Search (1 results, page 1 of 1)

  • × author_ss:"Herrera, J.C."
  • × author_ss:"Herrera-Viedma, E."
  • × theme_ss:"Retrievalalgorithmen"
  1. Herrera-Viedma, E.; Cordón, O.; Herrera, J.C.; Luqe, M.: ¬An IRS based on multi-granular lnguistic information (2003) 0.00
    0.0020593456 = product of:
      0.0102967275 = sum of:
        0.0102967275 = weight(_text_:a in 2740) [ClassicSimilarity], result of:
          0.0102967275 = score(doc=2740,freq=14.0), product of:
            0.050915137 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.044157036 = queryNorm
            0.20223314 = fieldWeight in 2740, product of:
              3.7416575 = tf(freq=14.0), with freq of:
                14.0 = termFreq=14.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.046875 = fieldNorm(doc=2740)
      0.2 = coord(1/5)
    
    Abstract
    An information retrieval system (IRS) based on fuzzy multi-granular linguistic information is proposed. The system has an evaluation method to process multi-granular linguistic information, in such a way that the inputs to the IRS are represented in a different linguistic domain than the outputs. The system accepts Boolean queries whose terms are weighted by means of the ordinal linguistic values represented by the linguistic variable "Importance" assessed an a label set S. The system evaluates the weighted queries according to a threshold semantic and obtains the linguistic retrieval status values (RSV) of documents represented by a linguistic variable "Relevance" expressed in a different label set S'. The advantage of this linguistic IRS with respect to others is that the use of the multi-granular linguistic information facilitates and improves the IRS-user interaction
    Type
    a