Appeal 2007-1122
Application 09/966,414
Payton also teaches increasing the frequency of recommendation of a
data class without decreasing the frequency of another data-class and
expanding the scope of a first user profile according to preferences in the
second user profile. In particular, Payton teaches that an item that has not
been rated previously by a subscriber may receive a rating based on the
ratings of other subscribers. (Finding of Fact 3.) Such a change in rating
increases the frequency of recommendation of that particular item, but does
not decrease the frequency of another item because it does not change the
rating of other items. Also, such a change in rating expands the scope of the
first subscriber profile according to the preferences in a second subscriber
profile.
Therefore, as claimed, the subject matter of claim 1 reads on Payton.
Claims 2-4 were not argued separately, and stand or fall together with
claim 1.
Regarding claim 5, we find that Payton teaches selecting test data for
revising a first user's profile based on data from a second user's profile. We
believe the claim term "test data" is broad enough to encompass items in the
subscriber profile, including items that have not been rated previously by the
subscriber. (Finding of Fact 3.)
Items not rated previously by a subscriber may be selected and, as
discussed with respect to claim 1, receive a rating based on the ratings of
other subscribers. (Finding of Fact 3.) The list of recommended items sent
to the subscriber may include items which the subscriber has not previously
requested. (Finding of Fact 4.) The subscriber is prompted to rate an item
when the subscriber selects it, and the subscriber's profile is updated based
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