Search (2 results, page 1 of 1)

  • × author_ss:"Ibekwe-SanJuan, F."
  • × author_ss:"SanJuan, E."
  1. Ibekwe-SanJuan, F.; SanJuan, E.: Knowledge organization research in the last two decades: 1988-2008 (2010) 0.00
    0.0021899752 = product of:
      0.0065699257 = sum of:
        0.0065699257 = weight(_text_:a in 3522) [ClassicSimilarity], result of:
          0.0065699257 = score(doc=3522,freq=4.0), product of:
            0.05209492 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.045180224 = queryNorm
            0.12611452 = fieldWeight in 3522, product of:
              2.0 = tf(freq=4.0), with freq of:
                4.0 = termFreq=4.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0546875 = fieldNorm(doc=3522)
      0.33333334 = coord(1/3)
    
    Abstract
    We apply an automatic topic mapping system to records of publications in knowledge organization published between 1988-2008. The data was collected from journals publishing articles in the KO field from Web of Science database (WoS). The results showed that while topics in the first decade (1988-1997) were more traditional, the second decade (1998-2008) was marked by a more technological orientation and by the appearance of more specialized topics driven by the pervasiveness of the Web environment.
    Type
    a
  2. Ibekwe-SanJuan, F.; SanJuan, E.: From term variants to research topics (2002) 0.00
    0.0019158293 = product of:
      0.005747488 = sum of:
        0.005747488 = weight(_text_:a in 1853) [ClassicSimilarity], result of:
          0.005747488 = score(doc=1853,freq=6.0), product of:
            0.05209492 = queryWeight, product of:
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.045180224 = queryNorm
            0.11032722 = fieldWeight in 1853, product of:
              2.4494898 = tf(freq=6.0), with freq of:
                6.0 = termFreq=6.0
              1.153047 = idf(docFreq=37942, maxDocs=44218)
              0.0390625 = fieldNorm(doc=1853)
      0.33333334 = coord(1/3)
    
    Abstract
    In a scientific and technological watch (STW) task, an expert user needs to survey the evolution of research topics in his area of specialisation in order to detect interesting changes. The majority of methods proposing evaluation metrics (bibliometrics and scientometrics studies) for STW rely solely an statistical data analysis methods (Co-citation analysis, co-word analysis). Such methods usually work an structured databases where the units of analysis (words, keywords) are already attributed to documents by human indexers. The advent of huge amounts of unstructured textual data has rendered necessary the integration of natural language processing (NLP) techniques to first extract meaningful units from texts. We propose a method for STW which is NLP-oriented. The method not only analyses texts linguistically in order to extract terms from them, but also uses linguistic relations (syntactic variations) as the basis for clustering. Terms and variation relations are formalised as weighted di-graphs which the clustering algorithm, CPCL (Classification by Preferential Clustered Link) will seek to reduce in order to produces classes. These classes ideally represent the research topics present in the corpus. The results of the classification are subjected to validation by an expert in STW.
    Type
    a