Search (163 results, page 1 of 9)

  • × language_ss:"e"
  • × theme_ss:"Informetrie"
  • × type_ss:"a"
  • × year_i:[2010 TO 2020}
  1. Chang, K.-C.; Zhou, W.; Zhang, S.; Yuan, C,-C.: Threshold effects of the patent H-index in the relationship between patent citations and market value (2015) 0.03
    0.027841903 = product of:
      0.055683807 = sum of:
        0.055683807 = product of:
          0.08352571 = sum of:
            0.03820133 = weight(_text_:k in 2344) [ClassicSimilarity], result of:
              0.03820133 = score(doc=2344,freq=2.0), product of:
                0.16142878 = queryWeight, product of:
                  3.569778 = idf(docFreq=3384, maxDocs=44218)
                  0.045220956 = queryNorm
                0.23664509 = fieldWeight in 2344, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.569778 = idf(docFreq=3384, maxDocs=44218)
                  0.046875 = fieldNorm(doc=2344)
            0.04532438 = weight(_text_:h in 2344) [ClassicSimilarity], result of:
              0.04532438 = score(doc=2344,freq=12.0), product of:
                0.11234917 = queryWeight, product of:
                  2.4844491 = idf(docFreq=10020, maxDocs=44218)
                  0.045220956 = queryNorm
                0.40342426 = fieldWeight in 2344, product of:
                  3.4641016 = tf(freq=12.0), with freq of:
                    12.0 = termFreq=12.0
                  2.4844491 = idf(docFreq=10020, maxDocs=44218)
                  0.046875 = fieldNorm(doc=2344)
          0.6666667 = coord(2/3)
      0.5 = coord(1/2)
    
    Abstract
    This study employs a panel threshold regression model to test whether the patent h-index has a threshold effect on the relationship between patent citations and market value in the pharmaceutical industry. It aims to bridge the gap in extant research on this topic. This study demonstrates that the patent h-index has a triple threshold effect on the relationship between patent citations and market value. When the patent h-index is less than or equal to the lowest threshold, 4, there is a positive relationship between patent citations and market value. This study indicates that the first regime (where the patent h-index is less than or equal to 4) is optimal, because this is where the extent of the positive relationship between patent citations and market value is the greatest.
    Object
    h-index
  2. Stvilia, B.; Hinnant, C.C.; Schindler, K.; Worrall, A.; Burnett, G.; Burnett, K.; Kazmer, M.M.; Marty, P.F.: Composition of scientific teams and publication productivity at a national science lab (2011) 0.03
    0.02521826 = product of:
      0.05043652 = sum of:
        0.05043652 = product of:
          0.075654775 = sum of:
            0.045020696 = weight(_text_:k in 4191) [ClassicSimilarity], result of:
              0.045020696 = score(doc=4191,freq=4.0), product of:
                0.16142878 = queryWeight, product of:
                  3.569778 = idf(docFreq=3384, maxDocs=44218)
                  0.045220956 = queryNorm
                0.2788889 = fieldWeight in 4191, product of:
                  2.0 = tf(freq=4.0), with freq of:
                    4.0 = termFreq=4.0
                  3.569778 = idf(docFreq=3384, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=4191)
            0.030634077 = weight(_text_:22 in 4191) [ClassicSimilarity], result of:
              0.030634077 = score(doc=4191,freq=2.0), product of:
                0.15835609 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.045220956 = queryNorm
                0.19345059 = fieldWeight in 4191, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=4191)
          0.6666667 = coord(2/3)
      0.5 = coord(1/2)
    
    Date
    22. 1.2011 13:19:42
  3. Ajiferuke, I.; Lu, K.; Wolfram, D.: ¬A comparison of citer and citation-based measure outcomes for multiple disciplines (2010) 0.02
    0.024987407 = product of:
      0.049974814 = sum of:
        0.049974814 = product of:
          0.07496222 = sum of:
            0.03820133 = weight(_text_:k in 4000) [ClassicSimilarity], result of:
              0.03820133 = score(doc=4000,freq=2.0), product of:
                0.16142878 = queryWeight, product of:
                  3.569778 = idf(docFreq=3384, maxDocs=44218)
                  0.045220956 = queryNorm
                0.23664509 = fieldWeight in 4000, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.569778 = idf(docFreq=3384, maxDocs=44218)
                  0.046875 = fieldNorm(doc=4000)
            0.036760893 = weight(_text_:22 in 4000) [ClassicSimilarity], result of:
              0.036760893 = score(doc=4000,freq=2.0), product of:
                0.15835609 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.045220956 = queryNorm
                0.23214069 = fieldWeight in 4000, 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=4000)
          0.6666667 = coord(2/3)
      0.5 = coord(1/2)
    
    Date
    28. 9.2010 12:54:22
  4. Norris, M.; Oppenheim, C.: ¬The h-index : a broad review of a new bibliometric indicator (2010) 0.02
    0.024749164 = product of:
      0.049498327 = sum of:
        0.049498327 = product of:
          0.07424749 = sum of:
            0.043613408 = weight(_text_:h in 4147) [ClassicSimilarity], result of:
              0.043613408 = score(doc=4147,freq=16.0), product of:
                0.11234917 = queryWeight, product of:
                  2.4844491 = idf(docFreq=10020, maxDocs=44218)
                  0.045220956 = queryNorm
                0.3881952 = fieldWeight in 4147, product of:
                  4.0 = tf(freq=16.0), with freq of:
                    16.0 = termFreq=16.0
                  2.4844491 = idf(docFreq=10020, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=4147)
            0.030634077 = weight(_text_:22 in 4147) [ClassicSimilarity], result of:
              0.030634077 = score(doc=4147,freq=2.0), product of:
                0.15835609 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.045220956 = queryNorm
                0.19345059 = fieldWeight in 4147, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=4147)
          0.6666667 = coord(2/3)
      0.5 = coord(1/2)
    
    Abstract
    Purpose - This review aims to show, broadly, how the h-index has become a subject of widespread debate, how it has spawned many variants and diverse applications since first introduced in 2005 and some of the issues in its use. Design/methodology/approach - The review drew on a range of material published in 1990 or so sources published since 2005. From these sources, a number of themes were identified and discussed ranging from the h-index's advantages to which citation database might be selected for its calculation. Findings - The analysis shows how the h-index has quickly established itself as a major subject of interest in the field of bibliometrics. Study of the index ranges from its mathematical underpinning to a range of variants perceived to address the indexes' shortcomings. The review illustrates how widely the index has been applied but also how care must be taken in its application. Originality/value - The use of bibliometric indicators to measure research performance continues, with the h-index as its latest addition. The use of the h-index, its variants and many applications to which it has been put are still at the exploratory stage. The review shows the breadth and diversity of this research and the need to verify the veracity of the h-index by more studies.
    Date
    8. 1.2011 19:22:13
    Object
    h-index
  5. McKeown, K.; Daume III, H.; Chaturvedi, S.; Paparrizos, J.; Thadani, K.; Barrio, P.; Biran, O.; Bothe, S.; Collins, M.; Fleischmann, K.R.; Gravano, L.; Jha, R.; King, B.; McInerney, K.; Moon, T.; Neelakantan, A.; O'Seaghdha, D.; Radev, D.; Templeton, C.; Teufel, S.: Predicting the impact of scientific concepts using full-text features (2016) 0.02
    0.023519512 = product of:
      0.047039025 = sum of:
        0.047039025 = product of:
          0.07055853 = sum of:
            0.055138867 = weight(_text_:k in 3153) [ClassicSimilarity], result of:
              0.055138867 = score(doc=3153,freq=6.0), product of:
                0.16142878 = queryWeight, product of:
                  3.569778 = idf(docFreq=3384, maxDocs=44218)
                  0.045220956 = queryNorm
                0.34156775 = fieldWeight in 3153, product of:
                  2.4494898 = tf(freq=6.0), with freq of:
                    6.0 = termFreq=6.0
                  3.569778 = idf(docFreq=3384, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=3153)
            0.015419668 = weight(_text_:h in 3153) [ClassicSimilarity], result of:
              0.015419668 = score(doc=3153,freq=2.0), product of:
                0.11234917 = queryWeight, product of:
                  2.4844491 = idf(docFreq=10020, maxDocs=44218)
                  0.045220956 = queryNorm
                0.13724773 = fieldWeight in 3153, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  2.4844491 = idf(docFreq=10020, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=3153)
          0.6666667 = coord(2/3)
      0.5 = coord(1/2)
    
  6. Liu, D.-R.; Shih, M.-J.: Hybrid-patent classification based on patent-network analysis (2011) 0.02
    0.020822838 = product of:
      0.041645676 = sum of:
        0.041645676 = product of:
          0.062468514 = sum of:
            0.03183444 = weight(_text_:k in 4189) [ClassicSimilarity], result of:
              0.03183444 = score(doc=4189,freq=2.0), product of:
                0.16142878 = queryWeight, product of:
                  3.569778 = idf(docFreq=3384, maxDocs=44218)
                  0.045220956 = queryNorm
                0.19720423 = fieldWeight in 4189, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.569778 = idf(docFreq=3384, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=4189)
            0.030634077 = weight(_text_:22 in 4189) [ClassicSimilarity], result of:
              0.030634077 = score(doc=4189,freq=2.0), product of:
                0.15835609 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.045220956 = queryNorm
                0.19345059 = fieldWeight in 4189, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=4189)
          0.6666667 = coord(2/3)
      0.5 = coord(1/2)
    
    Abstract
    Effective patent management is essential for organizations to maintain their competitive advantage. The classification of patents is a critical part of patent management and industrial analysis. This study proposes a hybrid-patent-classification approach that combines a novel patent-network-based classification method with three conventional classification methods to analyze query patents and predict their classes. The novel patent network contains various types of nodes that represent different features extracted from patent documents. The nodes are connected based on the relationship metrics derived from the patent metadata. The proposed classification method predicts a query patent's class by analyzing all reachable nodes in the patent network and calculating their relevance to the query patent. It then classifies the query patent with a modified k-nearest neighbor classifier. To further improve the approach, we combine it with content-based, citation-based, and metadata-based classification methods to develop a hybrid-classification approach. We evaluate the performance of the hybrid approach on a test dataset of patent documents obtained from the U.S. Patent and Trademark Office, and compare its performance with that of the three conventional methods. The results demonstrate that the proposed patent-network-based approach yields more accurate class predictions than the patent network-based approach.
    Date
    22. 1.2011 13:04:21
  7. Song, M.; Kang, K.; An, J.Y.: Investigating drug-disease interactions in drug-symptom-disease triples via citation relations (2018) 0.02
    0.020822838 = product of:
      0.041645676 = sum of:
        0.041645676 = product of:
          0.062468514 = sum of:
            0.03183444 = weight(_text_:k in 4545) [ClassicSimilarity], result of:
              0.03183444 = score(doc=4545,freq=2.0), product of:
                0.16142878 = queryWeight, product of:
                  3.569778 = idf(docFreq=3384, maxDocs=44218)
                  0.045220956 = queryNorm
                0.19720423 = fieldWeight in 4545, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.569778 = idf(docFreq=3384, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=4545)
            0.030634077 = weight(_text_:22 in 4545) [ClassicSimilarity], result of:
              0.030634077 = score(doc=4545,freq=2.0), product of:
                0.15835609 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.045220956 = queryNorm
                0.19345059 = fieldWeight in 4545, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=4545)
          0.6666667 = coord(2/3)
      0.5 = coord(1/2)
    
    Date
    1.11.2018 18:19:22
  8. Wan, X.; Liu, F.: Are all literature citations equally important? : automatic citation strength estimation and its applications (2014) 0.02
    0.018421499 = product of:
      0.036842998 = sum of:
        0.036842998 = product of:
          0.055264495 = sum of:
            0.0185036 = weight(_text_:h in 1350) [ClassicSimilarity], result of:
              0.0185036 = score(doc=1350,freq=2.0), product of:
                0.11234917 = queryWeight, product of:
                  2.4844491 = idf(docFreq=10020, maxDocs=44218)
                  0.045220956 = queryNorm
                0.16469726 = fieldWeight in 1350, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  2.4844491 = idf(docFreq=10020, maxDocs=44218)
                  0.046875 = fieldNorm(doc=1350)
            0.036760893 = weight(_text_:22 in 1350) [ClassicSimilarity], result of:
              0.036760893 = score(doc=1350,freq=2.0), product of:
                0.15835609 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.045220956 = queryNorm
                0.23214069 = fieldWeight in 1350, 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=1350)
          0.6666667 = coord(2/3)
      0.5 = coord(1/2)
    
    Abstract
    Literature citation analysis plays a very important role in bibliometrics and scientometrics, such as the Science Citation Index (SCI) impact factor, h-index. Existing citation analysis methods assume that all citations in a paper are equally important, and they simply count the number of citations. Here we argue that the citations in a paper are not equally important and some citations are more important than the others. We use a strength value to assess the importance of each citation and propose to use the regression method with a few useful features for automatically estimating the strength value of each citation. Evaluation results on a manually labeled data set in the computer science field show that the estimated values can achieve good correlation with human-labeled values. We further apply the estimated citation strength values for evaluating paper influence and author influence, and the preliminary evaluation results demonstrate the usefulness of the citation strength values.
    Date
    22. 8.2014 17:12:35
  9. Huang, M.-H.; Huang, W.-T.; Chang, C.-C.; Chen, D. Z.; Lin, C.-P.: The greater scattering phenomenon beyond Bradford's law in patent citation (2014) 0.02
    0.018421499 = product of:
      0.036842998 = sum of:
        0.036842998 = product of:
          0.055264495 = sum of:
            0.0185036 = weight(_text_:h in 1352) [ClassicSimilarity], result of:
              0.0185036 = score(doc=1352,freq=2.0), product of:
                0.11234917 = queryWeight, product of:
                  2.4844491 = idf(docFreq=10020, maxDocs=44218)
                  0.045220956 = queryNorm
                0.16469726 = fieldWeight in 1352, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  2.4844491 = idf(docFreq=10020, maxDocs=44218)
                  0.046875 = fieldNorm(doc=1352)
            0.036760893 = weight(_text_:22 in 1352) [ClassicSimilarity], result of:
              0.036760893 = score(doc=1352,freq=2.0), product of:
                0.15835609 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.045220956 = queryNorm
                0.23214069 = fieldWeight in 1352, 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=1352)
          0.6666667 = coord(2/3)
      0.5 = coord(1/2)
    
    Date
    22. 8.2014 17:11:29
  10. Ntuli, H.; Inglesi-Lotz, R.; Chang, T.; Pouris, A.: Does research output cause economic growth or vice versa? : evidence from 34 OECD countries (2015) 0.02
    0.018421499 = product of:
      0.036842998 = sum of:
        0.036842998 = product of:
          0.055264495 = sum of:
            0.0185036 = weight(_text_:h in 2132) [ClassicSimilarity], result of:
              0.0185036 = score(doc=2132,freq=2.0), product of:
                0.11234917 = queryWeight, product of:
                  2.4844491 = idf(docFreq=10020, maxDocs=44218)
                  0.045220956 = queryNorm
                0.16469726 = fieldWeight in 2132, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  2.4844491 = idf(docFreq=10020, maxDocs=44218)
                  0.046875 = fieldNorm(doc=2132)
            0.036760893 = weight(_text_:22 in 2132) [ClassicSimilarity], result of:
              0.036760893 = score(doc=2132,freq=2.0), product of:
                0.15835609 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.045220956 = queryNorm
                0.23214069 = fieldWeight in 2132, 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=2132)
          0.6666667 = coord(2/3)
      0.5 = coord(1/2)
    
    Date
    8. 7.2015 22:00:42
  11. Zhang, H.; Qiu, B.; Ivanova, K.; Giles, C.L.; Foley, H.C.; Yen, J.: Locality and attachedness-based temporal social network growth dynamics analysis : a case study of evolving nanotechnology scientific collaboration networks (2010) 0.02
    0.01575137 = product of:
      0.03150274 = sum of:
        0.03150274 = product of:
          0.047254108 = sum of:
            0.03183444 = weight(_text_:k in 3455) [ClassicSimilarity], result of:
              0.03183444 = score(doc=3455,freq=2.0), product of:
                0.16142878 = queryWeight, product of:
                  3.569778 = idf(docFreq=3384, maxDocs=44218)
                  0.045220956 = queryNorm
                0.19720423 = fieldWeight in 3455, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.569778 = idf(docFreq=3384, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=3455)
            0.015419668 = weight(_text_:h in 3455) [ClassicSimilarity], result of:
              0.015419668 = score(doc=3455,freq=2.0), product of:
                0.11234917 = queryWeight, product of:
                  2.4844491 = idf(docFreq=10020, maxDocs=44218)
                  0.045220956 = queryNorm
                0.13724773 = fieldWeight in 3455, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  2.4844491 = idf(docFreq=10020, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=3455)
          0.6666667 = coord(2/3)
      0.5 = coord(1/2)
    
  12. Onodera, N.; Iwasawa, M.; Midorikawa, N.; Yoshikane, F.; Amano, K.; Ootani, Y.; Kodama, T.; Kiyama, Y.; Tsunoda, H.; Yamazaki, S.: ¬A method for eliminating articles by homonymous authors from the large number of articles retrieved by author search (2011) 0.02
    0.01575137 = product of:
      0.03150274 = sum of:
        0.03150274 = product of:
          0.047254108 = sum of:
            0.03183444 = weight(_text_:k in 4370) [ClassicSimilarity], result of:
              0.03183444 = score(doc=4370,freq=2.0), product of:
                0.16142878 = queryWeight, product of:
                  3.569778 = idf(docFreq=3384, maxDocs=44218)
                  0.045220956 = queryNorm
                0.19720423 = fieldWeight in 4370, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.569778 = idf(docFreq=3384, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=4370)
            0.015419668 = weight(_text_:h in 4370) [ClassicSimilarity], result of:
              0.015419668 = score(doc=4370,freq=2.0), product of:
                0.11234917 = queryWeight, product of:
                  2.4844491 = idf(docFreq=10020, maxDocs=44218)
                  0.045220956 = queryNorm
                0.13724773 = fieldWeight in 4370, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  2.4844491 = idf(docFreq=10020, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=4370)
          0.6666667 = coord(2/3)
      0.5 = coord(1/2)
    
  13. Chang, Y.-W.; Huang, M.-H.: ¬A study of the evolution of interdisciplinarity in library and information science : using three bibliometric methods (2012) 0.02
    0.015351249 = product of:
      0.030702498 = sum of:
        0.030702498 = product of:
          0.046053745 = sum of:
            0.015419668 = weight(_text_:h in 4959) [ClassicSimilarity], result of:
              0.015419668 = score(doc=4959,freq=2.0), product of:
                0.11234917 = queryWeight, product of:
                  2.4844491 = idf(docFreq=10020, maxDocs=44218)
                  0.045220956 = queryNorm
                0.13724773 = fieldWeight in 4959, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  2.4844491 = idf(docFreq=10020, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=4959)
            0.030634077 = weight(_text_:22 in 4959) [ClassicSimilarity], result of:
              0.030634077 = score(doc=4959,freq=2.0), product of:
                0.15835609 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.045220956 = queryNorm
                0.19345059 = fieldWeight in 4959, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=4959)
          0.6666667 = coord(2/3)
      0.5 = coord(1/2)
    
    Source
    Journal of the American Society for Information Science and Technology. 63(2012) no.1, S.22-33
  14. Kuan, C.-H.; Liu, J.S.: ¬A new approach for main path analysis : decay in knowledge diffusion (2016) 0.02
    0.015351249 = product of:
      0.030702498 = sum of:
        0.030702498 = product of:
          0.046053745 = sum of:
            0.015419668 = weight(_text_:h in 2649) [ClassicSimilarity], result of:
              0.015419668 = score(doc=2649,freq=2.0), product of:
                0.11234917 = queryWeight, product of:
                  2.4844491 = idf(docFreq=10020, maxDocs=44218)
                  0.045220956 = queryNorm
                0.13724773 = fieldWeight in 2649, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  2.4844491 = idf(docFreq=10020, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=2649)
            0.030634077 = weight(_text_:22 in 2649) [ClassicSimilarity], result of:
              0.030634077 = score(doc=2649,freq=2.0), product of:
                0.15835609 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.045220956 = queryNorm
                0.19345059 = fieldWeight in 2649, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.0390625 = fieldNorm(doc=2649)
          0.6666667 = coord(2/3)
      0.5 = coord(1/2)
    
    Date
    22. 1.2016 14:23:00
  15. Abbasi, M. K.; Frommholz, I.: Cluster-based polyrepresentation as science modelling approach for information retrieval (2015) 0.01
    0.012733776 = product of:
      0.025467552 = sum of:
        0.025467552 = product of:
          0.07640266 = sum of:
            0.07640266 = weight(_text_:k in 1691) [ClassicSimilarity], result of:
              0.07640266 = score(doc=1691,freq=2.0), product of:
                0.16142878 = queryWeight, product of:
                  3.569778 = idf(docFreq=3384, maxDocs=44218)
                  0.045220956 = queryNorm
                0.47329018 = fieldWeight in 1691, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.569778 = idf(docFreq=3384, maxDocs=44218)
                  0.09375 = fieldNorm(doc=1691)
          0.33333334 = coord(1/3)
      0.5 = coord(1/2)
    
  16. Marx, W.; Bornmann, L.: On the problems of dealing with bibliometric data (2014) 0.01
    0.012253631 = product of:
      0.024507262 = sum of:
        0.024507262 = product of:
          0.073521785 = sum of:
            0.073521785 = weight(_text_:22 in 1239) [ClassicSimilarity], result of:
              0.073521785 = score(doc=1239,freq=2.0), product of:
                0.15835609 = queryWeight, product of:
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.045220956 = queryNorm
                0.46428138 = fieldWeight in 1239, product of:
                  1.4142135 = tf(freq=2.0), with freq of:
                    2.0 = termFreq=2.0
                  3.5018296 = idf(docFreq=3622, maxDocs=44218)
                  0.09375 = fieldNorm(doc=1239)
          0.33333334 = coord(1/3)
      0.5 = coord(1/2)
    
    Date
    18. 3.2014 19:13:22
  17. Hovden, R.: Bibliometrics for Internet media : applying the h-index to YouTube (2013) 0.01
    0.010176461 = product of:
      0.020352922 = sum of:
        0.020352922 = product of:
          0.061058767 = sum of:
            0.061058767 = weight(_text_:h in 1111) [ClassicSimilarity], result of:
              0.061058767 = score(doc=1111,freq=16.0), product of:
                0.11234917 = queryWeight, product of:
                  2.4844491 = idf(docFreq=10020, maxDocs=44218)
                  0.045220956 = queryNorm
                0.54347324 = fieldWeight in 1111, product of:
                  4.0 = tf(freq=16.0), with freq of:
                    16.0 = termFreq=16.0
                  2.4844491 = idf(docFreq=10020, maxDocs=44218)
                  0.0546875 = fieldNorm(doc=1111)
          0.33333334 = coord(1/3)
      0.5 = coord(1/2)
    
    Abstract
    The h-index can be a useful metric for evaluating a person's output of Internet media. Here I advocate and demonstrate adaption of the h-index and the g-index to the top video content creators on YouTube. The h-index for Internet video media is based on videos and their view counts. The h-index is defined as the number of videos with >=h × 10**5 views. The g-index is defined as the number of videos with >=g × 10**5 views on average. When compared with a video creator's total view count, the h-index and g-index better capture both productivity and impact in a single metric.
    Object
    h-index
  18. Waltman, L.; Eck, N.J. van: ¬The inconsistency of the h-index : the case of web accessibility in Western European countries (2012) 0.01
    0.009752254 = product of:
      0.019504508 = sum of:
        0.019504508 = product of:
          0.058513522 = sum of:
            0.058513522 = weight(_text_:h in 40) [ClassicSimilarity], result of:
              0.058513522 = score(doc=40,freq=20.0), product of:
                0.11234917 = queryWeight, product of:
                  2.4844491 = idf(docFreq=10020, maxDocs=44218)
                  0.045220956 = queryNorm
                0.5208185 = fieldWeight in 40, product of:
                  4.472136 = tf(freq=20.0), with freq of:
                    20.0 = termFreq=20.0
                  2.4844491 = idf(docFreq=10020, maxDocs=44218)
                  0.046875 = fieldNorm(doc=40)
          0.33333334 = coord(1/3)
      0.5 = coord(1/2)
    
    Abstract
    The h-index is a popular bibliometric indicator for assessing individual scientists. We criticize the h-index from a theoretical point of view. We argue that for the purpose of measuring the overall scientific impact of a scientist (or some other unit of analysis), the h-index behaves in a counterintuitive way. In certain cases, the mechanism used by the h-index to aggregate publication and citation statistics into a single number leads to inconsistencies in the way in which scientists are ranked. Our conclusion is that the h-index cannot be considered an appropriate indicator of a scientist's overall scientific impact. Based on recent theoretical insights, we discuss what kind of indicators can be used as an alternative to the h-index. We pay special attention to the highly cited publications indicator. This indicator has a lot in common with the h-index, but unlike the h-index it does not produce inconsistent rankings.
    Object
    h-index
  19. Zhang, C.-T.: Relationship of the h-index, g-index, and e-index (2010) 0.01
    0.0092518 = product of:
      0.0185036 = sum of:
        0.0185036 = product of:
          0.0555108 = sum of:
            0.0555108 = weight(_text_:h in 3418) [ClassicSimilarity], result of:
              0.0555108 = score(doc=3418,freq=18.0), product of:
                0.11234917 = queryWeight, product of:
                  2.4844491 = idf(docFreq=10020, maxDocs=44218)
                  0.045220956 = queryNorm
                0.49409178 = fieldWeight in 3418, product of:
                  4.2426405 = tf(freq=18.0), with freq of:
                    18.0 = termFreq=18.0
                  2.4844491 = idf(docFreq=10020, maxDocs=44218)
                  0.046875 = fieldNorm(doc=3418)
          0.33333334 = coord(1/3)
      0.5 = coord(1/2)
    
    Abstract
    Of h-type indices available now, the g-index is an important one in that it not only keeps some advantages of the h-index but also counts citations from highly cited articles. However, the g-index has a drawback that one has to add fictitious articles with zero citation to calculate this index in some important cases. Based on an alternative definition without introducing fictitious articles, an analytical method has been proposed to calculate the g-index based approximately on the h-index and the e-index. If citations for a scientist are ranked by a power law, it is shown that the g-index can be calculated accurately by the h-index, the e-index, and the power parameter. The relationship of the h-, g-, and e-indices presented here shows that the g-index contains the citation information from the h-index, the e-index, and some papers beyond the h-core.
    Object
    h-index
  20. Egghe, L.; Rousseau, R.: ¬The Hirsch index of a shifted Lotka function and its relation with the impact factor (2012) 0.01
    0.008813074 = product of:
      0.017626148 = sum of:
        0.017626148 = product of:
          0.052878443 = sum of:
            0.052878443 = weight(_text_:h in 243) [ClassicSimilarity], result of:
              0.052878443 = score(doc=243,freq=12.0), product of:
                0.11234917 = queryWeight, product of:
                  2.4844491 = idf(docFreq=10020, maxDocs=44218)
                  0.045220956 = queryNorm
                0.47066164 = fieldWeight in 243, product of:
                  3.4641016 = tf(freq=12.0), with freq of:
                    12.0 = termFreq=12.0
                  2.4844491 = idf(docFreq=10020, maxDocs=44218)
                  0.0546875 = fieldNorm(doc=243)
          0.33333334 = coord(1/3)
      0.5 = coord(1/2)
    
    Abstract
    Based on earlier results about the shifted Lotka function, we prove an implicit functional relation between the Hirsch index (h-index) and the total number of sources (T). It is shown that the corresponding function, h(T), is concavely increasing. Next, we construct an implicit relation between the h-index and the impact factor IF (an average number of items per source). The corresponding function h(IF) is increasing and we show that if the parameter C in the numerator of the shifted Lotka function is high, then the relation between the h-index and the impact factor is almost linear.
    Object
    h-index