Book ChapterDOI
Automatic Web Data Extraction Based on Genetic Algorithms and Regular Expressions
David F. Barrero,David Camacho,María D. R-Moreno +2 more
- pp 143-154
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TLDR
This chapter proposes an Evolutionary Computation approach to the problem of automatically learn software entities based on Genetic Algorithms and regular expressions, also called wrappers, that will be able to extract some kind of Web data structures from examples.Abstract:
Data Extraction from the World Wide Web is a well known, unsolved, and critical problem when complex information systems are designed. These problems are related to the extraction, management and reuse of the huge amount ofWeb data available. These data usually has a high heterogeneity, volatility and low quality (i.e. format and content mistakes), so it is quite hard to build reliable systems. This chapter proposes an Evolutionary Computation approach to the problem of automatically learn software entities based on Genetic Algorithms and regular expressions. These entities, also called wrappers, will be able to extract some kind of Web data structures from examples.read more
Citations
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Automatic Synthesis of Regular Expressions from Examples
TL;DR: A system that can produce regular expressions from user-provided examples performed with high precision and recall in 12 text-extraction tasks from real-world datasets, demonstrating the effectiveness of text extraction based on genetic programming.
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Book ChapterDOI
Learning Text Patterns Using Separate-and-Conquer Genetic Programming
TL;DR: This work considers the problem of extracting text slices that adhere to a syntactic pattern and proposes an approach capable of generating the desired pattern automatically, from a few annotated examples, based on Genetic Programming and generates extraction patterns in the form of regular expressions that may be input to existing engines without any post-processing.
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Playing regex golf with genetic programming
TL;DR: This paper generates a population of candidate regular expressions represented as trees and evolves such population based on a multi-objective fitness which minimizes the errors and the length of the regular expression.
References
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