Search (1 results, page 1 of 1)

  • × author_ss:"Alonso, M.A."
  • × theme_ss:"Multilinguale Probleme"
  1. Vilares, J.; Alonso, M.A.; Doval, Y.; Vilares, M.: Studying the effect and treatment of misspelled queries in Cross-Language Information Retrieval (2016) 0.01 
    0.005948606 = product of:
  0.014871514 = sum of:
    0.008173384 = weight(_text_:a in 2974) [ClassicSimilarity], result of:
      0.008173384 = score(doc=2974,freq=8.0), product of:
        0.053464882 = queryWeight, product of:
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.046368346 = queryNorm
        0.15287387 = fieldWeight in 2974, product of:
          2.828427 = tf(freq=8.0), with freq of:
            8.0 = termFreq=8.0
          1.153047 = idf(docFreq=37942, maxDocs=44218)
          0.046875 = fieldNorm(doc=2974)
    0.0066981306 = product of:
      0.013396261 = sum of:
        0.013396261 = weight(_text_:information in 2974) [ClassicSimilarity], result of:
          0.013396261 = score(doc=2974,freq=4.0), product of:
            0.08139861 = queryWeight, product of:
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.046368346 = queryNorm
            0.16457605 = fieldWeight in 2974, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              1.7554779 = idf(docFreq=20772, maxDocs=44218)
              0.046875 = fieldNorm(doc=2974)
      0.5 = coord(1/2)
  0.4 = coord(2/5)
    Abstract
    General graph random walk has been successfully applied in multi-document summarization, but it has some limitations to process documents by this way. In this paper, we propose a novel hypergraph based vertex-reinforced random walk framework for multi-document summarization. The framework first exploits the Hierarchical Dirichlet Process (HDP) topic model to learn a word-topic probability distribution in sentences. Then the hypergraph is used to capture both cluster relationship based on the word-topic probability distribution and pairwise similarity among sentences. Finally, a time-variant random walk algorithm for hypergraphs is developed to rank sentences which ensures sentence diversity by vertex-reinforcement in summaries. Experimental results on the public available dataset demonstrate the effectiveness of our framework.
    Source
    Information processing and management. 52(2016) no.4, S.646-657
    Type
    a