Text sparsification via local maxima

被引：0
|
作者：
Crescenzi, P
Del Lungo, A
Grossi, R
Lodi, E
Pagli, L
Rossi, G
机构：
[1] Univ Florence, Dipartimento Sistemi & Informat, I-50134 Florence, Italy
[2] Univ Siena, Dipartimento Matemat, I-53100 Siena, Italy
[3] Univ Pisa, Dipartimento Informat, I-56125 Pisa, Italy
来源：
FST TCS 2000: FOUNDATIONS OF SOFTWARE TECHNOLOGY AND THEORETICAL COMPUTER SCIENCE, PROCEEDINGS | 2000年 / 1974卷
关键词：
D O I：
暂无
中图分类号：
TP31 [计算机软件];
学科分类号：
081202 ; 0835 ;
摘要：
In this paper, we investigate a text sparsification technique based on the identification of local maxima. In particular, we first show that looking for an order of the alphabet symbols that minimizes the number of local maxima in a given string is an NP-hard problem. Successively, we describe how the local maxima sparsification technique can be used to filter the access to unstructured texts. Finally, we experimentally show that this approach can be successfully used in order to create a space efficient index for searching a DNA sequence as quickly as a full index.
引用
收藏
页码：290 / 301
页数：12
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