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  • × author_ss:"Ravichandra Rao, I.K."
  • × theme_ss:"Informetrie"
  1. Ravichandra Rao, I.K.; Sahoo, B.B.: Studies and research in informetrics at the Documentation Research and Training Centre (DRTC), ISI Bangalore (2006) 0.00
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    Abstract
    Contributions of DRTC to informetric studies and research are discussed. A report on recent work - a quantitative country-wise analysis of software literature based on the data from two bibliographic databases i.e. COMPENDEX and INSPEC is presented. The number of countries involved in R & D activities in software in the most productive group is increasing. The research contribution on software is decreasing in developed countries as compared to that in developing and less developed countries. India 's contribution is only 1.1% and it has remained constant over the period of 12 years 1989-2001. The number of countries involved in R&D activities in software has been increasing in the 1990s. It is also noted that higher the budget for higher education, higher the number of publications; and that higher the number of publications, higher the export as well as the domestic consumption of software.
  2. 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) 0.00
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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.

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