Ex Parte Iannace et al

Patent Trials and Appeals Board

Jan 22, 2019

14169866 - (D) (P.T.A.B. Jan. 22, 2019)

UNITED STA TES p A TENT AND TRADEMARK OFFICE
APPLICATION NO. FILING DATE
14/169,866 01/31/2014
125619 7590 01/24/2019
Mastercard International Incorporated
c/o Buckley, Maschoff & Talwalkar LLC
50 Locust A venue
New Canaan, CT 06840
FIRST NAMED INVENTOR
Marianne Iannace
UNITED STATES DEPARTMENT OF COMMERCE
United States Patent and Trademark Office
Address: COMMISSIONER FOR PATENTS
P.O. Box 1450
Alexandria, Virginia 22313-1450
www .uspto.gov
ATTORNEY DOCKET NO.
P01349-US-UTIL
(MOl.264)
CONFIRMATION NO.
7649
EXAMINER
STERRETT, JONATHAN G
ART UNIT PAPER NUMBER
3623
NOTIFICATION DATE DELIVERY MODE
01/24/2019 ELECTRONIC
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.
Notice of the Office communication was sent electronically on above-indicated "Notification Date" to the
following e-mail address(es):
martin@bmtpatent.com
szpara@bmtpatent.com
colabella@bmtpatent.com
PTOL-90A (Rev. 04/07)
UNITED STATES PATENT AND TRADEMARK OFFICE
BEFORE THE PATENT TRIAL AND APPEAL BOARD
Ex parte MARIANNE IANNACE and LUCKNER B. POLYCARPE
Appeal2017-004603
Application 14/169,866 1
Technology Center 3600
Before HUBERT C. LORIN, BRUCE T. WIEDER, and
ROBERT J. SILVERMAN, Administrative Patent Judges.
SILVERMAN, Administrative Patent Judge.
DECISION ON APPEAL
STATEMENT OF THE CASE
The Appellants appeal under 35 U.S.C. § 134(a) from the Examiner's
decision rejecting claims 1-20. We have jurisdiction under 35 U.S.C.
§ 6(b ).
We AFFIRM.
1 The Appellants identify MasterCard International Incorporated as the real
party in interest. Appeal Br. 2.
Appeal2017-004603
Application 14/169,866
ILLUSTRATIVE CLAIM
1. A method comprising:
receiving a first data set, the first data set including
anonymized transaction data representing purchase transactions
made by customers of a merchant;
receiving a second data set, the second data set including
anonymized transaction data representing purchase transactions
made by cardholders in a payment network;
filtering the second data set to remove therefrom data
relating to cardholders who are not customers of the merchant;
processing said first data set and said filtered second data
set using a probabilistic engine to establish linkages between
data in the first data set and data in the filtered second data set;
selecting a first data attribute with respect to data in the
first data set or other data supplied by the merchant;
selecting at least one second data attribute with respect to
data in the filtered second data set for which linkages exist with
data in the first data set;
defining a predictive model having at least one
independent variable and a dependent variable, said at least one
independent variable corresponding to said selected at least one
second data attribute and said dependent variable corresponding
to said selected first data attribute;
performing calculations using the predictive model to
generate output data; and
appending the output data to the first data set.
CITED REFERENCES
The Examiner relies upon the following references:
Kilger et al. US 7,490,052 B2 Feb. 10,2009
(hereinafter "Kilger")
Bernd Fischer & Joachim M. Buhmann, Bagging for Path-Based
Clustering, 25 IEEE TRANSACTIONS ON PATTERN ANALYSIS AND
MACHINE INTELLIGENCE (11 ), 1411 (2003) (hereinafter "Fischer")
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Chris Ding & Xiaofeng He, K-means Clustering via Principal
Component Analysis, Proceedings of the 21st International Conference
on Machine Leaming, Banff, Canada, 2004 (hereinafter "Ding")
REJECTIONS 2
I. Claims 1-20 are rejected under 35 U.S.C. § 101 as ineligible
subject matter.
II. Claims 1-20 are rejected under 35 U.S.C. § 112(a) as failing to
comply with the written description requirement. 3
III. Claims 1-20 are rejected under 35 U.S.C. § 112(b) as being
indefinite for failing to particularly point out and distinctly claim the subject
matter that the Appellants regard as the invention.
IV. Claims 1-3, 5-10, 12-17, 19, and 20 are rejected under
35 U.S.C. § 103(a) as unpatentable over Kilger and Fischer.
V. Claims 4, 11, and 18 are rejected under 35 U.S.C. § 103(a) as
unpatentable over Kilger, Fischer, and Ding.
FINDINGS OF FACT
The findings of fact relied upon, which are supported by a
preponderance of the evidence, appear in the following Analysis.
2 In addition to the enumerated rejections, the Final Office Action (pages
18-22) rejects claims 1, 8 and 15 on the ground of nonstatutory obviousness-
type double patenting. This rejection is withdrawn. See Answer 3, 23.
3 Although set forth under either 35 U.S.C. § 112(a) or 35 U.S.C. § 112 (pre-
AIA), first paragraph (see Final Action 23), the AIA version of the statute
applies herein, because the Application under review was filed after the
effective date of§ 4( c) of the Leahy-Smith America Invents Act (AIA)
(September 16, 2012). See, e.g., MPEP § 2161(I).
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ANALYSIS
Subject-Matter Eligibility
Under 35 U.S.C. § 101, an invention is patent-eligible if it claims a
"new and useful process, machine, manufacture, or composition of matter."
35 U.S.C. § 101. Yet, subject matter belonging to any of the statutory
categories may, nevertheless, be ineligible for patenting. The Supreme
Court has interpreted § 101 to exclude laws of nature, natural phenomena,
and abstract ideas, because they are regarded as the basic tools of scientific
and technological work, such that including them within the domain of
patent protection would risk inhibiting future innovation premised upon
them. Ass 'nfor Molecular Pathology v. Myriad Genetics, Inc., 569 U.S.
576, 589 (2013).
Of course, "[a]t some level, 'all inventions ... embody, use, reflect,
rest upon, or apply"' these basic tools of scientific and technological work.
Alice Corp. v. CLS Bankint'l, 134 S. Ct. 2347, 2354 (2014) (internal citation
omitted). Accordingly, evaluating ineligible subject matter, under this
judicial exclusion, involves a two-step framework for "distinguish[ing]
between patents that claim the buildin[g] block[ s] of human ingenuity and
those that integrate the building blocks into something more, thereby
transform[ing] them into a patent-eligible invention." Id. (internal quotation
marks and citation omitted). The first step determines whether the claim is
directed to judicially excluded subject matter (such as a so-called "abstract
idea"); the second step determines whether there are any "additional
elements" recited in the claim that ( either individually or as an "ordered
combination") amount to "significantly more" than the identified judicially
excepted subject matter itself. Id. at 2355.
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The USPTO recently published revised guidance on the application of
§ 101, in accordance with judicial precedent. 2019 Revised Patent Subject
Matter Eligibility Guidance, 84 Fed. Reg. 50, 52 (Jan. 7, 2019) ("2019
Revised Guidance"). Under the 2019 Revised Guidance, a claim is "directed
to" an abstract idea, only if the claim recites any of ( 1) mathematical
concepts, (2) certain methods of organizing human activity, and (3) mental
processes - without integrating such abstract idea into a "practical
application," i.e., without "apply[ing], rely[ing] on, or us[ing] the judicial
exception in a manner that imposes a meaningful limit on the judicial
exception, such that the claim is more than a drafting effort designed to
monopolize the judicial exception." Id. at 53-55. A claim so "directed to"
an abstract idea constitutes ineligible subject matter, unless it recites an
additional element ( or combination of elements) amounting to significantly
more than the abstract idea. Id. at 56.
As to the first step of the Alice framework the Examiner states that,
"[t]aken as a whole, the claim recites the abstract idea of using two different
data sets which are then processed and used to develop a model for
predicting customer behavior" that is considered to be "mathematical
relationships/formulas (i.e. which provide a prediction of customer shopping
or buying behavior based on past patterns)." Final Action 15. The
Examiner alternatively identifies the abstract idea as "processing customer
data from different databases for the purpose of generating a predictive
model of customer behavior," which the Examiner regards as a type of
"mathematical and/or statistical formulation." Id. at 14. The Examiner also
compares the present claims to those involved in Versata Development
Group, Inc. v. SAP America, Inc., 793 F.3d 1306 (Fed. Cir. 2015),
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explaining that the present claims amount to an "application of linking data
to form a predictive model" that is "merely a method of calculating."
Answer 10. Viewed through the lens of the 2019 Revised Guidance, 84 Fed.
Reg. at 52, the Examiner's analysis depicts the claimed subject matter as one
of the ineligible "[ c ]ertain methods of organizing human activity" that
include "advertising, marketing or sales activities or behaviors" and
"business relations."
Turning to the second step of the Alice framework, the Examiner
determines that the additional elements of the claims do not recite
significantly more than an abstract idea, but instead merely implement an
abstract idea by using routine computer functionality. Final Action 14, 15;
see also Answer 10.
The Appellants argue claims 1-20 as a group, treating claim 1 as
exemplary. Appeal Br. 8. Claim 1 is selected for analysis herein. See
37 C.F.R. § 4I.37(c)(l)(iv).
With regard to the first step of the Alice framework, the Appellants
contend that the Examiner's characterization of the claim language "is
crucially incomplete and fails to give 'full faith and credit' to the actual
details and complexity of the claimed invention." Appeal Br. 9. However,
this criticism refers to the Examiner's paraphrasing of only part of the
language of claim 1 - which the Examiner described as "[ d]efining a model
based on the linked variables and generating output" (Final Action 15)
( emphasis omitted)- rather than the Examiner's more detailed and
complete descriptions of the abstract idea, which are quoted above (see id.
at 14, 15). Elsewhere, the Appellants (Reply Br. 2-3) cite to an instance in
the Examiner's Answer referring to "the assertion ... that the claims are
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directed to an abstract idea of modelling data" (Answer 5). Yet, here again,
the Appellants, do not address the propriety of the Examiner's more
complete descriptions provide in the Final Office Action (pages 14 and 15).
A portion of the Appeal Brief (on page 10) identifies one of the
Examiner's more complete descriptions of the abstract idea - "processing
customer data from different databases for the purpose of generating a
predictive model of customer behavior" (see Final Action 14). Here, the
Appellants proceed to argue:
The Examiner likens this alleged abstract idea to one concerned
with "mathematical and/or statistical formulation." However, a
more accurate reading of the Examiner's statement of the
"abstract idea" would lead to a conclusion that the claims are
concerned with the field of computerized data processing,
including analysis of data stored in computer databases. This is
not a disembodied mathematical concept, but rather is
concerned with the widespread and practical field of data
analytics performed by computer.
Appeal Br. 10. Yet, the Appellants do not provide any basis for the
suggestion that the Examiner's position requires the claims to be directed to
"a disembodied mathematical concept." See id. Nor do the Appellants
explain why a solution from "the widespread and practical field of data
analytics performed by computer" cannot be an abstract idea. See id. See
also Reply Br. 3 ("[I]f one considers, 'what did the inventors invent?' -
then the answer is a specific improvement in the field computerized [sic]
data analytics, not an abstract idea.")
Similarly, the Appellants do not present any reason why the abstract
idea identified by the Examiner might be integrated into a practical
application, regarded in view of the second prong of "Revised Step 2A" of
the 2019 Revised Guidance, 84 Fed. Reg. at 54--55. Although the
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Appellants argue that claim 1 constitutes "a specific improvement in the
field computerized [sic] data analytics, not an abstract idea" (Reply Br. 3),
the alleged improvement is nothing more than implementing the identified
abstract idea in a computer environment. See Enfish, LLC v. Microsoft
Corp., 822 F.3d 1327, 1335-36 (Fed. Cir. 2016) ("[T]he first step in the
Alice inquiry in this case asks whether the focus of the claims is on the
specific asserted improvement in computer capabilities ... or, instead, on a
process that qualifies as an 'abstract idea' for which computers are invoked
merely as a tool.")
The Appellants also contend that the claims are not directed to an
abstract idea, because "the claims are completely different from the claims
in the Alice case, in which the claims merely recite computerization of a
conventional business practice." Appeal Br. 10. This argument is
unpersuasive, because it says nothing about the propriety of the Examiner's
determination of what the claims in this Appeal are directed to. Moreover,
the realm of abstract ideas is not restricted to any template based upon the
claims at issue in Alice.
Nor are we persuaded by the Appellants' criticism of the Examiner's
reliance upon Versata, wherein the Appellants assert that the Versata claims
involved "a computerized manner of determining prices, which is a
completely different type of subject matter from the data analytics field to
which the claims on appeal are related." Reply Br. 2. The Examiner's
reliance on Versata does not depend upon there being a precise match with
the claims in the present Appeal. Rather, the Examiner focuses on the
Versata claims and those in this Appeal as both being "method[ s] of
calculating." See Answer 10.
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Therefore, the Appellants do not persuasively argue that the Examiner
erred in performing the first step of the Alice framework.
With regard to the second step of the Alice framework ("Step 2B" of
the 2019 Revised Guidance, 84 Fed. Reg. at 56-57), the Appellants liken
claim 1 to those in DDR Holdings, LLC v. Hotels.com, LP, 773 F.3d 1245
(Fed. Cir. 2014), alleging that claim 1 "goes beyond what is routine and
conventional." Appeal Br. 10-11. More particularly, the Appellants
contend:
The claims in this application ... involve computerized
analysis of databases to uncover insights that can be gleaned
from a linking of two databases. This further extension of
computer-based data analytics is inherently tied to the field of
data processing by computer. As such it overcomes a problem
specifically arising in the field of computerized data processing.
Moreover, the definition of variables for the predictive model in
claim 1 goes beyond what is routine or conventional in the field
of data analytics.
Id. at 11. According to the Appellants, "[ w ]hile predictive modeling by
computer is of course in general a common activity, it is not conventional or
routine to select an independent variable for the model and a dependent
variable for the model in the manner recited in the claims" (Reply Br. 3)-
"[i].e., with at least one independent variable that corresponds to an attribute
of the network data, and a dependent variable that corresponds to an attribute
of the merchant data" (Appeal Br. 10 n.6) (comparing the claimed subject
matter to claim 2 of the US PTO' s Example 21, provided in July 2015).
This argument is unpersuasive, because the claimed features that the
Appellants rely upon, as constituting "significantly more" than the abstract
idea, are part of what the Examiner identifies as the abstract idea. See Final
Action 14 ( describing the abstract idea as "processing customer data from
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different databases for the purpose of generating a predictive model of
customer behavior"). The Federal Circuit has explained that "a claimed
invention's use of the ineligible concept to which it is directed cannot supply
the inventive concept that renders the invention 'significantly more' than
that ineligible concept. BSG Tech LLC v. BuySeasons, Inc., 899 F.3d 1281,
1290 (2018).
Therefore, in view of the foregoing analysis, we are not persuaded of
Examiner error in the rejection of claim 1, for being ineligible subject
matter. Pursuant to 37 C.F.R. § 4I.37(c)(l)(iv), we sustain the rejection of
claims 1-20 under 35 U.S.C. § 101.
Written Description
The rejection for lack of adequate written description, in the present
Appeal, concerns the "probabilistic engine" and "predictive model"
limitations that appear in each of independent claims 1, 8, and 15. See Final
Action 23. In claim 1, these limitations are set forth as follows:
processing said first data set and said filtered second data
set using a probabilistic engine to establish linkages between
data in the first data set and data in the filtered second data set;
[and]
defining a predictive model having at least one
independent variable and a dependent variable, said at least one
independent variable corresponding to said selected at least one
second data attribute and said dependent variable corresponding
to said selected first data attribute.
(Emphasis added).
In regard to a statement in the Specification that "the probabilistic
engine 102 operates to perform an inferred match analysis to assess the
inferred linkage for uniqueness and direct linkage," so as to "allow[ ] further
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assurance of anonymity and avoid[ ] use of any [personally identifiable
information]," the Examiner states that "[h ]ow the probabilistic [engine]
actually functions to achieve this 'inferred match' is not disclosed." Final
Action 24 (quoting Spec. p. 8, 11. 1-3). See also Answer 12-15.
Similarly, the Examiner regards the Specification as lacking adequate
written description for the recited "predictive model" of claim 1. See Final
Action 25. Among its disclosures, the Specification states:
As is familiar to those who are skilled in the art,
predictive analysis typically involves applying a predictive
model to a data set. The prediction is performed by the
predictive model on the basis of one or more independent
variables, and with respect to a dependent variable. In
accordance with aspects of the present invention, the data set
with respect to which the predictive analysis is to be made is
formed from the linkage of filtered payment network
transaction data to merchant transaction data. The independent
variable or variables for the predictive model may be selected
(block 1012, FIG. 10) to correspond to one or more attributes of
the payment network transaction data .
. . . Examples of suitable types of predictive model include
logistic regression, linear regression, k-means clustering, a
decision tree and a genetic algorithm. The nature and use of
these and other types of predictive model are known to those
who are skilled in the art.
It is contemplated that other types of predictive models
may be used in addition to or instead of those types listed
above. Predictive Model Markup Language (PMML) may be
used to describe and define the desired predictive model(s).
Spec. p. 21, 11. 21-p. 22, 1. 3; p. 22, 1. 24--p. 23, 1. 1. According to the
Examiner, "[ w ]hile PMML is understood in the art, the reference to this fails
to provide adequate written description for what model has actually been
developed." Final Action 25 (footnote omitted). Further, the Examiner
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states that "[h ]ow these [identified techniques] are applied to solve the
problem at hand is not discussed nor explained by the specification" and
"each of these models could give different results as each of these rely on
different numerical techniques and are very different." Answer 16.
Pursuant to the written-description requirement of 35 U.S.C. § 112(a),
"the test for sufficiency is whether the disclosure of the application relied
upon reasonably conveys to those skilled in the art that the inventor had
possession of the claimed subject matter as of the filing date." Ariad
Pharm., Inc. v. Eli Lilly & Co, 598 F.3d 1336, 1351 (Fed. Cir. 2010) (en
bane) ( citations omitted). Yet, "the level of detail required to satisfy the
written description requirement varies depending on the nature and scope of
the claims and on the complexity and predictability of the relevant
technology." Id. (citation omitted).
Although the Examiner states that particular details of the recited
"probabilistic engine" and "predictive model" are not disclosed in the
Specification, the Examiner's analysis does not squarely address whether the
Specification would adequately convey, to a person of ordinary skill in the
art, possession of the claimed subject matter in question.
Furthermore, and contrary to the Examiner's position, the
Specification reflects that the disclosed uses of a "predictive model" would
be familiar to a person of ordinary skill in the art. See Spec. p. 21, 11. 21-22
("As is familiar to those who are skilled in the art, predictive analysis
typically involves applying a predictive model to a data set"), p. 22, 11. 25-
27 ("The nature and use of these and other types of predictive model are
known to those who are skilled in the art").
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Additionally, the Appellants refer to the previously submitted Iannace
Declaration, 4 indicating that both the "probabilistic engine" and the
"predictive model" are familiar to persons of ordinary skill in the art
(specifically, the field of data analytics), such that the disclosure of the
Specification reflects possession thereof. See Iannace Deel. ,r,r 6-12.
In view of the foregoing, we are persuaded that the Examiner has not
adequately shown that independent claims 1, 8, and 15 fail to satisfy the
written-description requirement. Accordingly, we do not sustain the
rejection of claims 1-20 under 35 U.S.C. § 112(a).
Indefiniteness
According to the Examiner, because independent claims 1, 8, and 15
recite limitations that "fail to have inadequate [ sic, adequate] written
description, the metes and bounds of these limitations are not clear." Final
Action 26. "For example," the Examiner explains, "the claims recite using a
probabilistic engine and defining a predictive model," but "[i]t is not clear
what is being recited here, since the specification does not say [what]
constitutes the 'probabilistic engine' or defined '[predictive] model."' Id.
at 27.
Contrary to the Examiner's position (see Final Action 26), a
Specification's insufficient written description, in violation of 35 U.S.C.
§ 112(a), does not necessarily establish indefinite claim language, in
violation of 35 U.S.C. § 112(b ).
During the Office's evaluation, under 35 U.S.C. § 112(b ), a proposed
patent "claim is indefinite when it contains words or phrases whose meaning
4 We refer to the Rule 132 Declaration of Marianne Iannace received
December 31, 2015. See Appeal Br. 12.
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is unclear," i.e., "ambiguous, vague, incoherent, opaque, or otherwise
unclear in describing and defining the claimed invention." In re Packard,
751 F.3d 1307, 1310-11 (Fed. Cir. 2014) (per curiam); see also In re
McAward, No. 2015-006416, 2017 WL 3669566, at *3, *5-*6 (PTAB Aug.
25, 2017) (precedential).
The Examiner has not adequately addressed the question of whether a
person of ordinary skill in the art would have sufficiently understood the
meaning of the recited "probabilistic engine" and "predictive model," in
independent claims 1, 8, and 15, in accordance with the requirement of claim
definiteness. By contrast, the Appellants have submitted a declaration
stating that a person of ordinary skill in the art of data analytics would
understand the meanings of the terms "probabilistic engine" (see Iannace
Deel. ,r,r 6, 10) and "predictive model" (see id. ,r,r 11-12).
Therefore, we do not sustain the rejection of claims 1-20 under 35
U.S.C. § 112(b).
Obviousness
The Appellants contend that, among other arguments for the non-
obviousness of independent claim 1, the cited Kilger reference fails to teach
the claimed features of the recited "independent variable" and "dependent
variable":
Although Kilger briefly discusses a predictive model [at col. 9,
11. 39-42], the reference does not mention independent or
dependent variables of a predictive model. To the extent that
Kilger discusses prediction of consumer behavior, it is without
the definition of variables for a predictive model as specifically
recited in claim 1.
Appeal Br. 15.
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The Examiner responds by focusing on a portion of Kilger ( col. 9, 11.
29-32) that refers to "utiliz[ing] a previous consumer behavior to predict the
behavior of the respondent (e.g., the consumer) in the future." The
Examiner states:
Here the "previous customer behavior" is the independent
variable (i.e. predictions are based upon this variable) and the
respondent (e.g. consumer) is the dependent customer variable
(i.e. the variable being predicted). Thus Kilger teaches
independent and dependent customer variables as much as
claimed.
Answer 23.
Yet, the Appellants contend that "[t]he Examiner's reading of Kilger
strays far from the actual language of the claims," arguing that "[i]n the
claims, to be precise, the independent variable is specified to be an attribute
of payment network transaction data (not previous customer behavior) and
the dependent variable is specified to be an attribute of merchant transaction
data (not a respondent)." Reply Br. 4.
Indeed, claim 1 requires an "independent variable" that
"correspond[ s] to" a "second data attribute" (i.e., an attribute of "the second
data set including anonymized transaction data representing purchase
transactions made by cardholders in a payment network"), whereas the
recited "dependent variable" must "correspond[ ] to" a "first data attribute"
(i.e., an attribute of "the first data set including anonymized transaction data
representing purchase transactions made by customers of a merchant" or
"other data supplied by the merchant"). The claimed technique analyzes one
"data set" (including payment network data), in order to make predictions
regarding a second "data set" (including the merchant information).
According to the Specification, the significance of the claimed requirements
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for the "independent variable" and the "dependent variable" is that
merchants may use the results of a predictive analysis of payment network
transaction data, in order to improve customer marketing and promotional
efforts directed toward the merchant's own customers. Spec. p. 3, 11. 3-8.
See also id. at p. 11, 11. 22-24, and p. 21, 1. 24--p. 22, 1. 27. By contrast,
Kilger analyzes consumer data in an integrated database (formed by
"combining two or more market research databases"), in order to make
predictions about the future behavior (e.g., shopping patterns) of the entire
combined set of consumers being analyzed. Kilger, col. 9, 11. 20-21, 39-42.
In view of the foregoing, we do not sustain the rejection of
independent claim 1 and, for similar reasons, independent claims 8 and 15,
along with their respective dependent claims 2-7, 9-14, and 16-20, under
35 U.S.C. § 103(a).
DECISION
We AFFIRM the Examiner's decision rejecting claims 1-20 under 35
U.S.C. § 101.
We REVERSE the Examiner's decision rejecting claims 1-20 under
35 U.S.C. § 112(a).
We REVERSE the Examiner's decision rejecting claims 1-20 under
35 U.S.C. § 112(b ).
We REVERSE the Examiner's decision rejecting claims 1-20 under
35 U.S.C. § 103(a).
No time period for taking any subsequent action in connection with
this appeal may be extended under 37 C.F.R. § 1.136(a).
AFFIRMED
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