Ex Parte Selinger et al

Patent Trial and Appeal Board

Apr 28, 2017

12012451 (P.T.A.B. Apr. 28, 2017)

United States Patent and Trademark Office
UNITED STATES DEPARTMENT OF COMMERCE
United States Patent and Trademark Office
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Alexandria, Virginia 22313-1450
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APPLICATION NO. FILING DATE FIRST NAMED INVENTOR ATTORNEY DOCKET NO. CONFIRMATION NO.
12/012,451 02/01/2008 David Selinger 800054.407 2820
500 7590 04/28/2017
SFFD TNTFT T FFTT TAT PROPFRTY T AW GROT TP T T P
EXAMINER
701 FIFTH AVE POUNCIL, DARNELL A
SUITE 5400
SEATTLE, WA 98104 ART UNIT PAPER NUMBER
3621
MAIL DATE DELIVERY MODE
04/28/2017 PAPER
Please find below and/or attached an Office communication concerning this application or proceeding.
The time period for reply, if any, is set in the attached communication.
PTOL-90A (Rev. 04/07)
UNITED STATES PATENT AND TRADEMARK OFFICE
BEFORE THE PATENT TRIAL AND APPEAL BOARD
Ex parte DAVID SELINGER,
TYLER KOHN,
MICHAEL DeCOURCEY,
SUNDEEP AHUJA, JAMES OSIAL,
and ALBERT SUNWOO
Appeal 2015-000819
Application 12/012,451
Technology Center 3600
Before HUBERT C. LORIN, ANTON W. FETTING, and
BIBHU R. MOHANTY, Administrative Patent Judges.
FETTING, Administrative Patent Judge.
DECISION ON APPEAL
STATEMENT OF THE CASE1
David Selinger, Tyler Kohn, Michael DeCourcey, Sundeep Ahuja,
James Osial, and Albert Sunwoo (Appellants) seek review under
35 U.S.C. § 134 of a non—final rejection of claims 1—20, the only claims
1 Our decision will make reference to the Appellants’ Appeal Brief (“App.
Br.,” filed December 23, 2013) and Reply Brief (“Reply Br.,” filed October
17, 2014), and the Examiner’s Answer (“Ans.,” mailed August 18, 2014),
and Non-Final Action (“Non-Final Act.,” mailed July 19, 2013).
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Application 12/012,451
pending in the application on appeal. We have jurisdiction over the appeal
pursuant to 35 U.S.C. § 6(b).
The Appellants invented a way of providing targeted content, such as
advertising, by analyzing the context in which the content is to be provided
in light of known attributes of the content available to be provided and the
one or more recipients of the content. Specification para. 1.
An understanding of the invention can be derived from a reading of
exemplary claim 1, which is reproduced below (bracketed matter and some
paragraphing added).
1. A computer-implemented process comprising:
[1] generating a user model for a user
based at least in part on interactions between the user and
a first originating retailer,
the generating of the user model being performed by a
configured computer system;
[2] receiving a request from a manufacturer of one or [more]
products sold by one or more originating retailers that include
the first originating retailer,
the request being to advertise the one or more products,
the receiving of the request being performed by the
configured computer system;
[3] identifying at least one of the one or more products to
advertise to the user
by applying advertisement-specific selection models to
the user model
to identify which of the one or more products is relevant
to the user
based on information included in the applied
advertisement- specific selection models regarding types
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of users to which the at least one products are
marketable,
the identifying of the at least one products being
performed by the configured computer system;
and
[4] sending a communication to the user
including one or more advertisements for the identified at
least one products,
wherein the sent communication is configured
to appear to the user to have been sent by the first
originating retailer,
the sending of the communication being performed by
the configured computer system.
The Examiner relies upon the following prior art:
Van Der Riet US 2003/0126146 A1 July 3, 2003
Goyal US 2009/0030785 A1 Jan. 29, 2009
Barton US 2009/0192888 A1 July 30, 2009
Claims 1—4, 7—10, 13—17, and 20 stand rejected under 35 U.S.C.
§ 103(a) as unpatentable over Barton and Van Der Riet.
Claims 5,11, and 18 stand rejected under 35 U.S.C. § 103(a) as
unpatentable over Barton, Van Der Riet, and Goyal.
Claims 6, 12, and 19 stand rejected under 35 U.S.C. § 103(a) as
unpatentable over Barton, Van Der Riet, and Official Notice.
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ISSUES
The issues of obviousness turn primarily on whether the representational
characterizations Barton describes are within the scope of models.
FACTS PERTINENT TO THE ISSUES
The following enumerated Findings of Fact (FF) are believed to be
supported by a preponderance of the evidence.
Facts Related to Claim Construction
01. An advertisement-specific selection model is a model that
includes information regarding the types of users to which a
particular advertisement is to be directed. Spec. para. 126.
02. The Specification does not lexicographically define a model.
03. The ordinary meaning of a model is a representation of
something.2
Facts Related to Appellants ’ Disclosure
04. An advertisement-specific selection model is a model that
includes information regarding the types of users to which a
particular advertisement is to be directed. It is analogous in form
and function to the various selection models described herein,
with the distinction that the advertisement-specific selection
2 American Heritage Dictionary,
https://www.ahdictionary.com/word/search.html?q=model.
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model is based on information regarding the data/demographics of
user models to be selected. For example, based on data collected
as part of this and other systems and processes, it may be known
that a particular product is highly marketable within a given age
range, gender, geographic location, income level, race, purchasing
history, etc. This identified demographic information would be
included as the data set within the advertisement-specific selection
model and would be used to search and identify the desired user
models to be selected and utilized in the process for identifying a
subset of users for which a non-competitive advertisement is
relevant. Spec. para. 126.
Facts Related to the Prior Art
Barton
05. Barton is directed to targeted advertisements. Barton para. 2.
06. Barton describes obtaining purchase information submitted by a
user making a purchase on the website. The purchase information
is used to determine an advertisement for a product or service
related to the purchase but of a different type than the purchase.
An advertisement is displayed on the website when the purchase is
completed. Barton para. 7.
07. Barton describes retailers wishing to place their advertisements
in opportune times and places. Targeted advertisements can be
more effective and cost efficient when displayed at the time, or
immediately after, a user has acted on a decision to purchase and
is waiting for a confirmation message. The act performed may be
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the submission of information at checkout. Rather than displaying
advertisements for goods or services similar to the good or service
just purchased, Barton describes displaying advertisements for
goods or services that are related to and/or complementary to the
good or service just purchased. The user is more likely to
purchase a related or complementary good or service than a
similar good or service, since there is no need for a good or
service similar to that just purchased. Further, it is likely that the
related or complementary good or service will be highly relevant
to the user, since the user was interested enough to complete a
purchase for the purchased good or service. Purchase information
may include but is not limited to information about the product(s)
or service(s), the cost of the product(s), the amount the user paid,
the location of the user, personal and financial information, the
behavior of the user on the website, products selected and
removed before checkout, or any other information that could be
used to determine a relevant advertisement. Barton paras. 17—18.
08. Barton describes purchase information being analyzed to
determine advertisements for products or services that are related
and/or complementary to the product or service purchased. This
analysis may include comparing the purchase information to
comparative information. This comparative information may be
obtained by observing the user or the user's actions on the website.
Comparative information may also be information previously,
currently, or dynamically obtained from another source, database,
or party. The comparative information may include information
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about follow-on-purchase keyword purchases, keyword-
advertisement relationship information, aggregated information
from purchase or checkout histories, website search information,
one or more personalized search histories, index word proximity
information for one or more websites, retailer advertisement
bidding information, product search clustering information,
content of the landing or confirmation page during checkout,
click-through rates of advertising over time, or keyword
information provided by a third party. Comparative information
can also include purchase information from other users or from
previous purchases by the same user. Barton paras. 24—25.
09. Barton describes purchase information being analyzed to select
one or more advertisements for products or services that are
complementary and/or related to the purchased product or service.
The advertisement for a complementary and/or related product or
service may be selected based on a type of product or service
included in the advertisement. That is, rather than selecting for
display an advertisement for a similar type of product or service,
an advertisement for a different type of product or service that is
related in some way to the product or service purchased may be
selected for display. For example, books are of a different type of
product than flight information. A user may purchase a book
about visiting India. Upon purchase, existing websites may show
similar books about visiting India, chosen by previous purchasers
of the selected book. Alternatively, such a purchase may result in
a display of an advertisement for a good or service that is of a
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different type of product or service than that of the book. Barton
para. 29.
Van Der Riet
10. Van Der Riet is directed to interactive marketing
communication and transaction/distribution services platform for
building and managing personalized customer relationships. This
provides consumers with privacy, product/retailer (re)search,
shopping and ad based personalized info, news and entertainment
services, its manufacturing and retailing clients with interactive
marketing communication, IT, research support and effectiveness
benchmarking services and interactive media and telecom
companies with premium advertising, needed to develop
profitable ad-based personalized interactive info, news and
entertainment services. Van Der Riet para. 1.
11. Van Der Riet describes holistic consumer profiles being created
by capturing consumer purchase behavior and preferences for the
largest possible range of product brands, categories, and retailers.
The holistic purchase-behavior specific consumer profiles allow
manufacturers and/or retailers to customize their product and
category presentations to reflect an individual consumer's needs,
independent of the portal that the consumer is using and
independent of the retailer where the consumer is purchasing. The
consumer profiles also allow manufacturers and/or retailers to
reach their consumers, by placing consumer customized purchase-
behavior specific advertising messages on the consumer's
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personalized interactive shopping and ad sponsored info, news and
entertainment services. Advertisers may customize their
advertising messages on these services to reflect individual
consumer's purchase and shopping needs, independent of the
portal that the consumer has been using and independent of the
retailers where the consumer has been making purchases. By
sponsoring content delivery with premium, customized
advertising messages, it is possible to decrease the consumer's
price for such services. Consumer's receive such services in
return for consumers accepting the advertising exposure as well as
agreeing to the registration of their shopping and purchase
behavior, in a way that provides consumers with full control over
their profile data and that permits this data to be processed into
aggregated retailer and portal independent consumer feedback
information, that can be automatically processed and channeled
back to manufacturers and/or retailers. The processing of data
allows manufacturers and/or retailers to receive portal and retailer
independent information about consumer's needs as well as
information that permits manufacturers and/or retailers to
benchmark their different product and/or category presentations
and customized ad messages against each other, thus, enabling
them to evaluate the effectiveness of their communication
programs, assortments and products. Van Der Riet paras. 19—20.
12. Van Der Riet describes each participating manufacturer using
its Product Presentation Database to control/customize its
presentations. Features which may be customized include,
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without limitation, specification of product presentation, target
audience, and exposure timings. The product presentation
database may be used by participating retailers to access and
provide up-to-date product presentations, by participating portals
to obtain the product presentation for consumers, by participating
consumers to get up-to-date product presentations, and/or by each
participating manufacturer to get effectiveness measurement data,
such as indicators on the presentation's impact on consumer's
shopping behavior, benchmarking data for comparing the
performance of presentations against each other, or measurement
standards for assessing presentations portal and retailer
independent. Van Der Riet paras. 145—146.
13. The product presentation database is filled with product
presentation data that is uploaded by manufacturers of goods,
providers of services and retailers in the case of retailer branded
private-label products. Manufacturers, for example, may submit
presentation information for each of its products to the product
presentation database and may update that information over time,
as their product line, product availability, or specific product
specifications may change. Further, the manufacturer will
populate the ad messages database with advertisements to be
delivered to a specific consumer target audience, based on
purchase-based profile criteria and/or consumer audience that the
advertiser wants to reach with his advertising message.
Van Der Riet para. 159.
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Goyal
14. Goyal is directed to translating user interaction with rich media
advertising into brand effectiveness models. Goyal para. 2.
15. Goyal describes calculating brand index (BI) for interactive rich
media advertising that produces a brand effectiveness model. The
method includes categorizing advertising exposure of a rich media
ad into a type of bucket in memory, and for each type of bucket by
a processor: assigning a weight to each of a plurality of data types
collected in the bucket stored in memory, assigning a score in
memory to each of the data types collected in the bucket, tracking
a frequency of occurrence of each data type, and calculating a
bucket brand index (BBI) for the bucket as a product of the
assigned weight, the assigned score, and the tracked frequency.
The method further includes assigning a bucket weight to each
type of bucket stored in memory, calculating a weighted sum of a
plurality of BBIs of the buckets to generate an overall brand index
(BI) for an ad campaign by summing the weight of each bucket
times the BBI of each respective bucket, and communicating the
BI of the campaign to an advertiser or publisher as an indication
of the monetization value of the rich media ad. Goyal para. 8.
16. Goyal describes categorizing advertising exposure of some of a
plurality of rich media ads into a first type of bucket stored in
memory, and for each first type of bucket a processor: assigning a
weight to each of a plurality of data types collected in the bucket,
assigning a score to each of the data types collected in the bucket,
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tracking a frequency of occurrence of each data type, and
calculating the bucket brand index (BBI) for the bucket as a
product of the assigned weight, the assigned score, and the tracked
frequency. The method further includes categorizing advertising
exposure of the remainder of the plurality of rich media ads into a
second type of bucket stored in memory, and for each second type
of bucket the processor: collecting a plurality of data types
(d.sub.l, d.sub.2, . . . , d.sub.m) in the bucket stored in memory,
and expressing a bucket brand index (BBI) as a function of the
plurality of datatypes, f(d.sub.l, d.sub.2, . . . , d.sub.m), wherein
the function is finite, non-negative, and real for all non-negative
and finite (d). The method further includes assigning a bucket
weight to each first and second types of buckets stored in memory,
calculating a weighted sum of a plurality of BBIs of the first and
second buckets to generate an overall brand index (BI) for an ad
campaign by summing the weight of each bucket times the BBI of
each respective bucket, and communicating the BI of the
campaign to an advertiser or publisher as an indication of the
monetization value of the rich media ad. Goyal para. 8.
ANALYSIS
We adopt the Examiner’s findings and analysis from Final Action 3—7
and Answer 3—12 and reach similar legal conclusions. We now address the
arguments in the Reply Brief.
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Claims / 4, 7—10, 13—17, and 20 rejected under 35 U.S.C. § 103(a) as
unpatentable over Barton and Van Der Riet
We are not persuaded by Appellants' argument that the Examiner fails to
demonstrate that the relied-upon references disclose using an advertisement-
specific selection model that specifies a type of user for a product. Reply
Br. 6—10. As the claims revolve around models, we first construe a model.
A model is a representation of something. FF 02—03.
The Examiner finds that Barton describes a user model as the user being
represented by a transaction. This models the user’s behavior and product
desired based on an actual transaction. The Examiner then finds that Barton
describes an advertisement-specific selection model as the representation of
ads for products that are related and/or complementary to the product or
service purchased. Final Act. 3—5. See also FF 07.
The Specification defines such a model as one that includes information
regarding the types of users to which a particular advertisement is to be
directed. FF 01. Barton represents user types by the products they purchase,
and Barton’s advertisement selection model applies its selection criteria to
an actual purchase. Thus, Barton applies its advertisement selection model
to the actual purchase user model to identify which of the one or more
products is relevant to the user based on information regarding related and/or
complementary products included in the applied advertisement selection
models regarding types of users based on actual purchases to which the
purchased products are marketable.
We are not persuaded by Appellants' argument that the Examiner fails to
demonstrate that the relied-upon references disclose that a product
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advertisement sent to a user is configured to appear to be from a retailer that
sells the product, but is sent based on a received request from a manufacturer
of the product, after identifying the user as being appropriate for the product
based in part on previous interactions between the user and the retailer.
Reply Br. 10—13.
Appellants did not raise this issue in the Appeal Brief and nothing in the
Examiner’s Answer response would trigger this argument. The Examiner
was not given the opportunity to respond to this argument in the Answer. In
any event, we find that this limitation is undeserving of patentable weight.
The limitation recites no implementation for how the communication is
configured to appear to the user to have been sent by the first originating
retailer. Thus the limitation only recites a perception discemable only in the
mind of the beholder. Such perceptual limitations are afforded no patentable
weight. In re Bernhart, 417 F.2d 1395, 1399 (CCPA 1969). The test for
whether patentable weight should be afforded is whether the steps rely on
the limitation or the limitation relies on the steps. In re Ngai, 367 F.3d
1336, 1339 (Fed Cir 2004). Here the steps in no way depend on the
perception of the ad appearing to be from a retailer and perception of the ad
appearing to be from a retailer in no way depends on the steps. This is again
because no implementation is recited that would physically or functionally
narrow how the perception is caused.
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Claims 5, 11, and 18 rejected under 35 U.S.C. § 103(a) as unpatentable over
Barton, Van Der Riet, and Goyal
These claims recited identifying by a weighted scoring system
correlations between the user model and the advertisement-specific selection
models. We are not persuaded by Appellants' argument that Goyal fails to
describe this. Reply Br. 13—16. Goyal describes the notoriously well-
known use of weights for correlating statistics in behavioral models,
particularly those used in advertising. Appellants essentially argue that
Goyal does not explicitly describe using this in the exact set of models
recited in the claims. But as Barton already describes such models, Goyal is
only applied to show it was known to improve such a model based on
weighted correlations.
Claims 6, 12, and 19 rejected under 35 U.S.C. § 103(a) as unpatentable over
Barton, Van Der Riet, and Official Notice
These are not separately argued in the Reply Brief.
CONCLUSIONS OF LAW
The rejection of claims 1—4, 7—10, 13—17, and 20 under 35 U.S.C.
§ 103(a) as unpatentable over Barton and Van Der Riet is proper.
The rejection of claims 5, 11, and 18 under 35 U.S.C. § 103(a) as
unpatentable over Barton, Van Der Riet, and Goyal is proper.
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The rejection of claims 6, 12, and 19 under 35 U.S.C. § 103(a) as
unpatentable over Barton, Van Der Riet, and Official Notice is proper.
DECISION
The rejection of claims 1—20 is affirmed.
No time period for taking any subsequent action in connection with this
appeal may be extended under 37 C.F.R. § 1.136(a). See 37 C.F.R.
§ 1.136(a)(l)(iv) (2011).
AFFIRMED
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