Topic
Approximate string matching
About: Approximate string matching is a research topic. Over the lifetime, 1903 publications have been published within this topic receiving 62352 citations. The topic is also known as: fuzzy string-searching algorithm & fuzzy string-matching algorithm.
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TL;DR: A new design pattern matching method based on fuzzy is presented, in which matrix model is used for describing both design pattern and source code, and design pattern's static and dynamic information is defined as fuzzy attribute value for measuring the matching degree.
Abstract: Mining design patterns from source code is significant for improving the intelligibility and maintainability of software In this paper, we present a new design pattern matching method based on fuzzy, in which matrix model is used for describing both design pattern and source code, and design pattern's static and dynamic information is defined as fuzzy attribute value for measuring the matching degree Experiments on three open-source projects demonstrate the accuracy and efficiency of the proposed methodology
8 citations
05 Dec 2012
TL;DR: This paper presents a novel approach to constructing text indexes capable of efficiently supporting approximate search queries, relying on a new variant of the Context Bound Burrows-Wheeler Transform (k-bwt), referred to as the Variable Depth Burrows - Wheeler Transform (v- bwt).
Abstract: Approximate pattern matching is an important computational problem with a wide variety of applications in Information Retrieval. Efficient solutions to approximate pattern matching can be applied to natural language keyword queries with spelling mistakes, OCR scanned text incorporated into indexes, language model ranking algorithms based on term proximity, or DNA databases containing sequencing errors. In this paper, we present a novel approach to constructing text indexes capable of efficiently supporting approximate search queries. Our approach relies on a new variant of the Context Bound Burrows-Wheeler Transform (k-bwt), referred to as the Variable Depth Burrows-Wheeler Transform (v-bwt). First, we describe our new algorithm, and show that it is reversible. Next, we show how to use the transform to support efficient text indexing and approximate pattern matching. Lastly, we empirically evaluate the use of the v-bwt for DNA and English text collections, and show a significant improvement in approximate search efficiency over more traditional q-gram based approximate pattern matching algorithms.
8 citations
01 Jan 2007
TL;DR: A new method is presented to compute a combinatorial shift function (“best matching shift”) of the well-known Boyer–Moore string matching algorithm, which is shown to be the most efficient in particular cases such as the search for patterns of length from 7 to 15 in natural language texts.
Abstract: String matching is the problem of finding all the occurrences of a pattern in a text. We present a new method to compute a combinatorial shift function (“best matching shift”) of the well-known Boyer–Moore string matching algorithm. Moreover we conduct experiments showing that the algorithm using this best matching shift is the most efficient in particular cases such as the search for patterns of length from 7 to 15 in natural language texts.
8 citations
Proceedings Article•
01 Jan 2004
TL;DR: The exact string matching problem is to find all the occurrences of a given pattern x=x 1 x 2 ··· x m in a large text y=y 1 y 2··· y n, where both x and y are sequences of symbols drawn from a finite character set Σ of size σ.
8 citations