Fuzzy context-free languages—Part 2: Recognition and parsing algorithms
نویسندگان
چکیده
منابع مشابه
Fuzzy context-free languages - Part 2: Recognition and parsing algorithms
In a companion paper [9] we used fuzzy context-free grammars in order to model grammatical errors resulting in erroneous inputs for robust recognizing and parsing algorithms for fuzzy context-free languages. In particular, this approach enables us to distinguish between small errors (“tiny mistakes”) and big errors (“capital blunders”). In this paper we present some algorithms to recognize fuzz...
متن کاملTowards Robustness in Parsing - Fuzzifying Context-Free Language Recognition
− We discuss the concept of robustness with respect to parsing a context-free language. Our approach is based on the notions of fuzzy language, (generalized) fuzzy context-free grammar and parser / recognizer for fuzzy languages. As concrete examples we consider a robust version of Cocke−Younger−Kasami’s algorithm and a robust kind of recursive descent recognizer.
متن کاملParsing of Context Free Languages
Parsing is the process of assigning structure to sentences The structure is obtained from the grammatical description of the language Both in Com puter Science and in Computational Linguistics context free grammars and associated parsing algorithms are among the most useful tools Numerous parsing algorithms have been developed Special subclasses of the context free grammars have been introduced...
متن کاملParsing Beyond Context-Free Grammars
The first € price and the £ and $ price are net prices, subject to local VAT. Prices indicated with * include VAT for books; the €(D) includes 7% for Germany, the €(A) includes 10% for Austria. Prices indicated with ** include VAT for electronic products; 19% for Germany, 20% for Austria. All prices exclusive of carriage charges. Prices and other details are subject to change without notice. Al...
متن کاملParsing with Context - Free Grammars and WordStatistics
We present a language model in which the probability of a sentence is the sum of the individual parse probabilities, and these are calculated using a probabilistic context-free grammar (PCFG) plus statistics on individual words and how they t into parses. We have used the model to improve syntactic disambiguation. After training on Wall Street Journal (WSJ) text we tested on about 200 WSJ sente...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Theoretical Computer Science
سال: 2005
ISSN: 0304-3975
DOI: 10.1016/j.tcs.2005.06.013