On Thu, Dec 16, 2010 at 8:55 PM, gabeweb <[email protected]> wrote: > > Hi, I'm interested in following up on this question about combining boolean > and non-boolean data. Young and Sean mentioned two ways of doing this: > > (1) Assign each boolean data point an arbitrary rating, such as 4 out of 5. > > (2) Assume that all of the data is boolean, i.e. ignore the explicit > ratings. > > Are there any other ways of doing this that folks have found to work well? > I could imagine, for example, that instead of assigning each boolean data > point an arbitrary rating (such as 4), one could assign it the average of > the non-boolean ratings. > > The problem with any method of combining boolean and non-boolean data is > that it can't be tested objectively, because it is a means of constructing a > dataset -- including the test data! So it seems that only a subjective > evaluation could differentiate among different options. I'm hoping that > someone else has already done something along these lines. > > Thanks much in advance. > --
I am also interested in the problem of testing a model where implicit feedback is converted to explicit ratings. Please let me know if you find any research/work in this area.
