Search (1 results, page 1 of 1)

  • × author_ss:"Calegari, S."
  • × theme_ss:"Wissensrepräsentation"
  1. Calegari, S.; Pasi, G.: Personal ontologies : generation of user profiles based on the YAGO ontology (2013) 0.02
    0.019369897 = product of:
      0.058109686 = sum of:
        0.058109686 = weight(_text_:search in 2719) [ClassicSimilarity], result of:
          0.058109686 = score(doc=2719,freq=6.0), product of:
            0.1747324 = queryWeight, product of:
              3.475677 = idf(docFreq=3718, maxDocs=44218)
              0.05027291 = queryNorm
            0.33256388 = fieldWeight in 2719, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              3.475677 = idf(docFreq=3718, maxDocs=44218)
              0.0390625 = fieldNorm(doc=2719)
      0.33333334 = coord(1/3)
    
    Abstract
    Personalized search is aimed at tailoring the search outcome to users; to this aim user profiles play an important role: the more faithfully a user profile represents the user interests and preferences, the higher is the probability to improve the search process. In the approaches proposed in the literature, user profiles are formally represented as bags of words, as vectors, or as conceptual taxonomies, generally defined based on external knowledge resources (such as the WordNet and the ODP - Open Directory Project). Ontologies have been more recently considered as a powerful expressive means for knowledge representation. The advantage offered by ontological languages is that they allow a more structured and expressive knowledge representation with respect to the above mentioned approaches. A challenging research activity consists in defining user profiles by a knowledge extraction process from an existing ontology, with the main aim of producing a semantically rich representation of the user interests. In this paper a method to automatically define a personal ontology via a knowledge extraction process from the general purpose ontology YAGO is presented; starting from a set of keywords, which are representatives of the user interests, the process is aimed to define a structured and semantically coherent representation of the user topical interests. In the paper the proposed method is described, as well as some evaluations that show its effectiveness.