There were 48 sets of author productivity data tested against Lotka's Law of xn · y=c. Overwhelming conformity to the law was found. However, only seven data sets fitted the inverse square law. For future tests, representative coverage and good sampling techniques should be adhered to in data compllation. A method is suggested to compute the values of n and c from the data.
A method of selecting index terms directly from a word frequency list is described. The original idea was suggested by Goffman who reasoned that the most content-bearing words of a given text would occur at the transition region at which Zipf's First Law of words of high frequency of occurrences begins to take on properties of words of low frequency of occurrences. Word frequencies of two articles were analyzed. Results seem to indicate that the automated selection of index terms from a frequency list holds some promise for automatic indexing.
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