Appeal No. 2006-2225
Application No. 09/815,439
predetermined factor as claimed. The “sub-items” correspond to the selected set of
articles. Such sub-items represent at least the breadth of information relating to the item
(i.e., the scope of topics that the user is most interested) [see also Herz, col. 18, lines 28-
38]. We further note that Herz’ teaching of presenting a hierarchical cluster tree of target
objects to the user also fully meets the claimed limitation calling for automatically retrieving
sub-items and selecting such sub-items dynamically based on a predetermined factor as
claimed. Herz teaches automatically reorganizing the cluster tree so that clusters that are
most interesting to the user are identified [Herz, col. 69, lines 20-28]. Furthermore, the
system can display a special list of the most interesting clusters, or the most interesting
subclusters of the current cluster [Herz, col. 69, lines 29-34]. Notably, such automatic
reorganization includes, among other things, migrating interesting clusters higher in the
tree and even suppressing clusters with low interest scores from the menus entirely. As a
result, a customized tree develops that is more easily navigated [Herz, col. 69, lines 43-
63].
For example, such an automated hierarchical menu system can be applied in an
electronic mall application where target objects or clusters of target objects can be
automatically grouped based on certain criteria at the level of specific items (e.g., specific
brands and sizes of soaps and shampoos) and classes of items (e.g., soaps and
shampoos generally) [Herz, col. 71, lines 56-66]. Such a system, in our view, amply
teaches automatically retrieving sub-items from a storage medium and selecting such sub-
items dynamically based on a predetermined factor as claimed. Moreover, dynamically
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