Sentence examples for efficient string processing from inspiring English sources

This polynomial time complexity is achieved by manipulating a discretized version of the original matrix using efficient string processing techniques.

The polynomial time complexity is obtained by manipulating a discretized version of the original expression matrix and by using efficient string processing techniques based on suffix trees.

In this section we propose e-CCC-Biclustering, an algorithm designed to find and report all maximal CCC-Biclusters with approximate expression patterns (e-CCC-Biclusters) using a discretized matrix A and efficient string processing techniques.

First, the algorithm discretizes the matrix and then it works with string processing techniques based on suffix trees.

For the latter problem (Common Motifs Problem), several efficient algorithms based on string processing techniques have been proposed to date [ 25, 26].

A suffix tree, which provides us with a linear space full-text index of a given string, is a fundamental data structure for string processing and information retrieval.

Efficient string matching algorithms are therefore important for identifying theSe packets at line rate.

Current data management and information retrieval systems lack advanced string processing capabilities needed in string-oriented application areas like computational molecular biology.

Subword trees and DAWGs arise rather ubiquitously in applications of string processing, where they often play complementary roles.

This paper presents a memory and time efficient string matching algorithm specifically designed for NIMS on commodity processors.

Mentions output by BANNER are then subjected to additional string processing.