1. The Prioritized Inductive Logic Programs - Ma, Shilong; Sui, Yuefei; Xu, Ke
The limit behavior of inductive logic programs has not been explored, butwhen considering incremental or online inductive learning algorithms whichusually run ongoingly, such behavior of the programs should be taken intoaccount.

2. Extending Classical Logic with Inductive Definitions - Denecker, Marc
The goal of this paper is to extend classical logic with a generalized notionof inductive definition supporting positive and negative induction, toinvestigate the properties of this logic, its relationships to other logics inthe area of non-monotonic reasoning, logic programming and deductive databases,and to show its application for knowledge representation by giving a typologyof definitional knowledge.

3. Scaling Up Inductive Logic Programming by Learning from Interpretations - Blockeel, Hendrik; De Raedt, Luc; Jacobs, Nico; Demoen, Bart
When comparing inductive logic programming (ILP) and attribute-value learningtechniques, there is a trade-off between expressive power and efficiency.

4. Knowledge Discovery from Structured Mammography Reports Using InductiveLogic Programming - Burnside, Elizabeth S.; Davis, Jesse; Costa, Vítor Santos; de Castro Dutra, Inês; Kahn, Charles E.; Fine, Jason; Page, David
The development of large mammography databases provides an opportunityfor knowledge discovery and data mining techniques to recognize patternsnot previously appreciated.

5. Inductive Logic: From Data Analysis to Experimental Design - Knuth, Kevin H.
In its application to the scientific method, the logic of questions,inductive inquiry, can be applied to design an experiment that most effectivelyaddresses a scientific issue.

6. A Logic for Non-Monotone Inductive Definitions - Denecker, Marc; Ternovska, Eugenia
Well-known principles of induction include monotone induction and differentsorts of non-monotone induction such as inflationary induction, induction overwell-founded sets and iterated induction.

7. Logic Programming, Functional Programming, and Inductive Definitions - Paulson, Lawrence C.; Smith, Andrew W.
An attempt at unifying logic and functional programming is reported.

8. Learning Information Extraction Rules: An Inductive Logic Programming approach - Aitken, J.S.
The objective of this work is to learn information extraction rules byapplying Inductive Logic Programming (ILP) techniques to naturallanguage data.

9. Prediction of rodent carcinogenicity bioassays from molecular structure using inductive logic programming. - King, R D; Srinivasan, A
The machine learning program Progol was applied to the problem of forming the structure-activity relationship (SAR) for a set of compounds tested for carcinogenicity in rodent bioassays by the U.S.

10. Prediction of rodent carcinogenicity bioassays from molecular structure using inductive logic programming. - King, R D; Srinivasan, A
The machine learning program Progol was applied to the problem of forming the structure-activity relationship (SAR) for a set of compounds tested for carcinogenicity in rodent bioassays by the U.S.

11. Low Size-Complexity Inductive Logic Programming: The East-West Challenge Considered as a Problem in Cost-Sensitive Classification - Turney, Peter D.
The Inductive Logic Programming community has considered proof-complexity andmodel-complexity, but, until recently, size-complexity has received littleattention.

12. A fully logical inductive logic. - Nolt, John

13. Drug design by machine learning: the use of inductive logic programming to model the structure-activity relationships of trimethoprim analogues binding to dihydrofolate reductase. - King, R D; Muggleton, S; Lewis, R A; Sternberg, M J
The training data for the program were 44 trimethoprim analogues and their observed inhibition of Escherichia coli dihydrofolate reductase.

14. Drug design by machine learning: the use of inductive logic programming to model the structure-activity relationships of trimethoprim analogues binding to dihydrofolate reductase. - King, R D; Muggleton, S; Lewis, R A; Sternberg, M J
The training data for the program were 44 trimethoprim analogues and their observed inhibition of Escherichia coli dihydrofolate reductase.

15. Structure-activity relationships derived by machine learning: the use of atoms and their bond connectivities to predict mutagenicity by inductive logic programming. - King, R D; Muggleton, S H; Srinivasan, A; Sternberg, M J
We have tested the relational approach by investigating the SARs of 230 aromatic and heteroaromatic nitro compounds.

16. Structure-activity relationships derived by machine learning: the use of atoms and their bond connectivities to predict mutagenicity by inductive logic programming. - King, R D; Muggleton, S H; Srinivasan, A; Sternberg, M J
We have tested the relational approach by investigating the SARs of 230 aromatic and heteroaromatic nitro compounds.

17. FPL may be equivalent to FO but not equivalent to PFP - Shelah, Saharon
Given a class of finite models we would like to expand each model (allowingnew elements but the old universe is a separate sort), making the expressivepower of LFP (least fix point logic) and PFP (inductive logic) similar whilenot changing the expressive power of FO (first order logic).

18. A " Layers of Reality to a Web of Induction " Hypothesis - Abbas, Afsar
Each layer of reality has its owndistinctive inductive logic which may differ from that of the others.

19. Entropic criterion for model selection - Tseng, Chih-Yuan
One of methods is applyingKullback-Leibler distance or relative entropy as a selection criterion.

20. Top-down induction of clustering trees - Blockeel, Hendrik; De Raedt, Luc; Ramon, Jan
An approach to clustering is presented that adapts the basic top-downinduction of decision trees method towards clustering.

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