LPG–PCFG: An Improved Probabilistic Context- Free Grammar to Hit Low-Probability Passwords [PDF]
Sensors, 2022 With the development of the Internet, information security has attracted more attention. Identity authentication based on password authentication is the first line of defense; however, the password-generation model is widely used in offline password ...
Xiaozhou Guo +4 more
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A stochastic context free grammar based framework for analysis of protein sequences [PDF]
BMC Bioinformatics, 2009 Background In the last decade, there have been many applications of formal language theory in bioinformatics such as RNA structure prediction and detection of patterns in DNA.
Nebel Jean-Christophe, Dyrka Witold
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MolGramTreeNet: A multimodal molecular property prediction model via grammar tree-constrained molecular representation [PDF]
iScienceSummary: Molecular property prediction is pivotal for drug discovery. However, existing methods that rely on linear SMILES or 2D graphs often overlook explicit hierarchical structures and chemical grammar constraints.
Yekang Zhang +7 more
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Cross-Domain Feature Enhancement-Based Password Guessing Method for Small Samples [PDF]
EntropyAs a crucial component of account protection system evaluation and intrusion detection, the advancement of password guessing technology encounters challenges due to its reliance on password data. In password guessing research, there is a conflict between
Cheng Liu +7 more
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Learning of Structurally Unambiguous Probabilistic Grammars [PDF]
Logical Methods in Computer Science, 2023 The problem of identifying a probabilistic context free grammar has two aspects: the first is determining the grammar's topology (the rules of the grammar) and the second is estimating probabilistic weights for each rule.
Dana Fisman +2 more
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Split-Based Algorithm for Weighted Context-Free Grammar Induction
Applied Sciences, 2021 The split-based method in a weighted context-free grammar (WCFG) induction was formalised and verified on a comprehensive set of context-free languages. WCFG is learned using a novel grammatical inference method. The proposed method learns WCFG from both
Mateusz Gabor +2 more
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Learning Cover Context-Free Grammars from Structural Data [PDF]
Scientific Annals of Computer Science, 2014 We consider the problem of learning an unknown context-free gram- mar from its structural descriptions with depth at most ℓ. The structural descriptions of the context-free grammar are its unlabelled derivation trees. The goal is to learn a cover context-
M. Marin, G. Istrate
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Grammar Compression with Probabilistic Context-Free Grammar [PDF]
2020 Data Compression Conference (DCC), 2020 We propose a new approach for universal lossless text compression, based on grammar compression. In the literature, a target string $T$ has been compressed as a context-free grammar $G$ in Chomsky normal form satisfying $L(G) = \{T\}$. Such a grammar is often called a \emph{straight-line program} (SLP).
Naganuma, Hiroaki +4 more
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Undecidable problems concerning densities of languages [PDF]
Discrete Mathematics & Theoretical Computer Science, 2005 In this paper we prove that the question whether a language presented by a context free grammar has density, is undecidable. Moreover we show that there is no algorithm which, given two unambiguous context free grammars on input, decides whether the ...
Jakub Kozik
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A Context-Free Grammar Associated with Fibonacci and Lucas Sequences
Journal of Mathematics, 2023 We introduce a context-free grammar G=s⟶s+d,d⟶s to generate Fibonacci and Lucas sequences. By applying the grammar G, we give a grammatical proof of the Binet formula.
Harold Ruilong Yang
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