Appeal No. 2005-1644
Application 09/400,583
the store and, as noted in the new ground of rejection, we find
that determining the relative placement of products using data
mining techniques lacks written description support and is
misdescriptive of the described invention.
The examiner finds (FR2):
Hughes et al. teach[] associating spatial relationships with
customer data to determine additional information concerning
purchases by the customer ..., recording (identifying) paths
of customers ..., associating the locations of products with
the paths of customers as claimed ... which employs data
mining algorithms to generate input data for forming the set
of spatial relationships (see at least col. 17, lines 5-20,
30-45, col. 20, lines 10-15, 25-60) and spatial analysis
algorithms to form the set of spatial relationships (see at
least col. 20, lines 40-50, col. 19, lines 1-35, col. 13,
lines 25-45, col. 18, lines 15-40).
Appellants argue that the data mining of Hughes is not
described as generating spatial relationships, but is only
described as used for measuring overall facility performance.
For example, appellants argue (Br5):
The data mining of Hughes is not described or applied to
generating spatial relationships using data mining
techniques where the spatial relationships include
associations of customer paths through retail space with
product placement. In order to apply the teachings of data
mining from Tough [sic, Toung] to Hughes, Hughes must be
modified by applying the use of data mining to generating
spatial relationships using data mining techniques where the
spatial relationships include associations of customer paths
through the retail space with product placement. No such
teaching is found in either reference.
And, appellants further argue (Br6):
In addition, Hughes teaches using data mining for
measuring overall facility performance. Hughes does not
teach using data mining to generate spatial relationships
where the spatial relationships include relative placement
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