Enrique Alfonseca

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Enrique Alfonseca is an author.


Only those publications related to wikis are shown here.
Title Keyword(s) Published in Language DateThis property is a special property in this wiki. Abstract R C
WHAD: Wikipedia historical attributes data: Historical structured data extraction and vandalism detection from the Wikipedia edit history Attributes
Temporal data
Language Resources and Evaluation English 2013 This paper describes the generation of temporally anchored infobox attribute data from the Wikipedia history of revisions. By mining (attribute, value) pairs from the revision history of the English Wikipedia we are able to collect a comprehensive knowledge base that contains data on how attributes change over time. When dealing with the Wikipedia edit history, vandalic and erroneous edits are a concern for data quality. We present a study of vandalism identification in Wikipedia edits that uses only features from the infoboxes, and show that we can obtain, on this dataset, an accuracy comparable to a state-of-the-art vandalism identification method that is based on the whole article. Finally, we discuss different characteristics of the extracted dataset, which we make available for further study. 0 0
Information Extraction and Semantic Annotation of Wikipedia Relation Extraction
Semantic annotation
English 2008 0 0
Automatising the learning of lexical patterns: An application to the enrichment of WordNet by extracting semantic relationships from Wikipedia Information extraction
Lexical patterns
Ontology and thesaurus acquisition
Relation extraction
Data Knowl. Eng. English 2007 0 0
From Wikipedia to Semantic Annotations: automatic relationship extraction Annotation semantic text-mining wikipedia 1st Workshop on Semantic Wikis:, 2006. 2006 0 0
FromWikipedia to semantic relationships: A semi-automated annotation approach? CEUR Workshop Proceedings English 2006 In this paper, an experiment is presented for the automatic annotation of several semantic relationships in the Wikipedia, a collaborative on-line encyclopedia. The procedure is based on a methodology for the automatic discovery and generalisation of lexical patterns that allows the recognition of relationships among concepts. This methodology requires as information source any written, general-domain corpora and applies natural language processing techniques to extract the relationships from the textual corpora. It has been tested with eight different relations from the Wikipedia corpus. 0 0
Automatic Extraction of Semantic Relationships for WordNet by Means of Pattern Learning from Wikipedia Natural Language Processing and Information Systems English 2005 This paper describes an automatic approach to identify lexical patterns which represent semantic relationships between concepts, from an on-line encyclopedia. Next, these patterns can be applied to extend existing ontologies or semantic networks with new relations. The experiments have been performed with the Simple English Wikipedia and WordNet 1.7. A new algorithm has been devised for automatically generalising the lexical patterns found in the encyclopedia entries. We have found general patterns for the hyperonymy, hyponymy, holonymy and meronymy relations and, using them, we have extracted more than 1200 new relationships that did not appear in WordNet originally. The precision of these relationships ranges between 0.61 and 0.69, depending on the relation. 0 1
Automatic assignment of Wikipedia encyclopedic entries to WordNet synsets Lecture Notes in Computer Science English 2005 We describe an approach taken for automatically associating entries from an on-line encyclopedia with concepts in an ontology or a lexical semantic network. It has been tested with the Simple English Wikipedia and WordNet, although it can be used with other resources. The accuracy in disambiguating the sense of the encyclopedia entries reaches 91.11% (83.89% for polysemous words). It will be applied to enriching ontologies with encyclopedic knowledge. 0 1
Automatic assignment of wikipedia encyclopedic entries to wordnet synsets AWIC English 2005 0 1