Younger, D. H., 1967: Recognition and parsing of context-free languages in time n3. Information and Control, 10(2), 189--208.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....the corresponding string expression (c) in Figure 6 is derived. The string is parsed by a CFG parser with the input grammar of the SDTT, and the parsing tree (e) in Figure 7 is derived. Note that this parsing can be performed at worst in O(n 3 ) time in terms of the length of the input string [12]. Next, using the input parse tree and the rules of the SDTT, the output parse tree (f) in Figure 7 is obtained. The terminalassociations are shown by dotted lines in Figure 7. From the output string (d) in Figure 6 obtained from the output parse tree, the output tree structure is constructed. ....

D. H. Younger, `Recognition and parsing of context-free languages in time n3', Information and Control, 10(2), 189--208, (1967).

.... IFDS problems include the classic gen kill bit vector problems, as well as many other non gen kill problems, such as possibly uninitialized variables, truly live variables, and copy constant propagation [27] As is well known, context free languages require O(n ) time to recognize in general [32], and Reps argues that this provides important theoretical insight into why certain program analyses require O(n ) algorithms. Context free languages can be recognized in sub cubic time if the graph is acyclic [31] but this is rarely the case in program analysis. Algorithm A can neither ....

D.H. Younger. Recognition and parsing of contextfree languages in time n . Inf. and Cont., 10:189--208, 1967.

....However, restrictions under which parsing becomes polynomial have been studied by Lautemann, Vogler, and Drewes [18, 24, 3] Let us discuss the way in which the algorithm by Lautemann can be used. The algorithm is a generalization of the well known parsing algorithm by Cocke, Kasami, and Younger [25]. It can be reformulated in such a way that it returns a representation of all derivation trees of the (plain) input graph. Since there may be exponentially many derivation trees, sharing is used to represent them on polynomial space. In other words, the returned representation of the forest of ....

D. H. Younger. Recognition and parsing of context-free languages in time n . Information and Control, 10:189-208, 1967.

....lack of restriction can lead to the definition of complex systems is given in the following. In [Seki et al., 1989] a tabular method has been presented for the recognition of general LCFR languages as a generalization of the well known CYK algorithm for the recognition of CFG s (see for in stance [Younger, 1967] and [Aho and Ullman, 1972] In the following we will apply such a general method to the recognition of LCFRS(2) with the aim of hav ing an intuitive understanding of why it might be difficult to parse unrestricted crossing configurations. Let w be an input string of length n. In Figure 2, the ....

D. H. Younger. Recognition and parsing of context-free languages in time n s . Information and Control, 10:189-208, 1967. 95

....implemented for Picky is similar to carl s scoring model, the context earl probabilistic arley style parser ( Earl) icky probabilistic CKY like parser (V CKY) 2Some familiarity with chart parsing terminology is ,sumed in this paper. For terminological definitions, see [91, t0] 11] or [17]. 3Sections 2 a(I 3, the descriptions of the probabilistic models used in Picky and the icky algorithm, are similar in content to the corresl)Onding sections of Magerman and Weh [13] The experimental results and discussions which fi:dlov in sections 4 6 are ,riginal. 4O free grammar with ....

....grammars. One might questiou the need for a new algorithm to deal with context sensitive probabilistic models. However, these previons efforts have generally fa. iled to address both efficiency aud robusthess effectively. For non pro13abilistic grammar models, the CKY algorithm [9] [17] provides efficiency and robustness in polynomial time, O(G,3) CKY can be modified to hah die simple P CFGs [2] without loss of efficiency. How ever, with the introduction of context sensitive proba bility models, such as the history based grammar[I] and the CFG with CSP models[12] CKY cannot ....

Younger, D. H. 1967. Recognition and Parsing of Context-Free Languages in Time n s. Information and Control Vol. 10, No. 2, pp. 189-208.

.... at the intermediate points of a query, and (3) various authors [20, 21] have given experimental support for the practical efficiency of left corner parsers relative to that of chart parsers even though the latter have better (n as opposed to exponential) worst case complexity bounds [22, 23, 24]. However, initial attempts to modify Petrick s left corner parser to let it accept terminal symbols (words) in a strictly sequential, word at a time fashion proved harder than expected. This was due to the organization of the parser with respect to its handling of non determinism. Its ....

Younger, D. "Recognition and Parsing of Context-Free Language in Time n ." Information and Control 10 (1967): 189-208.

....(c) A BCf, d) AfoBC, e)Afoa, 0 A a The question whether the class of languages generated by DI CNF grammars is a proper or improper subclass of the DI languages will be left open. In considering the recognition of DI CNF grammars an extension of the CKY algorithm for CFC, s (lCsami, 1965; Younger, 1967) will be used which is essentially 365 inspired by an idea of Vijay Shanker and Weir in (Vijay Shanker and Weir, 1991) Let the n(n 1) 2 cells of a CKY table for an input of length n be indexed by i and j (li j u) in such a manner that cell Zi, j builds the top of a pyramid the base of which ....

D. H. Younger. Recognitio_n and parsing context-free languages in time n 3. Inf Con- trol, 10, 189-208. 367

....factored representation produced directly by the algorithm. After the inference component produces the semantic structure sequences corresponding to the non linguistic input, the parser produces the syntactic structure sequences corresponding to the linguistic input. A variant of the CKY algorithm[8, 19] is used to produce factored parse trees. Finally, the linker is applied in reverse to each corresponding parse tree semantic structure pair. This inverse linking process is termed fracturing. Fracturing is a recursive process applied to a parse tree fragment and a conceptual structure fragment. ....

D. H. Younger. Recognition and parsing of context-free languages in time O(n ). Information and Control, 10(2):189--208, 1967.

....a model for a restricted subclass of molecules which gives an e#cient approximate solution to this problem. The goal of this paper is to show how Chen and Dill s model can be translated into a context free grammar (CFG) so that their algorithm reduces to a variant of the CKY parsing algorithm [7, 14]. This formulation clarifies the structure of the algorithm, leading to a revised complexity analysis and an optimization in one case, and lays a formal foundation for generalizing this method to more complex cases using, for example, tree adjoining grammars [4, 6] Molecules like RNAs or ....

Daniel H. Younger. Recognition and parsing of context-free languages in time n . Information and Control, 10(2):189--208, 1967.

....sense, a grammar must be able to capture all possible meanings in order to be used in linguistic applications, and thus must be ambiguous. A number of parsing algorithms for general context free languages have been developed [11] the most common of them are the Cocke Kasami Younger algorithm [6, 16] for grammars in Chomsky normal form that constructs a square table of sets of nonterminals that derive all possible substrings of the input string, the Earley algorithm [4] for arbitrary grammars that uses quite complicated data structures, and one more tabular algorithm due to Graham, Harrison ....

D. H. Younger, \Recognition and parsing of context-free languages in time n ", Information and Control, 10 (1967), 189-208.

....a parser enumerates possibT parse trees usingb ottom up chart parsing for CFG which isobT7 L , b y the compiler. The remaining constraints whichcannotb ecovered with the CFG are solved at Phase 2. This paper describ es a parallel parsing algorithm for Phase 1. We chose the CKY algorithm[4][5] as ab asis of our parallel CFG parsing algorithm. A parallel CKY algorithm isdesirabTw from the viewpoints of speedup,distribT] tion of data and memory efficiency. The next section describ es the sequential CKY algorithm. Section 3 describ es our parallel CKY algorithm. The effectiveness ....

D.H. Younger. Recognition and parsing of context-free languages in time n 3 . Information and Control, 2(10):189--208, 1967.

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Younger, D. H., 1967: Recognition and parsing of context-free languages in time n3. Information and Control, 10(2), 189--208.

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Younger, D. (1967). Recognition and Parsing of Context-Free Languages in Time n 3 . Information and Control, 10(2):189--208.

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D. H. Younger. Recognition and parsing of context-free languages in time n

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D. H. Younger. Recognition and Parsing of Context-free Languages in time n

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D. H. Younger. Recognition and parsing of context-free languages in time n

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D.H. Younger. Recognition and parsing of context-free languages in time . Information and Control, 10:609--617, 1967.

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D. H. Younger. Recognition and Parsing of Context-free Languages in time n . Information and Control, 10:189-208, 1967. 11

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D. H. Younger. Recognition and parsing of context-free languages in time n . Information and Control, 10(2):189-208, 1967. 10

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D. H. Younger. Recognition and parsing of context-free languages in time n . Information and Control, 10:189--208, 1967.

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D. H.Younger, Recognition and Parsing of Context-freeLanguages in Time n ,Informationand Control (1967) 10,pp. 189--208.

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Younger, D. Recognition and parsing of context-free languages in time n . Inf. and Cont. 10 (1967), 189--208.

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Younger, D., Recognition and parsing of context-free language in time n3, Information and Control 10 (1967) 189-208.

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David H. Younger 1967. "Recognition and Parsing of Context-Free Languages in Time n s" . In Information and Control 10(), pp. 189-208.

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D. H. Younger. Recognition and parsing of context-free languages in time O(nS). Informa- tion and Control, 10(2):189-208, 1967.

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