Appeal No. 2006-2225
Application No. 09/815,439
where such sub-items represent at least one of depth and breadth information relating to
the item as claimed.
Herz’ system automatically identifies and retrieves target objects (i.e., digital data
representing newspaper stories, movies, items to purchase, etc.) [Herz, col. 6, lines 12-
15]. Notably, the user in Herz wishes to locate some small subset of the target objects,
such as the target objects that the user most desires to read, investigate, purchase, etc.
[Herz, col. 9, lines 51-58]. Information delivery is based on the similarity between a profile
for the target object and profiles for target objects for which the user has previously
provided positive feedback [Herz, col. 6, lines 16-20].
An application of such a technique is a customized electronic newspaper. In this
application, target objects are news articles that the user receives or potentially receives
[Herz, col. 7, lines 17-19]. A filtering technique automatically selects a set of articles that
the user is likely to desire to read from a larger group of articles (e.g., all items on the AP
news wire service, all advertisements in a set of newspapers, etc.) [Herz, col. 7, lines 19-
27]. The accuracy of this filtering system improves over time by noting which articles the
user reads and measuring the depth to which the user reads each article. This information
is then used to update the user’s target profile interest summary [Herz, col. 7, lines 27-31].
See also Herz, col. 55, line 42 – col. 61, line 28 (discussing dynamically selecting relevant
articles for a customized news clipping service based on the disclosed technique).
Herz’ filtering technique, in our view, automatically retrieves sub-items from a
storage medium and selects such sub-items dynamically based on at least one
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