Discovering taxonomies in Wikipedia by means of grammatical evolution
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- @Article{AraujoMF18,
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author = "Lourdes Araujo and Juan Martinez-Romo and
Andres Duque Fernandez",
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title = "Discovering taxonomies in {Wikipedia} by means of
grammatical evolution",
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journal = "Soft Computing",
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year = "2018",
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volume = "22",
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number = "9",
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pages = "2907--2919",
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keywords = "genetic algorithms, genetic programming, grammatical
evolution",
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URL = "https://doi.org/10.1007/s00500-017-2544-4",
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timestamp = "Sat, 05 May 2018 23:05:31 +0200",
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biburl = "https://dblp.org/rec/bib/journals/soco/AraujoMF18",
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DOI = "doi:10.1007/s00500-017-2544-4",
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abstract = "This work applies grammatical evolution to identify
taxonomic hierarchies of concepts from Wikipedia. Each
article in Wikipedia covers a topic and is cross-linked
by hyperlinks that connect related topics. Hierarchical
taxonomies and their generalization to ontologies are a
highly useful resource for many applications since they
enable semantic search and reasoning. Thus, the
automatic identification of taxonomies composed of
concepts associated with linked Wikipedia pages has
attracted much attention. We have developed a system
which arranges a set of Wikipedia concepts into a
taxonomy. This technique is based on the relationships
among a set of features extracted from the contents of
the Wikipedia pages. We have used a grammatical
evolution algorithm to discover the best way of
combining the considered features in an explicit
function. Candidate functions are evaluated by applying
a genetic algorithm to approximate the optimal taxonomy
that the function can provide for a number of training
cases. The fitness is computed as an average of the
precision obtained by comparing, for the set of
training cases, the taxonomy provided by the evaluated
function with the reference one. Experimental results
show that the proposal is able to provide valuable
functions to find high-quality taxonomies.",
- }
Genetic Programming entries for
Lourdes Araujo
Juan Martinez-Romo
Andres Duque Fernandez
Citations