Search (3 results, page 1 of 1)

  • × theme_ss:"Retrievalstudien"
  • × theme_ss:"Indexierungsstudien"
  1. Leininger, K.: Interindexer consistency in PsychINFO (2000) 0.00
    0.0021032572 = product of:
      0.0147228 = sum of:
        0.0147228 = product of:
          0.0294456 = sum of:
            0.0294456 = weight(_text_:22 in 2552) [ClassicSimilarity], result of:
              0.0294456 = score(doc=2552,freq=2.0), product of:
                0.12684377 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.03622214 = queryNorm
                0.23214069 = fieldWeight in 2552, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.046875 = fieldNorm(doc=2552)
          0.5 = coord(1/2)
      0.14285715 = coord(1/7)
    
    Date
    9. 2.1997 18:44:22
  2. Prasher, R.G.: Evaluation of indexing system (1989) 0.00
    0.0018148007 = product of:
      0.012703604 = sum of:
        0.012703604 = product of:
          0.06351802 = sum of:
            0.06351802 = weight(_text_:system in 4998) [ClassicSimilarity], result of:
              0.06351802 = score(doc=4998,freq=8.0), product of:
                0.11408355 = queryWeight, product of:
                  3.1495528 = idf(docFreq=5152, maxDocs=44218)
                  0.03622214 = queryNorm
                0.5567675 = fieldWeight in 4998, product of:
                  2.828427 = tf(freq=8.0), with freq of:
                    8.0 = termFreq=8.0
                  3.1495528 = idf(docFreq=5152, maxDocs=44218)
                  0.0625 = fieldNorm(doc=4998)
          0.2 = coord(1/5)
      0.14285715 = coord(1/7)
    
    Abstract
    Describes information system and its various components-index file construstion, query formulation and searching. Discusses an indexing system, and brings out the need for its evaluation. Explains the concept of the efficiency of indexing systems and discusses factors which control this efficiency. Gives criteria for evaluation. Discusses recall and precision ratios, as also noise ratio, novelty ratio, and exhaustivity and specificity and the impact of each on the efficiency of indexing system. Mention also various steps for evaluation.
  3. Huffman, G.D.; Vital, D.A.; Bivins, R.G.: Generating indices with lexical association methods : term uniqueness (1990) 0.00
    8.0203614E-4 = product of:
      0.0056142528 = sum of:
        0.0056142528 = product of:
          0.028071264 = sum of:
            0.028071264 = weight(_text_:system in 4152) [ClassicSimilarity], result of:
              0.028071264 = score(doc=4152,freq=4.0), product of:
                0.11408355 = queryWeight, product of:
                  3.1495528 = idf(docFreq=5152, maxDocs=44218)
                  0.03622214 = queryNorm
                0.24605882 = fieldWeight in 4152, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  3.1495528 = idf(docFreq=5152, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=4152)
          0.2 = coord(1/5)
      0.14285715 = coord(1/7)
    
    Abstract
    A software system has been developed which orders citations retrieved from an online database in terms of relevancy. The system resulted from an effort generated by NASA's Technology Utilization Program to create new advanced software tools to largely automate the process of determining relevancy of database citations retrieved to support large technology transfer studies. The ranking is based on the generation of an enriched vocabulary using lexical association methods, a user assessment of the vocabulary and a combination of the user assessment and the lexical metric. One of the key elements in relevancy ranking is the enriched vocabulary -the terms mst be both unique and descriptive. This paper examines term uniqueness. Six lexical association methods were employed to generate characteristic word indices. A limited subset of the terms - the highest 20,40,60 and 7,5% of the uniquess words - we compared and uniquess factors developed. Computational times were also measured. It was found that methods based on occurrences and signal produced virtually the same terms. The limited subset of terms producedby the exact and centroid discrimination value were also nearly identical. Unique terms sets were produced by teh occurrence, variance and discrimination value (centroid), An end-user evaluation showed that the generated terms were largely distinct and had values of word precision which were consistent with values of the search precision.