Maria Ruiz-Casado

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Maria Ruiz-Casado 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
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 & Knowledge Engineering , Issue 3 (June 2007) 2007 This paper describes Koru, a new search interface that offers effective domain-independent knowledge-based information retrieval. Koru exhibits an understanding of the topics of both queries and documents. This allows it to (a) expand queries automatically and (b) help guide the user as they evolve their queries interactively. Its understanding is mined from the vast investment of manual effort and judgment that is Wikipedia. We show how this open, constantly evolving encyclopedia can yield inexpensive knowledge structures that are specifically tailored to expose the topics, terminology and semantics of individual document collections. We conducted a detailed user study with 12 participants and 10 topics from the 2005 TREC HARD track, and found that Koru and its underlying knowledge base offers significant advantages over traditional keyword search. It was capable of lending assistance to almost every query issued to it; making their entry more efficient, improving the relevance of the documents they return, and narrowing the gap between expert and novice seekers. 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
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