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and The importance of writing it this way,apart from its simplicity,is that for each document x to calculate g x we simply add the coefficients ci for those index terms that are present,i
...The constant C which has been assumed the same for all documents x will of course vary from query to query,but it can be interpreted as the cut off applied to the retrieval function
...Let us now turn to the other part of g x,namely ci and let us try and interpret it in terms of the conventional contingency table
...There will be one such table for each index term;I have shown it for the index term i although the subscript i has not been used in the cells
...This is in fact the weighting formula F 4 used by Robertson and Sparck Jones 1 in their so called retrospective experiments
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| 124 |
example,in Figure 6
...I x 1,x 2 I x 2,x 3 I x 2,x 4 I x 2,x 5 I x 5 x 6 is a maximum
...Once the dependence tree has been found the approximating distribution can be written down immediately in the form A 2
...ti Prob xi 1 xj i 1 ri Prob xi 1 x j i 0 and r 1 Prob x 1 1 P xi xj i [ti [xi]1 ti [1][xi]][xj i []ri [xi]1 ri [1][xi]][1][xj i]then This is a non linear weighting function which will simplify to the one derived from A 1 when the variables are assumed to be independent,that is,when ti ri
...g x log P x w 1 log P x w 2 which now involves the calculation or estimation of twice as many parameters as in the linear case
...It is easier to see how g x combines differentweights for different terms if one looks at the weights contributed to g x for a given |
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