Appeal 2007-0987
Application 09/810,992
one which analyzes user data to generate new content and predict future
behavior.
Further, we agree with the Examiner’s characterization of the
disclosed expert system of Forecast Pro as one which analyzes user
historical data and selects the appropriate forecasting technique for a user’s
needs. In other words, with reference to the language of claim 18, we find
that the expert system of Forecast Pro is an “arbiter” which analyzes “profile
elements” in the form of user historical data to select a “personalization
engine,” i.e., forecasting model techniques, to develop a forecast tailored to
a user’s individual requirements.
With respect to dependent claims 19 and 20, Appellants’ arguments
(Br. 8-9) to the contrary notwithstanding, we find that the Examiner (Answer
3-4, 15) has explained exactly how the disclosure of Forecast Pro satisfies
the claimed requirements. We find no persuasive arguments from
Appellants that convince us of any error in the Examiner’s position that the
designated items 4 and 5 on pages 3 and 4 of Forecast Pro describe the
claimed features of personalized content object sending (claim 19) and
profile database access (claim 20).
In view of the above discussion, since all of the claimed limitations
are present in the disclosure of Forecast Pro, the Examiner’s 35 U.S.C.
§ 102(a) rejection of claims 18-20 is sustained.
35 U.S.C. § 103(a) REJECTIONS
Appellants’ arguments (Br. 10-17; Reply Br. 3-5) in response to the
Examiner’s obviousness rejection of independent claims 1 and 8 based on
the combination of Kadowaki and Forecast Pro assert a failure by the
8
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