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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Bidirectional parsing

Andrei, Ştefan. January 2000 (has links) (PDF)
Hamburg, University, Diss., 2000.
2

Syntaktische Fehlerkorrektur mit minimalen Kosten für deterministische Grammatiken

May, Ralf. January 2002 (has links) (PDF)
Bochum, Universiẗat, Diss., 2002.
3

Learning probabilistic grammars for language modeling

Carroll, Glenn R. January 1995 (has links)
Providence, RI, Brown Univ., Diss., 1995.
4

Ambiguity of context-free languages as a function of the word length

Naji, Mohamed Unknown Date (has links)
Univ., Diplomarbeit, 1998--Frankfurt (Main) / Englische Fassung der Diplomarbeit "Grad der Mehrdeutigkeit kontextfreier Grammatiken und Sprachen"
5

Treebank refinement optimising representations of syntactic analyses for probabilistic context-free parsing /

Ule, Tylman. January 2007 (has links)
Tübingen, Univ., Diss., 2007.
6

Eine Rekonstruktion der LR-Theorie zur Elimination von Redundanz mit Anwendung auf den Bau von ELR-Parsern

Kannapinn, Sönke. Unknown Date (has links) (PDF)
Techn. Universiẗat, Diss., 2001--Berlin.
7

Consistency of Probabilistic Context-Free Grammars

Stüber, Torsten 10 May 2012 (has links) (PDF)
We present an algorithm for deciding whether an arbitrary proper probabilistic context-free grammar is consistent, i.e., whether the probability that a derivation terminates is one. Our procedure has time complexity $\\\\mathcal O(n^3)$ in the unit-cost model of computation. Moreover, we develop a novel characterization of consistent probabilistic context-free grammars. A simple corollary of our result is that training methods for probabilistic context-free grammars that are based on maximum-likelihood estimation always yield consistent grammars.
8

Consistency of Probabilistic Context-Free Grammars

Stüber, Torsten 10 May 2012 (has links)
We present an algorithm for deciding whether an arbitrary proper probabilistic context-free grammar is consistent, i.e., whether the probability that a derivation terminates is one. Our procedure has time complexity $\\\\mathcal O(n^3)$ in the unit-cost model of computation. Moreover, we develop a novel characterization of consistent probabilistic context-free grammars. A simple corollary of our result is that training methods for probabilistic context-free grammars that are based on maximum-likelihood estimation always yield consistent grammars.

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