ILP: Compute Once, Reuse Often
Autor(a) principal: | |
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Data de Publicação: | 2007 |
Outros Autores: | , , |
Tipo de documento: | Livro |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | https://hdl.handle.net/10216/67388 |
Resumo: | Inductive Logic Programming (ILP) is a powerful and welldeveloped abstraction for multi-relational data mining techniques. However, ILP systems are not particularly fast, most of their execution time is spent evaluating the hypotheses they construct. The evaluation time needed to assess the quality of each hypothesis depends mainly on the number of examples and the theorem proving effort required to determine if an example is entailed by the hypothesis. We propose a technique that reduces the theorem proving effort to a bare minimum and stores valuable information to compute the number of examples entailed by each hypothesis (using a tree data structure). The information is computed only once (pre-compiled) per example. Evaluation of hypotheses requires only basic and efficient operations on trees. This proposal avoids re-computation of hypothesis value in theory-level search and cross-validation algorithms, whenever the same data set is used with different parameters. In an empirical evaluation the technique yielded considerable speedups. |
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ILP: Compute Once, Reuse OftenEngenharia do conhecimento, Engenharia electrotécnica, electrónica e informáticaKnowledge engineering, Electrical engineering, Electronic engineering, Information engineeringInductive Logic Programming (ILP) is a powerful and welldeveloped abstraction for multi-relational data mining techniques. However, ILP systems are not particularly fast, most of their execution time is spent evaluating the hypotheses they construct. The evaluation time needed to assess the quality of each hypothesis depends mainly on the number of examples and the theorem proving effort required to determine if an example is entailed by the hypothesis. We propose a technique that reduces the theorem proving effort to a bare minimum and stores valuable information to compute the number of examples entailed by each hypothesis (using a tree data structure). The information is computed only once (pre-compiled) per example. Evaluation of hypotheses requires only basic and efficient operations on trees. This proposal avoids re-computation of hypothesis value in theory-level search and cross-validation algorithms, whenever the same data set is used with different parameters. In an empirical evaluation the technique yielded considerable speedups.20072007-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/bookapplication/pdfhttps://hdl.handle.net/10216/67388engNuno A. FonsecaRicardo RochaRui CamachoVítor Santos Costainfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-29T14:26:51Zoai:repositorio-aberto.up.pt:10216/67388Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T00:01:24.725696Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
ILP: Compute Once, Reuse Often |
title |
ILP: Compute Once, Reuse Often |
spellingShingle |
ILP: Compute Once, Reuse Often Nuno A. Fonseca Engenharia do conhecimento, Engenharia electrotécnica, electrónica e informática Knowledge engineering, Electrical engineering, Electronic engineering, Information engineering |
title_short |
ILP: Compute Once, Reuse Often |
title_full |
ILP: Compute Once, Reuse Often |
title_fullStr |
ILP: Compute Once, Reuse Often |
title_full_unstemmed |
ILP: Compute Once, Reuse Often |
title_sort |
ILP: Compute Once, Reuse Often |
author |
Nuno A. Fonseca |
author_facet |
Nuno A. Fonseca Ricardo Rocha Rui Camacho Vítor Santos Costa |
author_role |
author |
author2 |
Ricardo Rocha Rui Camacho Vítor Santos Costa |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Nuno A. Fonseca Ricardo Rocha Rui Camacho Vítor Santos Costa |
dc.subject.por.fl_str_mv |
Engenharia do conhecimento, Engenharia electrotécnica, electrónica e informática Knowledge engineering, Electrical engineering, Electronic engineering, Information engineering |
topic |
Engenharia do conhecimento, Engenharia electrotécnica, electrónica e informática Knowledge engineering, Electrical engineering, Electronic engineering, Information engineering |
description |
Inductive Logic Programming (ILP) is a powerful and welldeveloped abstraction for multi-relational data mining techniques. However, ILP systems are not particularly fast, most of their execution time is spent evaluating the hypotheses they construct. The evaluation time needed to assess the quality of each hypothesis depends mainly on the number of examples and the theorem proving effort required to determine if an example is entailed by the hypothesis. We propose a technique that reduces the theorem proving effort to a bare minimum and stores valuable information to compute the number of examples entailed by each hypothesis (using a tree data structure). The information is computed only once (pre-compiled) per example. Evaluation of hypotheses requires only basic and efficient operations on trees. This proposal avoids re-computation of hypothesis value in theory-level search and cross-validation algorithms, whenever the same data set is used with different parameters. In an empirical evaluation the technique yielded considerable speedups. |
publishDate |
2007 |
dc.date.none.fl_str_mv |
2007 2007-01-01T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/book |
format |
book |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://hdl.handle.net/10216/67388 |
url |
https://hdl.handle.net/10216/67388 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799135937957986304 |