We present a divide-and-conquer algorithm for parsing context-free languages efficiently. Our algorithm is an instance of Valiant's (1975), who reduced the problem of parsing to matrix multiplications. We show that, while the conquer step of Valiant's is O(n^3), it improves to O(\log^2 n) under certain conditions satisfied by many useful inputs that occur in practice, and if one uses a sparse representation of matrices. The improvement happens because the multiplications involve an overwhelming majority of empty matrices. This result is relevant to modern computing: divide-and-conquer algorithms with a polylogarithmic conquer step can be parallelised relatively easily
We present an algorithm for incremental statistical parsing with Parallel Multiple Context-Free Gram...
AbstractEfficient parallel algorithms for some parsing problems are presented. These problems includ...
Kosaraju [Kosaraju 69] and independently ten years later, Guibas, Kung and Thompson [Guibas 79] dev...
We present a divide-and-conquer algorithm for parsing context-free languages efficiently. Our algori...
We present a divide-and-conquer algorithm for parsing context-free languages efficiently. Our algori...
We present a divide-and-conquer algorithm for parsing context-free languages efficiently. Our algori...
A parallel parsing technique is presented in which parentheses are inserted in the string to be pars...
: Valiant proposed an O(n 2 ) time algorithm which reduces the recognition problem for context-fre...
AbstractLet T(n) be the time to recognize context-free languages on a parallel random-access machine...
A new parallel parsing algorithm for block structured languages, capable of parsing incremen- tally ...
The paper presents an efficiently parallel parsing algorithm for arbitrary contextfree grammars. Thi...
. In this paper we present algorithms for parsing general Tree Adjoining Languages (TALs). Tree Adjo...
Using recent improvements to Valiant’s algorithm for parsing contextfree languages, we present an im...
The well-known parsing algorithm for context-free grammars due to Valiant (“General context-free rec...
We present an algorithm for incremental statistical parsing with Parallel Multiple Context-Free Gram...
We present an algorithm for incremental statistical parsing with Parallel Multiple Context-Free Gram...
AbstractEfficient parallel algorithms for some parsing problems are presented. These problems includ...
Kosaraju [Kosaraju 69] and independently ten years later, Guibas, Kung and Thompson [Guibas 79] dev...
We present a divide-and-conquer algorithm for parsing context-free languages efficiently. Our algori...
We present a divide-and-conquer algorithm for parsing context-free languages efficiently. Our algori...
We present a divide-and-conquer algorithm for parsing context-free languages efficiently. Our algori...
A parallel parsing technique is presented in which parentheses are inserted in the string to be pars...
: Valiant proposed an O(n 2 ) time algorithm which reduces the recognition problem for context-fre...
AbstractLet T(n) be the time to recognize context-free languages on a parallel random-access machine...
A new parallel parsing algorithm for block structured languages, capable of parsing incremen- tally ...
The paper presents an efficiently parallel parsing algorithm for arbitrary contextfree grammars. Thi...
. In this paper we present algorithms for parsing general Tree Adjoining Languages (TALs). Tree Adjo...
Using recent improvements to Valiant’s algorithm for parsing contextfree languages, we present an im...
The well-known parsing algorithm for context-free grammars due to Valiant (“General context-free rec...
We present an algorithm for incremental statistical parsing with Parallel Multiple Context-Free Gram...
We present an algorithm for incremental statistical parsing with Parallel Multiple Context-Free Gram...
AbstractEfficient parallel algorithms for some parsing problems are presented. These problems includ...
Kosaraju [Kosaraju 69] and independently ten years later, Guibas, Kung and Thompson [Guibas 79] dev...