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  • × author_ss:"Egghe, L."
  1. Egghe, L.: Expansion of the field of informetrics : the second special issue (2006) 0.05
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    Source
    Information processing and management. 42(2006) no.6, S.1405-1407
    Year
    2006
  2. Egghe, L.: Properties of the n-overlap vector and n-overlap similarity theory (2006) 0.02
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    Source
    Journal of the American Society for Information Science and Technology. 57(2006) no.9, S.1165-1177
    Year
    2006
  3. Egghe, L.; Guns, R.; Rousseau, R.; Leuven, K.U.: Erratum (2012) 0.02
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    Date
    14. 2.2012 12:53:22
  4. Egghe, L.: Empirical and combinatorial study of country occurrences in multi-authored papers (2006) 0.02
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    Source
    Information - Wissenschaft und Praxis. 57(2006) H.8, S.427-432
    Year
    2006
  5. Egghe, L.; Ravichandra Rao, I.K.: ¬The influence of the broadness of a query of a topic on its h-index : models and examples of the h-index of n-grams (2008) 0.01
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    Abstract
    The article studies the influence of the query formulation of a topic on its h-index. In order to generate pure random sets of documents, we used N-grams (N variable) to measure this influence: strings of zeros, truncated at the end. The used databases are WoS and Scopus. The formula h=T**1/alpha, proved in Egghe and Rousseau (2006) where T is the number of retrieved documents and is Lotka's exponent, is confirmed being a concavely increasing function of T. We also give a formula for the relation between h and N the length of the N-gram: h=D10**(-N/alpha) where D is a constant, a convexly decreasing function, which is found in our experiments. Nonlinear regression on h=T**1/alpha gives an estimation of , which can then be used to estimate the h-index of the entire database (Web of Science [WoS] and Scopus): h=S**1/alpha, , where S is the total number of documents in the database.
  6. Egghe, L.: Mathematical study of h-index sequences (2009) 0.01
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    Abstract
    This paper studies mathematical properties of h-index sequences as developed by Liang [Liang, L. (2006). h-Index sequence and h-index matrix: Constructions and applications. Scientometrics, 69(1), 153-159]. For practical reasons, Liming studies such sequences where the time goes backwards while it is more logical to use the time going forward (real career periods). Both type of h-index sequences are studied here and their interrelations are revealed. We show cases where these sequences are convex, linear and concave. We also show that, when one of the sequences is convex then the other one is concave, showing that the reverse-time sequence, in general, cannot be used to derive similar properties of the (difficult to obtain) forward time sequence. We show that both sequences are the same if and only if the author produces the same number of papers per year. If the author produces an increasing number of papers per year, then Liang's h-sequences are above the "normal" ones. All these results are also valid for g- and R-sequences. The results are confirmed by the h-, g- and R-sequences (forward and reverse time) of the author.
  7. Egghe, L.; Rousseau, R.: Averaging and globalising quotients of informetric and scientometric data (1996) 0.01
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    Source
    Journal of information science. 22(1996) no.3, S.165-170
  8. Egghe, L.: ¬A universal method of information retrieval evaluation : the "missing" link M and the universal IR surface (2004) 0.01
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    Date
    14. 8.2004 19:17:22