Policy-based memoization for ILP-based concept discovery systems

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dc.contributor.authorMutlu, Alev
dc.contributor.authorKaragoz, Pinar
dc.date.accessioned2020-03-26T19:25:40Z
dc.date.available2020-03-26T19:25:40Z
dc.date.issued2016
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractInductive Programming Logic (ILP)-based concept discovery systems aim to find patterns that describe a target relation in terms of other relations provided as background knowledge. Such systems usually work within first order logic framework, build large search spaces, and have long running times. Memoization has widely been incorporated in concept discovery systems to improve their running times. One of the problems that memoization brings to such systems is the memory overhead which may be a bottleneck. In this work we propose policies that decide what types of concept descriptors to store in memotables and for how long to keep them. The proposed policies have been implemented as extensions to a concept discovery system called Tabular CRIS wEF, and the resulting system is named Policy-based Tabular CRIS. Effects of the proposed policies are evaluated on several datasets. The experimental results show that the proposed policies greatly improve the memory consumption while preserving the benefits introduced by memoization.en_US
dc.identifier.doi10.1007/s10844-015-0354-7en_US
dc.identifier.endpage120en_US
dc.identifier.issn0925-9902en_US
dc.identifier.issn1573-7675en_US
dc.identifier.issue1en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.startpage99en_US
dc.identifier.urihttps://dx.doi.org/10.1007/s10844-015-0354-7
dc.identifier.urihttps://hdl.handle.net/20.500.12395/33886
dc.identifier.volume46en_US
dc.identifier.wosWOS:000372261600005en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSPRINGERen_US
dc.relation.ispartofJOURNAL OF INTELLIGENT INFORMATION SYSTEMSen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectMulti-relational data miningen_US
dc.subjectInductive logic programmingen_US
dc.subjectConcept discoveryen_US
dc.subjectMemoizationen_US
dc.subjectMemory consumptionen_US
dc.subjectScalabilityen_US
dc.titlePolicy-based memoization for ILP-based concept discovery systemsen_US
dc.typeArticleen_US

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