Search (1 results, page 1 of 1)

  • × author_ss:"Martín-Moncunill, D."
  • × theme_ss:"Konzeption und Anwendung des Prinzips Thesaurus"
  1. Martín-Moncunill, D.; García-Barriocanal, E.; Sicilia, M.-A.; Sánchez-Alonso, S.: Evaluating the practical applicability of thesaurus-based keyphrase extraction in the agricultural domain : insights from the VOA3R project (2015) 0.01
    0.011183213 = product of:
      0.03354964 = sum of:
        0.03354964 = weight(_text_:search in 2106) [ClassicSimilarity], result of:
          0.03354964 = score(doc=2106,freq=2.0), product of:
            0.1747324 = queryWeight, product of:
              3.475677 = idf(docFreq=3718, maxDocs=44218)
              0.05027291 = queryNorm
            0.19200584 = fieldWeight in 2106, product of:
              1.4142135 = tf(freq=2.0), with freq of:
                2.0 = termFreq=2.0
              3.475677 = idf(docFreq=3718, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2106)
      0.33333334 = coord(1/3)
    
    Abstract
    The use of Knowledge Organization Systems (KOSs) in aggregated metadata collections facilitates the implementation of search mechanisms operating on the same term or keyphrase space, thus preparing the ground for improved browsing, more accurate retrieval and better user profiling. Automatic thesaurus-based keyphrase extraction appears to be an inexpensive tool to obtain this information, but the studies on its effectiveness are scattered and do not consider the practical applicability of these techniques compared to the quality obtained by involving human experts. This paper presents an evaluation of keyphrase extraction using the KEA software and the AGROVOC vocabulary on a sample of a large collection of metadata in the field of agriculture from the AGRIS database. This effort includes a double evaluation, the classical automatic evaluation based on precision and recall measures, plus a blind evaluation aimed to contrast the quality of the keyphrases extracted against expert-provided samples and against the keyphrases originally recorded in the metadata. Results show not only that KEA outperforms humans in matching the original keyphrases, but also that the quality of the keyphrases extracted was similar to those provided by humans.