For example, using the current scoring equation, if i do a search for "Doug Cutting" and the results/scores i get back are... 1: 0.9 2: 0.3 3: 0.21 4: 0.21 5: 0.1 ...then there are at least two meaningful pieces of data I can glean: a) document #1 is significantly better then the other results b) document #3 and #4 are both equaly relevant to "Doug Cutting"
If I then do a search for "Chris Hostetter" and get back the following results/scores... 9: 0.9 8: 0.3 7: 0.21 6: 0.21 5: 0.1
...then I can assume the same corrisponding information is true about my new search term (#9 is significantly better, and #7/#8 are equally as good)
However, I *cannot* say either of the following: x) document #9 is as relevant for "Chris Hostetter" as document #1 is relevant to "Doug Cutting" y) document #5 is equally relevant to both "Chris Hostetter" and "Doug Cutting"
That's right. Thanks for the nice description of the issue.
I think the OP is arguing that if the scoring algorithm was modified in the way they suggested, then you would be able to make statements x & y.
And I am not convinced that, with the changes Chuck describes, one can be any more confident of x and y.
Doug
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