Appeal 2007-2745
Application 09/761,671
1 (5) The Appellant argues that Bielinski’s usage of sensitivity analysis is
2 incompatible with Brown’s neural network scoring for the same data (Br.
3 13:Bottom ¶).
4 We again find that the Appellant compared Bielinski’s single company analysis
5 to Brown’s example of portfolio analysis, as the scoring pointed to by the
6 Appellant (Brown 56:reference to ranking of future returns of stocks) is again
7 within the investment analysis examples of Brown.
8 Further, Bielinski applies the results of its sensitivity analysis to future strategic
9 action (FF 11). Similarly, Brown applies its results to future strategic actions (FF
10 22). We find nothing incompatible between using the results of sensitivity
11 analysis, their implications for future actions, and the results of neural networks for
12 suggesting future actions.
13 The Appellant goes on to argue that Bielinski and Brown are measuring the
14 same thing and there would be no point in using two methodologies to measure the
15 same thing (Br. 13:Bottom ¶). We find this is not an argument of incompatibility,
16 but of so much compatibility as to be redundant. We further find that Bielinski and
17 Brown base their analysis on different inputs (Bielinski using cash flows and
18 Brown using large databases) and the use of different analytical methods to
19 converge on a common result to reduce uncertainty is widely known and applied.
20 The Appellant has not sustained its burden of showing the Examiner erred.
21 Changing Principle of Operation
22 The Appellant argues that Bielinski and Rappaport’s Shareholder Value
23 Analysis (SVA) would change Brown’s neural network because it would use a tree
24 based analysis, acknowledge that the efficient market theory does not explain all
20
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Last modified: September 9, 2013