SAS Institute Inc.

Patent Trials and Appeals Board

Oct 4, 2021

2020003289 (P.T.A.B. Oct. 4, 2021)

UNITED STATES PATENT AND TRADEMARK OFFICE
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
APPLICATION NO. FILING DATE FIRST NAMED INVENTOR ATTORNEY DOCKET NO. CONFIRMATION NO.
16/030,142 07/09/2018 Hansi Jiang 04500-0075-02 3173
114605 7590 10/04/2021
Bell & Manning, LLC
2801 West Beltline Hwy.
Ste. 210
Madison, WI 53713
EXAMINER
LAROCQUE, EMILY E
ART UNIT PAPER NUMBER
2182
NOTIFICATION DATE DELIVERY MODE
10/04/2021 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):
cbell@bellmanning.com
docketing@bellmanning.com
eofficeaction@appcoll.com
PTOL-90A (Rev. 04/07)
UNITED STATES PATENT AND TRADEMARK OFFICE
BEFORE THE PATENT TRIAL AND APPEAL BOARD
Ex parte HANSI JIANG, WENHAO HU, HAOYU WANG, DEOVRAT
VIJAY KAKDE, and ARIN CHAUDHURI
Appeal 2020-003289
Application 16/030,142
Technology Center 2100
Before JEREMY J. CURCURI, NATHAN A. ENGELS, and
AMEE A. SHAH, Administrative Patent Judges.
CURCURI, Administrative Patent Judge.
DECISION ON APPEAL
STATEMENT OF THE CASE
Pursuant to 35 U.S.C. § 134(a), Appellant1 appeals from the
Examiner’s decision to reject claims 1–30. We have jurisdiction under
35 U.S.C. § 6(b).
We AFFIRM.

1 We use the word Appellant to refer to “applicant” as defined in 37 C.F.R.
§ 1.42(a). Appellant identifies the real party in interest as SAS Institute Inc.
Appeal Br. 3.
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Application 16/030,142
2
CLAIMED SUBJECT MATTER
The claims are directed to an “[a]nalytical system to incrementally
update a support vector data description for outlier identification.” Spec.,
Title. Claim 29, reproduced below, is illustrative of the claimed subject
matter:
29. A computing device comprising:
a processor; and
a non-transitory computer-readable medium operably
coupled to the processor, the computer-readable medium having
computer-readable instructions stored thereon that, when
executed by the processor, cause the computing device to
compute a Gaussian similarity matrix between a
plurality of observation vectors, wherein each
observation vector of the plurality of observation vectors
includes a variable value for each variable of a plurality
of variables;
compute an inverse Gaussian similarity matrix
from the computed Gaussian similarity matrix;
compute a row sum vector that includes a row sum
value computed from each row of the computed inverse
Gaussian similarity matrix;
select a set of boundary support vectors from the
plurality of observation vectors by removing any interior
vectors from the plurality of observation vectors, wherein
the set of boundary support vectors define a boundary
around the plurality of observation vectors, wherein the
computed inverse Gaussian similarity matrix and the
computed row sum vector are updated based on the
selected set of boundary support vectors to define a
trained support vector data description (SVDD) model;
(a) select a new observation vector from an event
stream or from an input dataset;
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(b) compute an acceptance value for the selected
new observation vector using the selected set of
boundary support vectors, the computed row sum vector,
and the new observation vector;
(c) when the computed acceptance value is greater
than zero, compute an incremental vector from the
computed inverse Gaussian similarity matrix and the
selected new observation vector;
(d) when the computed acceptance value is greater
than zero and when a maximum value of the computed
incremental vector is less than a first predefined tolerance
value, output an indicator that the selected new
observation vector is an abnormal observation vector
relative to the selected set of boundary support vectors;
and
(e) repeat (a) to (d) until the event stream is
stopped or a last observation vector is selected from the
input dataset in (a).
REJECTION
Claims 1–30 are rejected under 35 U.S.C. § 101 as directed to a
judicial exception without significantly more. Final Act. 4–12.
PRINCIPLES OF LAW
An invention is patent-eligible if it claims a “new and useful process,
machine, manufacture, or composition of matter.” 35 U.S.C. § 101.
However, the Supreme Court has long interpreted 35 U.S.C. § 101 to include
implicit exceptions: “[l]aws of nature, natural phenomena, and abstract
ideas” are not patentable. E.g., Alice Corp. v. CLS Bank Int’l, 573 U.S. 208,
216 (2014).
In determining whether a claim falls within an excluded category, we
are guided by the Supreme Court’s two-step framework, described in Mayo
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and Alice. Id. at 217–18 (citing Mayo Collaborative Servs. v. Prometheus
Labs., Inc., 566 U.S. 66, 75–77 (2012)). In accordance with that framework,
we first determine what concept the claim is “directed to.” See Alice, 573
U.S. at 219 (“On their face, the claims before us are drawn to the concept of
intermediated settlement, i.e., the use of a third party to mitigate settlement
risk.”); see also Bilski v. Kappos, 561 U.S. 593, 611 (2010) (“Claims 1 and 4
in petitioners’ application explain the basic concept of hedging, or protecting
against risk.”).
Concepts determined to be abstract ideas, and thus patent ineligible,
include certain methods of organizing human activity, such as fundamental
economic practices (Alice, 573 U.S. at 219–20; Bilski, 561 U.S. at 611);
mathematical formulas (Parker v. Flook, 437 U.S. 584, 594–95 (1978)); and
mental processes (Gottschalk v. Benson, 409 U.S. 63, 69 (1972)). Concepts
determined to be patent eligible include physical and chemical processes,
such as “molding rubber products” (Diamond v. Diehr, 450 U.S. 175, 192
(1981)); “tanning, dyeing, making waterproof cloth, vulcanizing India
rubber, smelting ores” (id. at 184 n.7 (quoting Corning v. Burden, 56 U.S.
252, 267–68 (1854))); and manufacturing flour (Benson, 409 U.S. at 69
(citing Cochrane v. Deener, 94 U.S. 780, 785 (1876))).
In Diehr, the claim at issue recited a mathematical formula, but the
Supreme Court held that “[a] claim drawn to subject matter otherwise
statutory does not become nonstatutory simply because it uses a
mathematical formula.” Diehr, 450 U.S. at 176; see also id. at 192 (“We
view respondents’ claims as nothing more than a process for molding rubber
products and not as an attempt to patent a mathematical formula.”). Having
said that, the Supreme Court also indicated that a claim “seeking patent
protection for that formula in the abstract . . . is not accorded the protection
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of our patent laws, . . . and this principle cannot be circumvented by
attempting to limit the use of the formula to a particular technological
environment.” Id. (citing Benson and Flook); see, e.g., id. at 187 (“It is now
commonplace that an application of a law of nature or mathematical formula
to a known structure or process may well be deserving of patent
protection.”).
If the claim is “directed to” an abstract idea, we turn to the second
step of the Alice and Mayo framework, where “we must examine the
elements of the claim to determine whether it contains an ‘inventive
concept’ sufficient to ‘transform’ the claimed abstract idea into a patent-
eligible application.” Alice, 573 U.S. at 221 (quotation marks omitted). “A
claim that recites an abstract idea must include ‘additional features’ to
ensure ‘that the [claim] is more than a drafting effort designed to
monopolize the [abstract idea].’” Id. (quoting Mayo, 566 U.S. at 77).
“[M]erely requir[ing] generic computer implementation[] fail[s] to transform
that abstract idea into a patent-eligible invention.” Id.
The PTO recently published revised guidance on the application of
§ 101. USPTO’s January 7, 2019 Memorandum, 2019 Revised Patent
Subject Matter Eligibility Guidance (“Memorandum”). Under that guidance,
we first look to whether the claim recites:
(1) any judicial exceptions, including certain groupings of abstract
ideas (i.e., mathematical concepts, certain methods of organizing
human interactions such as a fundamental economic practice, or
mental processes); and
(2) additional elements that integrate the judicial exception into a
practical application (see MPEP § 2106.05(a)–(c), (e)–(h)).
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Only if a claim (1) recites a judicial exception and (2) does not integrate that
exception into a practical application, do we then look to whether the claim:
(3) adds a specific limitation beyond the judicial exception that is not
“well-understood, routine, conventional” in the field (see MPEP
§ 2106.05(d)); or
(4) simply appends well-understood, routine, conventional activities
previously known to the industry, specified at a high level of
generality, to the judicial exception.
See Memorandum.
OPINION
The Judicial Exception Rejection of Claims 1–30
The Examiner determines claim 29 recites mathematical concepts.
Final Act. 5–7; see also Ans. 5–6 (citing October 2019 Update, Section II,
A, ii–iii) (“Other than applying the mathematical concepts in a processor, the
claimed invention entirely recites math.”).
The Examiner further determines
the following additional elements: computing device, processor,
computer readable medium, selecting a new observation vector
from an event stream or from an input dataset, and outputting an
indicator that the observation vector is an abnormal observation
vector . . . are recited at a high level of generality and in a manner
that merely generally links the recited abstract idea, the
mathematical concepts, to the additional elements, fails to
implement the abstract idea in conjunction with a particular
machine or manufacture, or at best results in an insignificant
extra solution activity.
Final Act. 7; see also Final Act. 7–8 (further discussing Step 2A, Prong
Two), Ans. 6–8 (“The claims recite a mathematical solution to a problem,
not a technological solution to a technical problem . . . the SVDD model
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continues to comprise mathematical concepts . . . the claims do in fact seek
to monopolize a mathematical approach to calculating outliers in data.”).
The Examiner further determines “the claim, considered individually
and as an ordered combination does not include additional elements that are
sufficient to amount to significantly more than the abstract idea.” Final
Act. 8; see also Final Act. 8–9 (further discussing Step 2B), Ans. 8–9 (citing
Spec. ¶¶ 40–51) (“[T]here is no inventive concept beyond the mathematics;
the claimed invention merely applies the mathematics in a computing
device.”).
Appellant presents the following principal arguments:
i. “None of the claim elements of Claims 1, 29, and 30 recite a
mathematical relationship, a numerical formula or equation, or a
mathematical calculation.” Appeal Br. 25–26; see also Reply Br. 2–4 (“An
indicator that the selected new observation vector is an abnormal
observation vector is not an indicator of math, but a determination using a
new and non-obvious process that may rely on math, but is not itself
math.”).
ii.
The computing operations included in Claims 1, 29, and 30 are
directly analogous to the “generating” step in example 38 and are
the only claim elements at all relatable to an abstract idea. Just as
in example 38 though, the computing operations included in
Claims 1, 29, and 30 may be based on mathematical concepts,
but the mathematical concepts are not recited in the claims.
Appeal Br. 27 (citing Subject Matter Eligibility Examples: Abstract Ideas,
issued Jan. 7, 2019, Example 38).
iii. “Similarly, even the computing operations included in Claims
1, 29, and 30 may be based on mathematical concepts, but the mathematical
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concepts are not recited in the claims. Appeal Br. 28 (citing Subject Matter
Eligibility Examples: Abstract Ideas, issued Jan. 7, 2019, Example 39).
iv. The claimed process improves the functioning of a computer.
See Appeal Br. 28–38. For example, Appellant argues
[t]hough the claimed process includes computations, the claimed
process is applied to detect an abnormal observation vector
using a process that achieves significant memory usage and
computer run time improvements relative to existing
computerized methods that compute a global optimal solution
that requires use of all of the data points.
Appeal Br. 29; see also Reply Br. 4–5 (citing McRO, Inc. v. Bandai Namco
Games Am. Inc., 837 F.3d 1299, 1306 (Fed. Cir. 2016)) (“The claims recite
the process by which the improvement is achieved . . . Directly analogous to
McRO, the present claims are directed to an automatic process that is new
and non-obvious and is applied to provide accurate abnormal observation
vector identification.”).
v. The claimed process effects a transformation to a different state.
See Appeal Br. 38–39. For example, Appellant argues “[t]he set of boundary
support vectors and the defined SVDD model are a transformation of the
plurality of observation vectors that are applied to indicate that the selected
new observation vector is an abnormal observation vector.” Appeal Br. 39;
see also Reply Br. 6 (“[T]here is no transformation of mathematical
relationships in the claims.”).
vi. The claimed process is not designed to monopolize math. See
Appeal Br. 39–40. For example, Appellant argues “it is the process not a
specific mathematical relationship or formula that achieves the
improvements.” Appeal Br. 39; see also Reply Br. 6 (“The many existing
methods for identifying outliers in data are not preempted.”).
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vii. The claims include an inventive concept. See Appeal Br. 40–45.
For example, Appellant argues “[n]o indication of support as required by the
Berkheimer Memo has been performed for any claim element. It cannot
reasonably be argued that all, or in fact any, of the claim elements are a
mathematical concept.” Appeal Br. 42. For example, Appellant argues “[t]he
present claims are directed to a new and non-obvious process that cannot be
directed to well-understood, routine or conventional activities.” Appeal
Br. 42. For example, Appellant argues
The claim limitations select the set of boundary support vectors
and make the determination that a new observation vector is
abnormal based on the selected set of boundary vectors in an
unconventional way that involves an inventive concept that is not
well-understood, routine, conventional activity in the field and
that results in improved computer functionality as discussed
above.
Appeal Br. 45.
We do not see any error in the Examiner’s determination that the
claims are directed to a judicial exception without significantly more.
Are the claims patent-eligible?
Step 1
Claim 1 recites a non-transitory computer-readable medium, which
falls within the “manufacture” category of 35 U.S.C. § 101. Claim 29 recites
a computing device, which falls within the “machine” category of 35 U.S.C.
§ 101. Claim 30 recites a method, which falls within the “process” category
of 35 U.S.C. § 101. Thus, we must determine whether the claims recite a
judicial exception and fail to integrate the exception into a practical
application. See Memorandum, 84 Fed. Reg. at 54–55. If both elements are
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satisfied, the claims are directed to a judicial exception under the first step of
the Alice/Mayo test. See id.
Step 2A, Prong One
Independent claim 29 recites the following steps:
[i] compute a Gaussian similarity matrix between a
plurality of observation vectors, wherein each
observation vector of the plurality of observation vectors
includes a variable value for each variable of a plurality
of variables;
[ii] compute an inverse Gaussian similarity matrix
from the computed Gaussian similarity matrix;
[iii] compute a row sum vector that includes a row
sum value computed from each row of the computed
inverse Gaussian similarity matrix;
[iv] select a set of boundary support vectors from
the plurality of observation vectors by removing any
interior vectors from the plurality of observation vectors,
wherein the set of boundary support vectors define a
boundary around the plurality of observation vectors,
wherein the computed inverse Gaussian similarity matrix
and the computed row sum vector are updated based on
the selected set of boundary support vectors to define a
trained support vector data description (SVDD) model;
(a) select a new observation vector from an event
stream or from an input dataset;
(b) compute an acceptance value for the selected
new observation vector using the selected set of
boundary support vectors, the computed row sum vector,
and the new observation vector;
(c) when the computed acceptance value is greater
than zero, compute an incremental vector from the
computed inverse Gaussian similarity matrix and the
selected new observation vector;
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(d) when the computed acceptance value is greater
than zero and when a maximum value of the computed
incremental vector is less than a first predefined tolerance
value, output an indicator that the selected new
observation vector is an abnormal observation vector
relative to the selected set of boundary support vectors;
and
(e) repeat (a) to (d) until the event stream is
stopped or a last observation vector is selected from the
input dataset in (a).
The overall process described by steps [i]–[iv] and (b)–(c) describes
“mathematical formulas or equations” or “mathematical calculations.”
Memorandum, 84 Fed. Reg. at 52. Thus, steps [i]–[iv] and (b)–(c) recite the
abstract concept of “[m]athematical concepts.” Id.
For example, in step [i], “comput[ing] a Gaussian similarity matrix” is
an act of calculating using mathematical methods. Similarly, in step [ii],
“comput[ing] an inverse Gaussian similarity matrix” is also an act of
calculating using mathematical methods. Similarly, in step [iii],
“comput[ing] a row sum vector” is also an act of calculating using
mathematical methods.
Further, in step [iv], “select[ing] a set of boundary support vectors” is
an act of calculating using mathematical methods. As well, “updat[ing]” the
computed inverse Gaussian similarity matrix and the computed row sum
vector “to define a trained support vector data description (SVDD) model” is
also an act of calculating using mathematical methods. Similarly, in step (b),
“comput[ing] an acceptance value for the selected new observation vector”
is also an act of calculating using mathematical methods. Similarly, in step
(c), “comput[ing] an incremental vector from the computed inverse Gaussian
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similarity matrix and the selected new observation vector” is also an act of
calculating using mathematical methods.
Thus, we determine claim 29 recites a judicial exception. For these
same reasons, we also determine claims 1 and 30 recite a judicial exception.
Step 2A, Prong Two
Because claims 1, 29, and 30 recite a judicial exception, we next
determine if the claims recite additional elements that integrate the judicial
exception into a practical application.
In addition to the limitations of claim 29 discussed above that recite
abstract concepts, claim 29 further recites “a processor” and “a non-
transitory computer-readable medium.” Claim 29 also further recites the
following steps: “(a) select a new observation vector from an event stream or
from an input dataset”;
(d) when the computed acceptance value is greater than zero and
when a maximum value of the computed incremental vector is
less than a first predefined tolerance value, output an indicator
that the selected new observation vector is an abnormal
observation vector relative to the selected set of boundary
support vectors
and “(e) repeat (a) to (d) until the event stream is stopped or a last
observation vector is selected from the input dataset in (a).”
The Specification does not provide additional details that would
distinguish the additional limitations from a generic implementation of the
abstract idea. For example, Appellant’s Specification discloses “[c]omputer-
readable medium 108 is an electronic holding place or storage for
information so the information can be accessed by processor 110 as
understood by those skilled in the art.” Spec. ¶ 40. Appellant’s Specification
further discloses “[p]rocessor 110 executes instructions as understood by
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those skilled in the art.” Spec. ¶ 41. Thus, the “processor” and the “non-
transitory computer-readable medium” do not integrate the judicial
exception into a practical application.
Further, the additional limitation reciting “(a) select a new observation
vector from an event stream or from an input dataset” does not add any
meaningful limitations to the abstract idea because this merely is directed to
the insignificant extra-solution activity of selecting a particular data source
or type of data to be manipulated. See MPEP § 2106.05(g); see also Elec.
Power, at 1353 (“Accordingly, we have treated collecting information,
including when limited to particular content (which does not change its
character as information), as within the realm of abstract ideas”).
Still further, the additional limitation reciting
(d) when the computed acceptance value is greater than zero and
when a maximum value of the computed incremental vector is
less than a first predefined tolerance value, output an indicator
that the selected new observation vector is an abnormal
observation vector relative to the selected set of boundary
support vectors
also does not add any meaningful limitations to the abstract idea because it
merely is directed to the insignificant post-solution activity of outputting
data. See MPEP § 2106.05(g).
Still further, the additional limitation reciting “(e) repeat (a) to (d)
until the event stream is stopped or a last observation vector is selected from
the input dataset in (a)” does not add any meaningful limitations to the
abstract idea because steps (b) and (c) are part of the abstract idea, and steps
(a) and (d) do not add any meaningful limitations to the abstract idea for
reasons explained above.
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Thus, we determine claim 29 is directed to a judicial exception
because claim 29 does not recite additional elements that integrate the
recited judicial exception into a practical application. For these same
reasons, we also determine claims 1 and 30 are directed to a judicial
exception.
Is there something else in the claims that ensures that they are
directed to significantly more than a patent ineligible concept?
Step 2B
Because claims 1, 29, and 30 are directed to a judicial exception, we
must determine, according to Alice, whether these claims recite an element,
or combination of elements that is enough to ensure that the claim is directed
to significantly more than a judicial exception.
Regarding the “processor” and the “non-transitory computer-readable
medium,” the conventional or generalized functional terms by which the
computer components are described reasonably indicate that Appellant’s
Specification discloses conventional components. See Spec. ¶¶ 40, 41. Thus,
these limitations simply append well-understood, routine, conventional
activities previously known to the industry, specified at a high level of
generality, to the judicial exception.
Further, regarding “(a) select a new observation vector from an event
stream or from an input dataset” and
(d) when the computed acceptance value is greater than zero and
when a maximum value of the computed incremental vector is
less than a first predefined tolerance value, output an indicator
that the selected new observation vector is an abnormal
observation vector relative to the selected set of boundary
support vectors,
our reviewing court has recognized that receiving, processing, and storing
data as well as receiving or transmitting data over a network are well-
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understood, routine, and conventional activities. Mortg. Grader, Inc. v. First
Choice Loan Servs. Inc., 811 F.3d 1314 (Fed. Cir. 2016) (generic computer
components, such as an “interface,” “network,” and “database,” fail to
satisfy the inventive concept requirement); TLI Commc’ns, 823 F.3d
607; Elec. Power, 830 F.3d at 1350. There is no indication that the recited
elements override the conventional use of known features or involve an
unconventional arrangement or combination of elements such that the
particular combination of generic technology results in anything beyond
well-understood, routine, and conventional data gathering and output. Alice,
573 U.S. at 223 (“[T]he mere recitation of a generic computer cannot
transform a patent-ineligible abstract idea into a patent-eligible
invention.”); Customedia Techs., LLC v. Dish Network Corp., 951 F.3d
1359, 1366 (Fed. Cir. 2020) (“[T]he invocation of ‘already-available
computers that are not themselves plausibly asserted to be an advance . . .
amounts to a recitation of what is well-understood, routine, and
conventional.’” (quoting SAP Am., Inc. v. InvestPic, LLC, 898 F.3d 1161,
1170 (Fed. Cir. 2018))); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355
(Fed. Cir. 2014) (“That a computer receives and sends the information over
a network—with no further specification—is not even arguably inventive.”).
Still further, the additional limitation reciting “(e) repeat (a) to (d)
until the event stream is stopped or a last observation vector is selected from
the input dataset in (a)” does not add any meaningful limitations to the
abstract idea because steps (b) and (c) are part of the abstract idea, and steps
(a) and (d) do not add any meaningful limitations to the abstract idea for
reasons explained above.
Thus, we determine claim 29 is not directed to significantly more than
a patent ineligible concept. For these same reasons, we also determine
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claims 1 and 30 are not directed to significantly more than a patent ineligible
concept.
Regarding Appellant’s argument (i), this argument does not show any
reversible error because we determine the overall process described by steps
[i]–[iv] and (b)–(c) recites the abstract concept of “[m]athematical
concepts.” Memorandum, 84 Fed. Reg. at 52. That is, we determine the
computing, selecting, and updating are all acts of calculating using
mathematical methods. Contrary to Appellant’s arguments, we determine
that these steps are math, rather than process steps based on math.
Regarding Appellant’s arguments (ii) and (iii), these arguments also
do not show any reversible error because, again, we determine that the
recited steps are math, rather than process steps based on math. In short, we
determine “comput[ing] a Gaussian similarity matrix,” “comput[ing] an
inverse Gaussian similarity matrix,” “comput[ing] a row sum vector,”
“select[ing] a set of boundary support vectors,” “updat[ing]” the computed
inverse Gaussian similarity matrix and the computed row sum vector “to
define a trained support vector data description (SVDD) model,”
“comput[ing] an acceptance value for the selected new observation vector,”
and “comput[ing] an incremental vector from the computed inverse
Gaussian similarity matrix and the selected new observation vector” are
math—not process steps based on math.
Regarding Appellant’s argument (iv), this argument also does not
show any reversible error because the overall process described by steps
[i]–[iv] and (b)–(c) is directed to the abstract concept of “[m]athematical
concepts.” Memorandum, 84 Fed. Reg. at 52. Further, the additional
limitation reciting “(a) select a new observation vector from an event stream
or from an input dataset” is directed to the insignificant extra-solution
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activity of selecting a particular data source or type of data to be
manipulated. Still further, the additional limitation reciting
(d) when the computed acceptance value is greater than zero and
when a maximum value of the computed incremental vector is
less than a first predefined tolerance value, output an indicator
that the selected new observation vector is an abnormal
observation vector relative to the selected set of boundary
support vectors
is directed to the insignificant post-solution activity of outputting data. We
do not see any particular improvements to technology. Therefore, on the
record before us, the claim limitations do not improve the functionality of
the various hardware components, nor do they achieve an improved
technological result in conventional industry practice. McRO, Inc. v. Bandai
Namco Games Am. Inc., 837 F.3d 1299, 1316 (Fed. Cir. 2016). Further, to
the extent the claim achieves significant memory usage and computer run
time improvements, these improvements follow from a generic
implementation of the abstract idea—the claims do not recite any more than
merely outputting data that results from the mathematical calculations.
Regarding Appellant’s arguments (v) and (vi), these arguments also
do not show any reversible error because we do not agree that the SVDD
model is a transformation of the observation vectors. Rather, we determine
the computing, selecting, and updating steps are math—not process steps
based on math. Further, we determine that further computations for the new
observation vector are also math. Beyond the mathematical steps, the
remaining steps in the claim are insignificant extra-solution activity, and do
not add any meaningful limitations to the abstract idea. The fact that other
methods for identifying outliers are not preempted does not make the claims
any less abstract.
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Regarding Appellant’s argument (vii), this argument also does not
show any reversible error for reasons explained above where we applied the
Memorandum.
We, therefore, sustain the Examiner’s rejection of claims 1, 29,
and 30.
Appellant presents arguments for some of the dependent claims. See
Appeal Br. 45–55. The arguments, in essence, are variations of the
arguments presented for the independent claims, and do not show any
reversible error for the same reasons explained above where we applied the
Memorandum. Thus, we also determine claims 2–28 are not directed to
significantly more than a patent ineligible concept. We add the following for
emphasis.
Claims 8, 10, 20, and 27 do not add any meaningful limitations to the
abstract idea because they merely are directed to the insignificant post-
solution and well-understood, routine, and conventional activity of
outputting data.
Claims 15–17, 19, and 23 do not add any meaningful limitations to the
abstract idea because the additional steps recited in these claims are math,
and any improvements follow from a generic implementation of the abstract
idea using well-understood, routine, and conventional computer
components.
Claims 24–26 do not add any meaningful limitations to the abstract
idea because they merely are directed to the insignificant extra-solution
activity of selecting a particular data source or type of data to be
manipulated, and to the well-understood, routine, and conventional activity
of data gathering.
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Claim 28 does not add any meaningful limitations to the abstract idea
because it merely is directed to the insignificant extra-solution activity of
selecting a particular data source or type of data to be manipulated, to the
well-understood, routine, and conventional activity of data gathering, and to
the insignificant post-solution and well-understood, routine, and
conventional activity of outputting data
We, therefore, also sustain the Examiner’s rejection of claims 2–28.
CONCLUSION
The Examiner’s decision to reject claims 1–30 is affirmed.
DECISION SUMMARY
In summary:
Claims
Rejected
35 U.S.C.
§
Reference(s)/Basis Affirmed Reversed
1–30 101 Eligibility 1–30

TIME PERIOD FOR RESPONSE
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)(1)(iv).
AFFIRMED