Appeal 2007-0271
Application 09/750,948
3. Net Perceptions discloses “generat[ing] a set of rules based upon
said patterns” in that such rules would be required for the recommendation
engine to “prompt[] agents with pertinent customer information and specific
purchase recommendations for whoever is on the line”. (Id. See also
Answer 9.)
4. One of ordinary skill in the art would equate “a rules engine”
(Spec. 1), with a “recommendation engine” (claim 11). (See also Net
Perceptions, ¶ 4; Andrew passim.)
5. Finally, Net Perceptions discloses “using a recommendation engine
to apply said rules to a current customer interaction to recognize one or more
of said patterns in said interaction and suggest an interaction strategy
corresponding to said recognized patterns.” (See Net Perceptions, ¶¶ 2-4
(“system’s recommendation engine zeroes in on individual preferences by
pooling information from current customers and previous calls, and by
drawing upon a database of information on other customers with similar
buying patterns” and “prompts agents with pertinent customer information
and specific purchase recommendations” based on the identified patterns).)
6. Andrews further describes Net Perceptions’ recommendation
engines and their versatility and identifies Net Perceptions as one company
offering recommendation engines. (See Andrews passim.)
7. Andrews discloses, or at least suggests, using “executable
instructions for analyzing customer data from [a] plurality of channels.”
(Andrews, ¶ 1 (“recommendation engines,” such as that of Net Perceptions,
“can use multiple channels”). See also Andrews, ¶ 4 (“Net Perceptions’
recommendation engine . . . provide[s] advice to consumers . . . through
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