A Case Study on Grammatical-Based Representation for Regular Expression Evolution

González-Pardo, Antonio; Barrero, David F.; Camacho, David; R-Moreno, María D.

doi:10.1007/978-3-642-12433-4_45

Cited by 6 publications

(8 citation statements)

References 4 publications

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“…The study of extracting regexes that describe a given set of examples is not new. Different authors have used genetic algorithm to perform this task [10], [11], [12], nevertheless this work uses a different approach based on grammatical evolution to automatically generate regexes based on a defined grammar.…”

Section: Regexmentioning

confidence: 99%

Analysis of grammatical evolutionary approaches to regular expression induction

González-Pardo

Camacho

2011

2011 IEEE Congress of Evolutionary Computation (CEC)

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Regular expressions, or regexes, have been used traditionally as a pattern matching tool to search for structures in a set of objects, like files, text documents or folders. Pattern matching can be used to look for files whose name contains a given string, to search files that contain a specific pattern within them, or simply to extract text in a set of documents. It is very popular to apply regexes to detect and extract patterns that represent phone numbers, URLs, email addresses, etc. These kind of information can be characterized because it has a well defined structure. Nevertheless, regexes are not very frequently used because its high complexity in both, syntax and grammatical rules, makes regexes difficult to understand. For this reason, the development of programs able to automatically generate, and evaluate, regexes has become a valuable task. This work analyzes the performance of different grammatical evolutionary approaches in the generation of regexes able to extract URL patterns. Four different types of grammars have been evaluated: a context-free grammar, a context-free grammar with a penalized fitness function, an extensible context-free grammar, and a Christiansen grammar. For the considered problem, the experimental results show that the best performance of the system, measured as cumulative success rate, is achieved using Christiansen grammars.

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Section: Regexmentioning

confidence: 99%

Analysis of grammatical evolutionary approaches to regular expression induction

González-Pardo

Camacho

2011

2011 IEEE Congress of Evolutionary Computation (CEC)

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“…Several earlier works addressed the text extraction problem with evolutionary approaches, such as Genetic Algorithms (GA) [2,9] and Genetic Programming (GP) [19,7,18,3]. In [2], after an initial evolution, individuals are recombined and then selected to obtain the final regular expression.…”

Section: Related Workmentioning

confidence: 99%

“…In [2], after an initial evolution, individuals are recombined and then selected to obtain the final regular expression. In [9], the alphabet for regular expressions is chosen after a preliminary frequency analysis on the set of examples. Both proposals are evaluated on the task of URL extraction (composition and size of training and testing sets are not provided in [9]).…”

Section: Related Workmentioning

confidence: 99%

“…In [9], the alphabet for regular expressions is chosen after a preliminary frequency analysis on the set of examples. Both proposals are evaluated on the task of URL extraction (composition and size of training and testing sets are not provided in [9]). Methods based on GP encode regular expressions as GP trees and evolve the corresponding individuals-each individual being a candidate expression-to maximize effectiveness according to some metric [19,7,18].…”

Section: Related Workmentioning

confidence: 99%

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Automatic string replace by examples

Lorenzo

Medvet

Bartoli

2013

Proceedings of the 15th Annual Conference on Genetic and Evolutionary Computation

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Search-and-replace is a text processing task which may be largely automated with regular expressions: the user must describe with a specific formal language the regions to be modified (search pattern) and the corresponding desired changes (replacement expression). Writing and tuning the required expressions requires high familiarity with the corresponding formalism and is typically a lengthy, error-prone process.In this paper we propose a tool based on Genetic Programming (GP) for generating automatically both the search pattern and the replacement expression based only on examples. The user merely provides examples of the input text along with the desired output text and does not need any knowledge about the regular expression formalism nor about GP. We are not aware of any similar proposal. We experimentally evaluated our proposal on 4 different searchand-replace tasks operating on real-world datasets and found good results, which suggests that the approach may indeed be practically viable.

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“…In order to perform this task, regular expressions [13] have been used. In this way data like the messages sent between avatars, or the exact position of an event in the world, can be used [14].…”

Section: Data Extraction and Processingmentioning

confidence: 99%

Clustering avatars behaviours from virtual worlds interactions

Orgaz

R-Moreno

Camacho

et al. 2012

Proceedings of the 4th International Workshop on Web Intelligence &Amp; Communities - WI&C '12

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Esta es la versión de autor de la comunicación de congreso publicada en: This is an author produced version of a paper published in: In virtual world, the user (or avatar) can move and interact within an artificial world with a high degree of freedom. The movements and iterations of the avatar can be monitorized, and hence this information can be analysed to obtain interesting behavioural patterns. Usually, only the information related to the avatars conversations (textual chat logs) are directly available for processing. However, these open platforms allow to capture other kind of information like the exact position of an avatar in the VW, what they are looking at (eye-gazing) or which actions they perform inside these worlds. This paper studies how this information, can be extracted, processed and later used by clustering methods to detect behaviour or group formations in the world. To detect the behavioural patterns of the avatars considered, clustering techniques have been used. These techniques, using the correct data preprocessing and modelling, can be used to automatically detect hidden patterns from data.

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A Case Study on Grammatical-Based Representation for Regular Expression Evolution

Cited by 6 publications

References 4 publications

Analysis of grammatical evolutionary approaches to regular expression induction

Analysis of grammatical evolutionary approaches to regular expression induction

Automatic string replace by examples

Clustering avatars behaviours from virtual worlds interactions

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