Evaluation of fast spoken term detection using a suffix array

2011 ◽  
Author(s):  
Kouichi Katsurada ◽  
Shinta Sawada ◽  
Shigeki Teshima ◽  
Yurie Iribe ◽  
Tsuneo Nitta
Keyword(s):  
Suffix Array ◽  
Spoken Term Detection

Acceleration of spoken term detection using a suffix array by assigning optimal threshold values to sub-keywords

2013 ◽  
Author(s):  
Kouichi Katsurada ◽  
Seiichi Miura ◽  
Kheang Seng ◽  
Yurie Iribe ◽  
Tsuneo Nitta
Keyword(s):  
Suffix Array ◽  
Optimal Threshold ◽  
Threshold Values ◽  
Spoken Term Detection

An Efficient Tool for Searching Maximal and Super Maximal Repeats in Large DNA/Protein Sequences via Induced-Enhanced Suffix Array

2019 ◽  
Vol 12 (2) ◽  
pp. 128-134
Author(s):  
Sanjeev Kumar ◽  
Suneeta Agarwal ◽  
Ranvijay
Keyword(s):  
Protein Sequences ◽  
Input Sequence ◽  
Suffix Array ◽  
Secondary Memory ◽  
Time And Space ◽  
Efficient Tool ◽  
Frequency Distributions ◽  
Alignment Algorithms ◽  
Common Prefix ◽  
Art Works

Background: DNA and Protein sequences of an organism contain a variety of repeated structures of various types. These repeated structures play an important role in Molecular biology as they are related to genetic backgrounds of inherited diseases. They also serve as a marker for DNA mapping and DNA fingerprinting. Efficient searching of maximal and super maximal repeats in DNA/Protein sequences can lead to many other applications in the area of genomics. Moreover, these repeats can also be used for identification of critical diseases by finding the similarity between frequency distributions of repeats in viruses and genomes (without using alignment algorithms). Objective: The study aims to develop an efficient tool for searching maximal and super maximal repeats in large DNA/Protein sequences. Methods: The proposed tool uses a newly introduced data structure Induced Enhanced Suffix Array (IESA). IESA is an extension of enhanced suffix array. It uses induced suffix array instead of classical suffix array. IESA consists of Induced Suffix Array (ISA) and an additional array-Longest Common Prefix (LCP) array. ISA is an array of all sorted suffixes of the input sequence while LCP array stores the lengths of the longest common prefixes between all pairs of consecutive suffixes in an induced suffix array. IESA is known to be efficient w.r.t. both time and space. It facilitates the use of secondary memory for constructing the large suffix-array. Results: An open source standalone tool named MSR-IESA for searching maximal and super maximal repeats in DNA/Protein sequences is provided at https://github.com/sanjeevalg/MSRIESA. Experimental results show that the proposed algorithm outperforms other state of the art works w.r.t. to both time and space. Conclusion: The proposed tool MSR-IESA is remarkably efficient for the analysis of DNA/Protein sequences, having maximal and super maximal repeats of any length. It can be used for identification of well-known diseases.

Suffix array for multi-pattern matching with variable length wildcards

2021 ◽  
Vol 25 (2) ◽  
pp. 283-303
Author(s):  
Na Liu ◽  
Fei Xie ◽  
Xindong Wu
Keyword(s):  
Dynamic Programming ◽  
Data Structure ◽  
Pattern Matching ◽  
Edit Distance ◽  
State Of The Art ◽  
Suffix Array ◽  
Variable Length ◽  
Distance Method ◽  
Efficient Data ◽  
Comparison Algorithms

Approximate multi-pattern matching is an important issue that is widely and frequently utilized, when the pattern contains variable-length wildcards. In this paper, two suffix array-based algorithms have been proposed to solve this problem. Suffix array is an efficient data structure for exact string matching in existing studies, as well as for approximate pattern matching and multi-pattern matching. An algorithm called MMSA-S is for the short exact characters in a pattern by dynamic programming, while another algorithm called MMSA-L deals with the long exact characters by the edit distance method. Experimental results of Pizza & Chili corpus demonstrate that these two newly proposed algorithms, in most cases, are more time-efficient than the state-of-the-art comparison algorithms.

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