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|    comp.ai    |    Awaiting the gospel from Sarah Connor    |    1,954 messages    |
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|    Message 687 of 1,954    |
|    Ted Dunning to All    |
|    Re: Data Mining of Preference Orderings    |
|    03 Apr 05 23:48:01    |
      From: ted.dunning@gmail.com              You say that purchase is not necessarily what you are trying to       predict, but that is really just a bit of a red herring. Purchase and       revenues happened to be what I worked on most, but any other form of       measurable outcome is reasonable.              Much more importantly, however, purchase was only what I was       predicting, not what I was using as input. As input, I used direct       monitoring of use which correlates much better to preference than does       purchase and vastly more than any outcome of an artificial task such as       rating or assigning a value.              There is a long tradition in marketing that people don't tell you what       they are thinking and that they are really bad reporters of their own       motivations. I believe that there was an instructive study in which       posters were presented to experimental subjects who were asked which       poster they liked. Some of the subjects were asked to explain why they       liked the poster they selected, others were not asked. Subsequent       followup showed that those who had to explain their preference did not       select the same posters some months later as much as those who did not       have to explain their preference. I don't have the reference,       unfortunately.              The inescapable conclusion is that explained preference and unexplained       preference are different things cognitively.              This study conforms very directly to my own experience which showed       that the only really good data for determining likelihood that somebody       would like to play a bit of music was a history of what they had       already played. Ratings were like explanations and, worse, people who       want to play music don't want to make ratings. Browsing is also a poor       indicator of preference. Even purchase is a highly compromised       indicator.              *That* is my first point ... that you have to use direct consumption to       get really, really good results.              My second point is that you have to have a really solid and objective       goal and practical goals are often composite and complex. Revenue is       simply and example of a target variable that lots of people seem to       care about.              I guess it comes down to a question of tense. When you say "I solve       this by ...", do you mean that you have already built a system that       succeeds for this task (which would justify the present tense) or do       you mean that you PLAN to build a system using this method (which would       only justify the future tense). In my case, I use the past tense. I       did build such a system and know from experience that there are many       slips between paper design and accurate predictions.              [ comp.ai is moderated. To submit, just post and be patient, or if ]       [ that fails mail your article to |
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