Luc, Dehaspe, Luc·1997·Machine Learning
DOI 10.1023/a:1007361123060
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  • LFI is the second most popular learning setting, where an example is an interpretation (a set of facts).

    “The second most popular (De Raedt & Dehaspe, 1997; Blockeel & De Raedt, 1998; Law et al., 2014) learning setting is LFI where an example is an interpretation, i.e. a set of facts.”

    From Inductive Logic Programming At 30: A New Introduction (2022) · cites this paper as De Raedt & Dehaspe, 1997

    Section 3.3.3 states that examples in the paper’s learning-from-interpretations setting are interpretations, and Section 2 describes a Herbrand interpretation as a set of ground facts. Section 3 calls normal inductive logic programming the setting used by the large majority of systems, but does not rank learning from interpretations as the second most popular; its numbered list is a list of formalisations, not a popularity ranking. Page numbers were not available in our copy. (LLM, conf=0.88)

    Experimental — accuracy not yet measured

  • Some ILP systems induce full (unrestricted) clausal theories, such as Claudien and CF-induction.

    “Some systems induce full (unrestricted) clausal theories, such as Claudien (De Raedt & Dehaspe, 1997) and CF-induction (Inoue, 2004).”

    From Inductive Logic Programming At 30: A New Introduction (2022) · cites this paper as De Raedt & Dehaspe, 1997

  • Many systems employ the covering algorithm whereby hypotheses are constructed iteratively clause by clause.

    “The above paragraph refers only to generality orders on single clauses, as many systems employ the covering algorithm whereby hypotheses are constructed iteratively clause by clause (Quinlan, 1990; De Raedt & Dehaspe, 1997; Muggleton, 1995; Blockeel & De Raedt, 1998; Srinivasan, 2001).”

    From Inductive Logic Programming At 30: A New Introduction (2022) · cites this paper as De Raedt & Dehaspe, 1997

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References 57 · Cited by 235

Research works printed but not linked: 50

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Authors
De Raedt, L., & Dehaspe, L.
Affiliations
KU Leuven (BE)
Venue
Machine Learning
Publisher
Springer Science and Business Media LLC
Published
1997-02
Volume
26
Issue
2-3
Pages
99-146
ISSN
  • 0885-6125 (ISSN-L)
  • 1573-0565
DOI
10.1023/a:1007361123060
OpenAlex
W2914587038
Cited by
235
References
57
Citations by year
2026: 1 · 2025: 2 · 2024: 4 · 2023: 1 · 2022: 3 · 2021: 2 · 2020: 2 · 2019: 1 · 2018: 2 · 2017: 1 · 2016: 10 · 2015: 4 · 2014: 5 · 2013: 4 · 2012: 10
FWCI
52.11
Type
journal article
Language
en
Open access
Licence
Locations
  • Machine Learning (publishedVersion)
  • Lirias (submittedVersion, other-oa)
Funders
Fonds De La Recherche Scientifique - FNRS
Topics
  • Physical Sciences › Computer Science › Information Systems › Data Mining Algorithms and Applications
  • Physical Sciences › Computer Science › Artificial Intelligence › Logic, Reasoning, and Knowledge
  • Physical Sciences › Computer Science › Artificial Intelligence › Bayesian Modeling and Causal Inference
Keywords
inductive logic programming, Herbrand interpretations

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