Zipfian distribution

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Experimental information retrieval
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25 collection ...I am arguing that in using distributional information about index terms to provide,say,index term weighting we are really attacking the old problem of controlling exhaustivity and specificity ...These terms are defined in the introduction on page 10 ...If we go back to Luhn s original ideas,we remember that he postulated a varying discrimination power for index terms as a function of the rank order of their frequency of occurrence,the highest discrimination power being associated with the middle frequencies ...Attempts have been made to apply weighting based on the way the index terms are distributed in the entire collection ...The difference between the last mode of weighting and the previous one may be summarised by saying that document frequency weighting places emphasis on content description whereas weighting by specificity attempts to emphasise the ability of terms to discriminate one document from another ...Salton and Yang [24]have recently attempted to combine both methods of weighting by looking at both inter document frequencies
15 linguistics in information science ...The chapter therefore starts with the original ideas of Luhn on which much of automatic text analysis has been built,and then goes on to describe a concrete way of generating document representatives ...Luhn s ideas In one of Luhn s [6]early papers he states:It is here proposed that the frequency of word occurrence in an article furnishes a useful measurement of word significance ...I think this quote fairly summaries Luhn s contribution to automatic text analysis ...Let f be the frequency of occurrence of various word types in a given position of text and r their rank order,that is,the order of their frequency of occurrence,then a plot relating f and r yields a curve similar to the hyperbolic curve in Figure 2 ...