Search (1 results, page 1 of 1)

  • × author_ss:"Kang, I.-S."
  • × author_ss:"Kim, P."
  • × year_i:[2000 TO 2010}
  1. Kang, I.-S.; Na, S.-H.; Lee, S.; Jung, H.; Kim, P.; Sung, W.-K.; Lee, J.-H.: On co-authorship for author disambiguation (2009) 0.05
    0.049952157 = sum of:
      0.025381705 = product of:
        0.10152682 = sum of:
          0.10152682 = weight(_text_:authors in 2453) [ClassicSimilarity], result of:
            0.10152682 = score(doc=2453,freq=4.0), product of:
              0.23755142 = queryWeight, product of:
                4.558814 = idf(docFreq=1258, maxDocs=44218)
                0.05210816 = queryNorm
              0.42738882 = fieldWeight in 2453, product of:
                2.0 = tf(freq=4.0), with freq of:
                  4.0 = termFreq=4.0
                4.558814 = idf(docFreq=1258, maxDocs=44218)
                0.046875 = fieldNorm(doc=2453)
        0.25 = coord(1/4)
      0.024570452 = product of:
        0.049140904 = sum of:
          0.049140904 = weight(_text_:i in 2453) [ClassicSimilarity], result of:
            0.049140904 = score(doc=2453,freq=2.0), product of:
              0.1965379 = queryWeight, product of:
                3.7717297 = idf(docFreq=2765, maxDocs=44218)
                0.05210816 = queryNorm
              0.25003272 = fieldWeight in 2453, product of:
                1.4142135 = tf(freq=2.0), with freq of:
                  2.0 = termFreq=2.0
                3.7717297 = idf(docFreq=2765, maxDocs=44218)
                0.046875 = fieldNorm(doc=2453)
        0.5 = coord(1/2)
    
    Abstract
    Author name disambiguation deals with clustering the same-name authors into different individuals. To attack the problem, many studies have employed a variety of disambiguation features such as coauthors, titles of papers/publications, topics of articles, emails/affiliations, etc. Among these, co-authorship is the most easily accessible and influential, since inter-person acquaintances represented by co-authorship could discriminate the identities of authors more clearly than other features. This study attempts to explore the net effects of co-authorship on author clustering in bibliographic data. First, to handle the shortage of explicit coauthors listed in known citations, a web-assisted technique of acquiring implicit coauthors of the target author to be disambiguated is proposed. Then, a coauthor disambiguation hypothesis that the identity of an author can be determined by his/her coauthors is examined and confirmed through a variety of author disambiguation experiments.