Persona:
Araujo Serna, M. Lourdes

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ORCID
0000-0002-7657-4794
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Araujo Serna
Nombre de pila
M. Lourdes
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2010 - 20112
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Tipo de ítem: Publication × Tipo: actas de congreso × Tipo: conference proceedings ×

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Mostrando 1 - 2 de 2
  • Miniatura
    Publicación
    Identifying patterns for unsupervised grammar induction
    (2010-07-15) Santamaría, Jesús; Araujo Serna, M. Lourdes
    This paper describes a new method for unsupervised grammar induction based on the automatic extraction of certain patterns in the texts. Our starting hypothesis is that there exist some classes of words that function as separators, marking the beginning or the end of new constituents. Among these separators we distinguish those which trigger new levels in the parse tree. If we are able to detect these separators we can follow a very simple procedure to identify the constituents of a sentence by taking the classes of words between separators. This paper is devoted to describe the process that we have followed to automatically identify the set of separators from a corpus only annotated with Part-of-Speech (POS) tags. The proposed approach has allowed us to improve the results of previous proposals when parsing sentences fromtheWall Street Journal corpus.
  • Miniatura
    Publicación
    Analyzing information retrieval methods to recover broken web links
    (2011-06-19) Martínez Romo, Juan; Araujo Serna, M. Lourdes
    In this work we compare different techniques to automatically find candidate web pages to substitute broken links. We extract information from the anchor text, the content of the page containing the link, and the cache page in some digital library.The selected information is processed and submitted to a search engine. We have compared different information retrievalmethods for both, the selection of terms used to construct the queries submitted to the search engine, and the ranking of the candidate pages that it provides, in order to help the user to find the best replacement. In particular, we have used term frequencies, and a language model approach for the selection of terms; and cooccurrence measures and a language model approach for ranking the final results. To test the different methods, we have also defined a methodology which does not require the user judgments, what increases the objectivity of the results.