{"title":"Learning Cover Context-Free Grammars from Structural Data","authors":"M. Marin, Gabriel Istrate","doi":"10.7561/SACS.2014.2.253","DOIUrl":null,"url":null,"abstract":"We consider the problem of learning an unknown context-free grammar when the only knowledge available and of interest to the learner is about its structural descriptions with depth at most l. The goal is to learn a cover context-free grammar (CCFG) with respect to l, that is, a CFG whose structural descriptions with depth at most l agree with those of the unknown CFG. We propose an algorithm, called LA l, that efficiently learns a CCFG using two types of queries: structural equivalence and structural membership. We show that LA l runs in time polynomial in the number of states of a minimal deterministic finite cover tree automaton (DCTA) with respect to l. This number is often much smaller than the number of states of a minimum deterministic finite tree automaton for the structural descriptions of the unknown grammar.","PeriodicalId":53862,"journal":{"name":"Scientific Annals of Computer Science","volume":"116 1","pages":"241-258"},"PeriodicalIF":0.5000,"publicationDate":"2014-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientific Annals of Computer Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.7561/SACS.2014.2.253","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, THEORY & METHODS","Score":null,"Total":0}
引用次数: 0
Abstract
We consider the problem of learning an unknown context-free grammar when the only knowledge available and of interest to the learner is about its structural descriptions with depth at most l. The goal is to learn a cover context-free grammar (CCFG) with respect to l, that is, a CFG whose structural descriptions with depth at most l agree with those of the unknown CFG. We propose an algorithm, called LA l, that efficiently learns a CCFG using two types of queries: structural equivalence and structural membership. We show that LA l runs in time polynomial in the number of states of a minimal deterministic finite cover tree automaton (DCTA) with respect to l. This number is often much smaller than the number of states of a minimum deterministic finite tree automaton for the structural descriptions of the unknown grammar.
期刊介绍：
Scientific Annals of Computer Science is an international journal devoted to papers in computer science with results which are formally stated and proved. It is mainly a forum for the dissemination of formal solutions of problems appearing in all areas of computer science. We only consider original work which has not been previously published in other journals, nor submitted simultaneously for publication elsewhere. Extended versions of papers which have previously appeared in conference proceedings are also considered; the authors should indicate this at the time of submission. Promoting quality over quantity, Scientific Annals of Computer Science does not consider papers outside the scope of the journal. Starting with volume 17, SACS becomes an open access journal without subscription. All articles are freely available online, offering an increased visibility and usage of their results.
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