ORACLE INTERNATIONAL CORPORATION

Patent Trials and Appeals Board

May 4, 2020

14248225 - (D) (P.T.A.B. May. 4, 2020)

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.
14/248,225 04/08/2014 John David HOLDER ORA130844-US-NP 5809
55498 7590 05/04/2020
Vista IP Law Group, LLP (Oracle)
2160 Lundy Avenue
Suite 230
San Jose, CA 95131
EXAMINER
BEHNCKE, CHRISTINE M
ART UNIT PAPER NUMBER
3624
NOTIFICATION DATE DELIVERY MODE
05/04/2020 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):
docketing@viplawgroup.com
ev@viplawgroup.com
PTOL-90A (Rev. 04/07)

UNITED STATES PATENT AND TRADEMARK OFFICE
____________

BEFORE THE PATENT TRIAL AND APPEAL BOARD
____________

Ex parte JOHN DAVID HOLDER and
AARON JOHNSON

Appeal 2019-006218
Application 14/248,225
Technology Center 3600
____________

Before ERIC B. GRIMES, RICHARD M. LEBOVITZ, and
FRANCISCO C. PRATS, Administrative Patent Judges.

LEBOVITZ, Administrative Patent Judge.

DECISION ON APPEAL
The Examiner rejected the claims under 35 U.S.C. § 103(a) as
obvious, under 35 U.S.C. § 101 as reciting patent ineligible subject matter,
and under 35 U.S.C. § 112 as indefinite. Pursuant to 35 U.S.C. § 134(a),
Appellant1 appeals from the Examiner’s decision to reject the claims. 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. Appellant identifies the real party in interest as Oracle
International Corporation. Appeal Br. 3.
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STATEMENT OF THE CASE
The Examiner finally rejected the claims as follows:
1. Claims 1–8, 10–17, and 19–26 under 35 U.S.C. § 103(a) as
obvious in view of Banerjee et al. (US 2010/0250338 A1, published Sept.
30, 2010)(“Banerjee”), “New and Notable Features within BIRT 4.2,”
https://www.eclipse.org/birtlphoenix/project/notable4.2.php (“Archived
back at least as far as July 2012”) (“BIRT”), and Berger et al. (US
2005/0177553 A1, published Aug. 11, 2005) (“Berger”). Final Act. 6.
2. Claims 2–5, 8, 11–14, 17, 20–23, and 26 under 35 U.S.C. § 103(a)
as obvious in view of Banerjee, BIRT, Berger, and Hassine et al. (US
2009/0234710 A1, published Sept. 17, 2009 (“Hassine”). Final Act. 12–13
3. Claim 1–27 under 35 U.S.C. § 101 because the claimed invention is
directed to a judicial exception. Final Act. 4.
4. Claims 1–27 under 35 U.S.C. § 112(b) as indefinite for failing to
particularly point out and distinctly claim the subject matter which the
inventor or a joint inventor regards as the invention. Final Act. 3.
Claim 1 is illustrative and reproduced below. The claim is annotated
with bracket numbering and lettering to reference the limitations in the
claim.
1. A computer implemented method implemented with a
processor, compnsmg:
[1] maintaining a database comprising historical data and
real-time data, the real-time data comprising items processed
and items to be processed;
[2] configuring a plurality of tables, the plurality of tables
each comprising:
[2a] a set of columns comprising an item name
column and an item count column, and
[2b] a set of rows wherein each row corresponds to
a particular item and a particular item count corresponding to a
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number of times within a particular month the particular item
has been processed,
[3] wherein each table of the plurality of tables
corresponds to a month,
[4] wherein item counts for items are pre-calculated from
the historical data and stored in respective tables corresponding
to respective months,
[5] wherein the plurality of tables is updated with the
real-time data corresponding to the particular month associated
with the real-time data on an ongoing basis;
[6] generating item frequency data comprising the item
counts for the items processed by performing pre-calculations
on the historical data, the pre-calculations comprising:
[6a] retrieving the historical data corresponding to
an analysis time period, identifying one or more items
associated with the historical data,
[6b] specifying a plurality of time periods within
the analysis time period, the plurality of time periods
corresponding to a plurality of months associated to the
plurality of tables,
[6c] calculating the item counts for the one or
more items for each of the plurality of months using the
historical data retrieved, and
[6d] storing the item frequency data comprising
the calculated item counts associated with the plurality of
months into the respective tables of the plurality of tables
corresponding to the respective months;
[7] processing real-time data;
[8] in response to processing the real-time data
comprising the items to be processed, updating the calculated
item frequency data stored in the respective tables of the
plurality of tables corresponding to a specific month associated
with the real-time data, wherein updating is performed in real
time as the real-time data is processed, and comprises:
[8a] identifying an item associated with the real-
time data,
[8b] determining the specific month associated
with the item, the specific month corresponding to a specific
table of the plurality of tables, and
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[8c] updating the calculated item frequency data
stored in the specific table by incrementing or decrementing the
item count column of a row corresponding to the item
associated with the real-time data being processed; and
[9] displaying, in a user interface, a ranking of the item
frequency data in real-time for a given month by:
[9a] retrieving item frequency data from a
particular table from the plurality of tables corresponding to the
given month, and
[9b] generating the ranking of the item frequency
data by sorting values of the item count column of the item
frequency data retrieved from the particular table.

OBVIOUSNESS REJECTIONS
The Examiner found that Banerjee describes maintaining a database
comprising historical and real-time data and comprising items processed and
items to be processed as in step [1] of claim 1. Final Act. 6. With respect to
the organization of the rows and columns in the table of step [2], the
Examiner cited BIRT and stated it would have been obvious to one of
ordinary skill in the art to have incorporated BIRT’s arrangement of data in
Banerjee as a known organization of data. Id. at 7, 10–11. For the limitation
of using monthly tables as in step [3], the Examiner cited Berger. Id. The
Examiner further found that Banerjee describes steps [5]–[8] of claim 1. Id.
at 8–10. The Examiner stated that Banerjee does not use the term “ranking”
recited in step [9], but found that Banerjee describes data regarding product
quantities and reasoned that it would have been obvious to one of ordinary
skill to “rank” the quantities to improve the process. Id. at 10. The Examiner
further cited Banerjee’s disclosure of higher and lower frequency
transactions as evidence of the obviousness of ranking quantities against
each other. Ans. 18.
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Appellant contends that BIRT does not disclose “configuring multiple
tables, especially how the multiple tables are interrelated as required by the
current claim limitations.” Appeal Br. 32. Appellant repeats substantially
the same argument on pages 33 and 35 of the Appeal Brief. Appellant also
argues that “Berger was not relied upon by the Office Action to disclose this
claim limitation,” and therefore “does not cure the deficiencies of Banerjee
and BIRT.” Id. at 35.
This argument is not persuasive. The Examiner cited Berger for its
description of a plurality of tables in which item counts are pre-calculated
from historical data and stored in tables corresponding to respective months.
Final Act. 7.
Paragraph 27 of Berger, cited by the Examiner, discloses:
A client or user can employ client system 120 to specify a
distinct count query of data stored in data store 110. For
instance, a user could specify sales queries such as “What are
the number of distinct customers that purchased a particular
product during a specific time period?” or more generally
“How many customers are buying each of my products?” or
“How many distinct products were purchased in the fourth
quarter?”
Paragraph 41 of Berger, also cited by the Examiner, discloses
(emphasis added):
FIG. 7 is a flow chart diagram illustrating a method 700 of pre-
aggregating data. At 710 data is partitioned. Database size has
been increasing steadily over the years since its acceptance. . . .
Partitions, inter alia, allow large amounts of data to be scanned
and manipulated by allowing data to be distributed amongst a
plurality of servers or processors. . . . A database can be
separated into partitions by a database administrator who is
familiar with the data set and the most popular queries. . . .
[H]euristic tools can be utilized to assist a database
administrator or to automatically and intelligently partition
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data. For example, if a database houses a business’ sales results
since the opening of the business data can be partitioned by
year (e.g., 1999, 2000, 2001 . . .), by fiscal year, by month or
any other unit of time that is often a topic of inquiry. (emphasis
added)
It is clear from each of these disclosures that Berger discloses dividing
data into multiple partitions (¶ 41: “data is partitioned. . . . Partitions, inter
alia, allow large amounts of data to be scanned and manipulated by allowing
data to be distributed amongst a plurality of servers or processors”) and
partitioning the tables into months (¶ 41: “a database houses a business’
sales results since the opening of the business data can be partitioned . . . by
month”). While Berger does not expressly teach that the partitions are
“tables” as asserted by Appellant (Reply Br. 18), it would have been obvious
to use tables as the partitions because BIRT describes the advantages of
tables and Banerjee discloses storing its data in tables (Banerjee ¶¶ 9, 17,
56). Thus, Appellant’s statement that Berger does not cure the deficiencies
of Banerjee and BIRT is not supported by the evidence in this record.
Berger also teaches pre-calculating data and its benefits, as recited in
steps [4] and [6] of claim 1. Paragraph 27 of Berger, cited by the Examiner,
discloses (emphasis added):
Data store 110 is a database capable of storing large amounts of
information. According to an aspect of the subject invention,
the data store 110 is an OLAP [online analytical processing
database] with ordered partitioned data stored therein.
Accordingly, data store 110 stores pre-aggregated or pre-
calculated data with respect to distinct count queries.
Aggregation of data prior to receiving a query is an important
factor in reducing overall query response time. Data
aggregation can be implemented by a database administrator,
determined heuristically and intelligently by an aggregation
system, or a hybrid utilizing a wizard, for instance, to guide a
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database administrator through a series of steps for optimizing
data aggregation and thus query response time. Data
aggregation or pre-calculation can include dividing or
separating data into optimal partitions and ordering the
partitioned data.
Appellant argues that the cited publications do not disclose “ranking”
as required by step [9] of claim 1. Appeal Br. 35–36. Appellant disputes the
Examiner’s finding that Banerjee suggests ranking item frequency data.
Reply Br. 19.
This argument does not persuade us that the Examiner erred.
The Examiner cited paragraph 56 of Banerjee. Banerjee discloses that
“if a user requests sales frequency information for Merchant B’s Product A,
the financial institution 130 can provide the requested recurrence using, for
example, a graphical user interface (GUI).” Banerjee ¶ 56. Thus, Banerjee
expressly discloses providing sales frequency information which is the same
as “item frequency data” as in step [9] of claim 1.
The Examiner further cited paragraph 66 of Banerjee to meet
limitation [9] of clam 1. Banerjee discloses:
For example, with the transaction recurrence engine’s output as
shown in FIG. 3B, the financial institution 130 may, for
example, improve its pricing offerings since the transaction
recurrence engine 132 may both identify merchants which are
popular and also which particular type of transaction is popular
for a certain merchant.
We interpret a “popular” transaction to be one in which a specific item
is frequently purchased. In order to identify “popular” transactions, the
transactions must be analyzed to determine which are most frequent. This
could be accomplished by ranking the transactions and identifying which are
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most frequent and therefore “popular.” Thus, Banerjee either discloses
ranking “item frequency data” as recited in step [9] or reasonably suggests it.
Appellant acknowledges that Banerjee discloses determining “higher
and lower frequency” transactions, but argues that Banerjee does not
describe “sorting” as required by claim 1. Reply Br. 19. We do not agree
because one way for Banerjee to determine popular transactions, including
transactions of a high or low frequency, would be to sort them, thereby
ranking them. “A person of ordinary skill is also a person of ordinary
creativity, not an automaton.” KSR Int’l Co. v. Teleflex Inc., 550 U.S. 398,
421 (2007). Thus, one of ordinary skill in the art, as discussed by the
Examiner, would have found it obvious to sort item frequency data as a way
of determining the popularity of items as described by Banerjee.
For the foregoing reasons, the rejection of claim 1 as obvious in view
of Banerjee, BIRT, and Berger is affirmed. For the same reason, we also
affirm the rejection based on Banerjee, BIRT, Berger, and Hassine.
Appellant does not provide separate arguments for claims 2–8, 10–17, 19–
26. Appeal Br. 36–37. These claims therefore fall with claim 1. 37 C.F.R. §
41.37(c)(1)(iv) (2018).

SECTION 101 REJECTION
Principles of Law
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.”
However, not every discovery is eligible for patent protection. Diamond v.
Diehr, 450 U.S. 175, 185 (1981). “Excluded from such patent protection are
laws of nature, natural phenomena, and abstract ideas.” Id. The Supreme
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Court articulated a two-step analysis to determine whether a claim falls
within an excluded category of invention. Alice Corp. Pty. Ltd. v. CLS Bank
Int’l, 573 U.S. 208, 216 (2014); Mayo Collaborative Servs. v. Prometheus
Labs, Inc., 566 U.S. 66, 75–77 (2012).
In the first step, it is determined “whether the claims at issue recite
“one of those patent-ineligible concepts.” Alice, 573 U.S. at 217. If it is
determined that the claims recite an ineligible concept, then the second step
of the two-part analysis is applied in which it is asked “[w]hat else is there in
the claims before us?” Id. The Court explained that this step involves:
a search for an ‘inventive concept’ — i.e., an element or
combination of elements that is ‘sufficient to ensure that the
patent in practice amounts to significantly more than a patent
upon the [ineligible concept] itself.’
Alice, 573 U.S. at 217–18 (citing from Mayo, 566 U.S. at 75–77).
Alice, relying on the analysis in Mayo, stated that in the second part of
the analysis, “the elements of each claim both individually and ‘as an
ordered combination’” must be considered “to determine whether the
additional elements ‘transform the nature of the claim’ into a patent-eligible
application.” Alice, 573 U.S. at 217.
The PTO published guidance on the application of 35 U.S.C. § 101.
USPTO’s January 7, 2019 Memorandum, 2019 Revised Patent Subject
Matter Eligibility Guidance, 84 Fed. Reg. 50, 51–57 (2019) (“Eligibility
Guidance”). This guidance provides additional direction on how to
implement the two-part analysis of Mayo and Alice.
Step 2A, Prong One, of the 2019 Eligibility Guidance, looks at the
specific limitations in the claim to determine whether the claim recites a
judicial exception to patent eligibility. In Step 2A, Prong Two, the claims are
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examined to identify whether there are additional elements in the claims that
integrate the exception in a practical application, namely, is there a
“meaningful limit on the judicial exception, such that the claim is more than
a drafting effort designed to monopolize the judicial exception.” 84 Fed.
Reg. 54 (2. Prong Two).
If the claim recites a judicial exception that is not integrated into a
practical application, then, as in the Mayo/Alice framework, Step 2B of the
Eligibility Guidance instructs us to determine whether there is a claimed
inventive concept to ensure that the claims define an invention that is
significantly more than the ineligible concept, itself. 84 Fed. Reg. 56. In
making this determination, we must consider whether there are specific
limitations or elements recited in the claim “that are not well-understood,
routine, conventional activity in the field, which is indicative that an
inventive concept may be present” or whether the claim “simply appends
well-understood, routine, conventional activities previously known to the
industry, specified at a high level of generality, to the judicial exception,
indicative that an inventive concept may not be present.” 84 Fed. Reg. 56
(footnote omitted).
With these guiding principles in mind, we proceed to determine
whether the claimed subject matter in this appeal is eligible for patent
protection under 35 U.S.C. § 101.

Discussion
Claim 1 is directed to a “computer implemented method implemented
with a processor.” Following the first step of the Mayo/Alice analysis, we
find that the claim is directed a “process,” and therefore falls into one of the
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broad statutory categories of patent-eligible subject matter under 35 U.S.C.
§ 101. We thus proceed to Step 2A, Prong One, of the Eligibility Guidance.

Step 2A, Prong One
In Step 2A, Prong One, of the Eligibility Guidance, the specific
limitations in the claim are examined to determine whether the claim recites
a judicial exception to patent eligibility, namely whether the claim recites an
abstract idea, law of nature, or natural phenomenon.
We begin with the elements recited in the claim. Claim 1 refers to [1]
“items processed” and “items to be processed.” The claim further refers to
calculating [4] “item counts” and [6] “generating item frequency data.” The
item counts are tracked by month (steps [4], [5]). Based on the Specification,
we understand item processing to refer to processing of sales orders for the
item. Spec. ¶ 8 (“These counts are updated when ongoing sales orders are
processed”), ¶ 18 (“These counts are updated when ongoing sales orders are
processed. This approach allows the counts for the months that are currently
relevant to be summed quickly and ranked at runtime so the items with the
highest frequency can be recommended.”). The claim therefore keeps track
of items which are ordered (i.e., sales) and ranks them by the number of
orders for each item (step [9]).
The Examiner found that the claims recite an abstract idea comprising
employing mathematical algorithms on sales data. Final Act. 4. The
Examiner after reviewing the 2019 Eligibility Guidance also found that the
claims recite a fundamental economic practice. Ans. 5–6.
Appellant argues that the recited steps in the claim go “far beyond any
mathematical concepts or any mathematical relationships that may be found
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to be implicit within the claim.” Appeal Br. 22. Appellant argues that the
claims are an improvement to how a computer operates and significantly
more than an abstract idea, itself. Appeal Br. 20. However, Appellant did not
rebut the Examiner’s findings that the claim recites an abstract idea.
We are not persuaded by Appellant’s arguments. Specifically, step [6]
expressly recites that pre-calculations are performed comprising [6c]
“calculating the item counts for the one or more items for each of the
plurality of months using the historical data retrieved.” Step [8] also
performs calculations, comprising [8c] “updating the calculated item
frequency data stored in the specific table by incrementing or decrementing
the item count column of a row corresponding to the item associated with
the real-time data being processed.” The 2019 Guidelines identify
“mathematical calculations” as a “Mathematical concept,” one of the three
groupings of abstract ideas. 84 Fed. Reg. 52. Appellant’s only argument is
that the claim goes far beyond a mathematical concept or relationship.
Appeal Br. 21. However, Appellant does not identify a defect in the
Examiner’s finding that the claim recites the abstract idea of a mathematical
concept.
The Examiner also found that the claim recites a fundamental
economic practice. Ans. 5–6. A fundamental economic practice is listed in
the Eligibility Guidance as an abstract idea. 84 Fed. Reg. 52. We agree with
the Examiner that performing calculations on sales data is a fundamental
economic process. Final Act. 4. The Specification acknowledges that many
businesses employ business applications to manage aspects of their business,
including online transaction processing, finance, and accounting. Spec. ¶ 3.
As explained in Alice, a fundamental economic practice is one that is “‘long
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prevalent in our system of commerce’” and therefore outside the scope of §
101. Alice, 134 S.Ct. at 2356. It appears from the Specification, and
Appellant’s own acknowledgements (Appeal Br. 18), that the practice of
keeping track of items that are ordered by customers is a practice that is
prevalent in commerce, and therefore is a fundamental economic practice.
In sum, we find that the Examiner’s findings that claim 1 recites an
abstract idea is supported by a preponderance of the evidence. Accordingly,
we proceed to Step 2A, Prong Two, of the Eligibility Guidance.

Step 2, Prong Two
Prong Two of Step 2A under the 2019 Eligibility Guidance asks
whether there are additional elements that integrate the exception into a
practical application. As in the Mayo/Alice framework, we must look at the
claim elements individually and “as an ordered combination” to determine
whether the additional elements integrate the recited abstract idea into a
practical application. The Eligibility Guidance explains that “[a] claim that
integrates a judicial exception in a practical application will apply, rely on,
or use the judicial exception in a manner that places a meaningful limit on
the judicial exception, such that the claim is more than a drafting effort
designed to monopolize the judicial exception.” Eligibility Guidance, 84
Fed. Reg. 54. Integration into a practical application is evaluated by
identifying whether there are additional elements individually, and in
combination, which go beyond the judicial exception. Eligibility Guidance,
84 Fed. Reg. 54–55. Specifically, the Guidance describe several
considerations in determining whether the abstract idea is integrated into a
practical application:
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An additional element reflects an improvement in the
functioning of a computer, or an improvement to other
technology or technical field
84 Fed. Reg. 55.
Appellant also argues that the claim is “an improvement to the way
the computer operates through the recitation of interrelated data structures to
improve the way a computer stores and retrieves data.” Id. at 20 (emphasis
omitted). Specifically, Appellant asserts that the claim “explicitly recites a
very particular structure of database tables and interrelationships between
the tables, columns and rows to improve the functioning of the computer
itself.” Id. at 21. Appellant explains that “the configuration of the particular
database structures that are interrelated in the particular way that improves
the functioning of the computer itself when displaying a ranking of the item
frequency data” because “the ranking of the item frequency data may be
achieved simply by sorting values of the item count column of the item
frequency data retrieved from a particular table.” Id. at 22. Appellant asserts
that any abstract idea is integrated into a practical application. Id. at 24.
Appellant states:
For example, item frequency data are generated from historical
data and stored into a plurality of data structures (e.g., tables) so
that counts of items processed can be stored in the plurality of
tables interrelated in a particular way. In response to processing
the real-time data, the counts of items corresponding to the
items being processed are updated in respective tables
corresponding to the respective months to keep the item
frequency data stored within the plurality of tables accurate and
up-to-date. The item frequency data for a given month can be
quickly displayed in real-time merely by a ranking of the item
frequency data of a particular table corresponding to the given
month by sorting values of the item count column of the
particular table. Appellant respectfully submits that it is the
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interrelated data structures that improve the way the computer
stores and retrieves the item frequency data.
Id.
We have considered these arguments, but do not find they
demonstrate error in the Examiner’s rejection.
The claimed table has columns with item name and count, and rows
with item count and number of times the item has been processed (step [2]).
Appellant has not provided evidence that this configuration of rows and
columns improves how the computer operates. Appellant cites Enfish, LLC
v. Microsoft Corp., 822 F.3d 1327 (Fed. Cir. 2016) (Appeal Br. 24).
However, Enfish is distinguishable from the rejected claims.
In Enfish, the claims were directed to a data storage and retrieval
system for a computer memory. Enfish, 822 F.3d at 1336. The system
comprised a system for configuring the memory according to logical table,
where the logical table included:
a plurality of logical rows, each said logical row including an
object identification number (OID) to identify each said logical
row, each said logical row corresponding to a record of
information;
a plurality of logical columns intersecting said plurality of
logical rows to define a plurality of logical cells, each said
logical column including an OID to identify each said logical
column; and
means for indexing data stored in said table.
Id.
The court found that the claimed “self-referential table functions
differently than conventional database structures.” Enfish, 822 F.3d at 1337.
The court found the claims were not simply directed to the concept of
organizing information, but instead “are directed to an improvement in the
functioning of a computer.” Id. at 1338. Specifically, the court found that
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“self-referential table recited in the claims on appeal is a specific type of
data structure designed to improve the way a computer stores and retrieves
data in memory.” Id. at 1339.
Appellant has not explained how the specific configuration of rows
and columns in which items counts are listed is not simply a generic
database structure which organizes information. The recited table in step [2]
of claim 1 lists items and item counts for each month. It thus appears that the
table organizes the information in a commonsense way to show the item and
the number of times it has been ordered. Appellant did not explain, and we
do not see, how this organization improves the way the computer operates as
it did in Enfish or improves how the information is organized.
Appellant also refers to the allegedly claimed “interrelated data
structures” as an improvement to computer function. Appeal Br. 20–21.
Appellant did not persuasively establish that the claim require an interrelated
data structure. The plurality of tables recited in the claim are tables that
correspond to each month (steps [2b], [3]). The claim does not require that
these tables are “interrelated.” We have not been guided to a limitation in the
claim that requires the tables to interact or interrelate in such a way that the
operation of the computer is improved. The claim refers to filling in
historical data for each month (step [4]) and updating this data month by
month (step [8]), but Appellant did not identify a limitation the claim that
requires the different months to interrelate.
Appellant also argues that the data structure improves how the ranking
is accomplished. Appeal Br. 22, 24 (see argument summarized above).
Appellant’s argument, however, is just a restatement of the steps of the
claim.
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Appellant states that the improvement is because “the ranking of the
item frequency data may be achieved simply by sorting values of the item
count column of the item frequency data retrieved from a particular table.”
Id. at 22. But how else is ranking achieved but by sorting values in a column
from highest or lowest value? The claim does not recite how the sorting is
specifically achieved. Thus, we do not see how this step constitutes an
improvement to a technology or a technical field.
To accomplish the ranking, Appellant refers to the steps in the claim
which perform mathematical calculations (pre-calculations of step [6] and
updating the item frequency data of step [8]). Appeal Br. 22. These steps, as
explained above, are abstract ideas and therefore cannot serve as additional
elements of the claim. The “additional element” relied upon as the basis for
eligibility must be “claim features, limitations, and/or steps that are recited
in the claim beyond the identified judicial exception.” Eligibility Guidance,
84 Fed. Reg. 55 (fn. 24). As held in Parker v. Flook, 437 U.S. 584, 594–95,
“[t]he process itself, not merely the mathematical algorithm, must be new
and useful.” Id. at 591.
We recognize that the pre-calculation and the updating steps ([6] and
[8]) are used when ranking the items in step [9]. However, the improvement,
if any, is to the mathematical concept in which the calculations are
accomplished and then the items are ranked. The “ranking” itself, is either a
mathematical concept because it is ordering values or something that can be
performed mentally, which is also an abstract idea (Eligibility Guidance, 84
Fed. Reg. 52). Furthermore, while performing pre-calculations may enhance
the speed of the process, it does not change how the ranking is done.
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Appellant further argues that “particular structures of tables recited in
the claim is above and beyond the simple concept of tables, rows and
columns.” Appeal Br. 25. This argument is not persuasive. As explained by
the Examiner and illustrated in Figure 5C, the arrangement, indeed, appears
to reflect a simple concept of a table with rows and columns. Figure 5C is
reproduced below:

Fig. 5C shows “buckets” or tables for January and February, with a
list of the item, the number of each item, and their ranking. The
Specification states, with respect to Fig. 5C, that the “February bucket 504
may sort its item counts as it is updated in real time.” Spec. ¶ 53. The
Specification explains that “the update following order information 504
caused the count for hats to exceed the count for jackets, in which case the
sorting of the counts within February bucket 504 may be updated to reflect
this.” Id. The figure shows columns and rows, Appellant did not explain how
this basis arrangement is “beyond the simple concept of tables, rows and
columns” (Appeal Br. 25) when the figure shows a simple column of items
and the number of each item ordered.
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Appellant contends that “it is the very specific arrangement of the
tables combined together in a particular way that achieves the performance
advantages to the functioning of the computer itself, as acknowledged by the
Office Action at page 18.” Appeal Br. 25. Appellant also contends that the
claims solve the technical problem when there a lot of ongoing transactions
comprising “populating live data into tables in a database that already have a
large volume of data (e.g., historical data) stored within the tables.” Appeal
Br. 25–26. Appellant asserts to have solved this problem by “pre-calculating
historical data and continuously updating the pre-calculated data with real-
time data to provide the certain type of information used at runtime.” Id. at
26. Appellant states that “retrieving the certain type of information from the
smaller sized tables having the partitioned content, already pre-calculated, is
much more efficient, thus resulting in a faster processing time for the
computer and less memory since the information is retrieved from a smaller
sized table and already pre-calculated.” Id.
The Examiner explained on page 18 of the Final Action that the
Examiner “does not necessarily disagree conceptually that performing first
calculations on data in a first session in advance of performing second
calculations in a second session results in fewer calculations being
performed in each session when compared to performing both the first and
second calculations in the same session.” Final Act. 18. However, the
Examiner found that this “improvement” is to the abstract idea and not to
how the tables, themselves, are configured. Id. at 18–19.
The Examiner found that the claims are similar to those in BSG Tech
LLC v. Buyseasons, Inc., 899 F.3d 1281 (Fed Cir. 2018), which were found
to be patent ineligible. Final Act. 19. We agree. In BSG, 899 F.3d at 1286,
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the court stated that “the asserted claims are directed to the abstract idea of
considering historical usage information while inputting data.” The court
specifically recognized that the historical use of information, similar to
performing pre-calculations on historical data in steps [4] and [6] of claim 1,
allowed “‘users to quickly and efficiently access hundreds of thousands or
even millions of records, and still find only those few records that are
relevant.’” Id. at 1288. However, as discussed by the Examiner, the court
found that these “benefits” asserted by BSG, “are not improvements to
database functionality. Instead, they are benefits that flow from performing
an abstract idea in conjunction with a well-known database structure.” Id. at
1288. The Examiner clearly articulated the deficiency in Appellant’s
argument:
Throughout the Appeal Brief, Appellant rests his
conclusion that the claims recite an improvement to computing
systems heavily on the notion that the sheer volume of data that
the computer system must process gives rise to a problem
solved by the claim. Appeal Br. 9, 20, 28. However, Appellant's
arguments are not commensurate with the scope of the claims.
The broadest reasonable interpretation of claim 1, for example,
requires two tables, each table including a row describing a
single item and a count corresponding to that item in a
respective month.
Ans. 8.
Appellant cites DDR Holdings, LLC v. Hotels.com, L.P., 773 F.3d
1245 (Fed. Cir. 2014) to support the contention that the claims are patent
eligible. Appeal Br. 27–28. We have considered this argument, but conclude
that it does not persuasively demonstrate an error in the rejection. In DDR,
the claims were directed to an “e-commerce outsourcing system “to serve a
composite web page to the visitor computer wit[h] a look and feel based on
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the look and feel description in the data store and with content based on the
commerce object associated with the link.” DDR, 773 F.3d at 1249. The
court found the claims to be patent eligible because “the claimed solution is
necessarily rooted in computer technology in order to overcome a problem
specifically arising in the realm of computer networks.” Id. at 1257. As the
court explained, “the claims at issue here specify how interactions with the
Internet are manipulated to yield a desired result—a result that overrides the
routine and conventional sequence of events ordinarily triggered by the click
of a hyperlink.” Id. at 1258.
Appellant did not establish that the rejected claims are “necessarily
rooted in computer technology” as they were in DDR. The steps in the claim
are performed on a computer system, but Appellant has not explained how
the steps address a problem that improves the computer system which carries
out the method. The additional element cited by Appellant appears to be a
pre-calculated table that is updated to improve the speed of ranking. Appeal
Br. 27. Appellant also states the problem is solved by creating separate
tables corresponding to specific months. Id. at 28. We agree with the
Examiner that Appellant did not establish that these tables do anything more
than store data in a commonsense way, and unlike in DDR, do not provide a
technical solution deeply rooted in computer technology, but rather improve
calculating item frequency and ranking, which are abstract concepts.
The steps referred to by Appellant, even if additional elements beyond
the judicial exception, are insufficient to confer eligibility because they are
not recited with sufficient specificity to avoid preemption. As explained in
McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 1314 (Fed.
Cir. 2016), the “abstract idea exception has been applied to prevent patenting
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of claims that abstractly cover results where ‘it matters not by what process
or machinery the result is accomplished.’ [O’Reilly v. Morse, 56 U.S. 62,
113, (1853)]; see also Mayo, 132 S.Ct. at 1301.” McRO stated that therefore,
a court must “look to whether the claims in these patents focus on a specific
means or method that improves the relevant technology or are instead
directed to a result or effect that itself is the abstract idea and merely invoke
generic processes and machinery.” McRO, 837 F.3d at 1314. In this case,
while steps [6] and [8] recite steps to accomplish the result, the individual
steps are not required by the claim to be executed in a specific manner. For
example, the claim recites that the item counts are calculated and stored
(step [6c] and [6d]), but the claim does recite with any specificity how the
calculation is performed and the result stored. Step [8] recites that the
frequency is adjusted by incrementing and decrementing item counts, but
this step is just simple arithmetic and embodies a mathematical concept.
In sum, we conclude that the recited abstract idea of recited in the
claims is not integrated into a practical application.

Step 2B
Because we determined that the judicial exception is not integrated
into a practical application, we proceed to Step 2B of the Eligibility
Guidance, which asks, as in the Mayo/Alice framework, whether there is an
inventive concept. In making this Step 2B determination, we must consider
whether there are specific limitations or elements recited in the claim “that
are not well-understood, routine, conventional activity in the field, which is
indicative that an inventive concept may be present” or whether the claim
“simply appends well-understood, routine, conventional activities previously
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known to the industry, specified at a high level of generality, to the judicial
exception, indicative that an inventive concept may not be present.”
Eligibility Guidance, 84 Fed. Reg. 56 (footnote omitted). We must also
consider whether the combination of steps in the claim perform “in an
unconventional way and therefore include an ‘inventive step,’ rendering the
claim eligible at Step 2B.” Id. In this part of the analysis, we consider “the
elements of each claim both individually and ‘as an ordered combination’”
must be considered “to determine whether the additional elements
‘transform the nature of the claim’ into a patent-eligible application.” Alice,
573 U.S. at 217.
Appellant argues that “generating item frequency data by performing
pre-calculations on historical data to populate the plurality of tables” (step
[6]), “updating the item count column in respective tables in real-time with
real-time data when processing the real-time data” (steps [7], [8]) and
“generating, at runtime, the ranking of the item frequency data by merely
sorting the item count column of the specific table, thus resulting in efficient
retrieval of the ranking of the item frequency data at runtime” (step [9])
“naturally results in faster processing speed” and confers eligibility on the
claims.” Appeal Br. 27. See also Appeal Br. 19, 20, 21, 22, 23, 24, 25, 26,
27, and 28–31, repeating the same argument again about the interrelated
tables.
We understand and acknowledge Appellant’s arguments that all the
steps in the claim, particularly table configuration, monthly tables used, pre-
calculations, updating in real-time, and ranking of the items, is a specific
arrangement which enables the ranking to perform efficiently, etc. But the
question is whether this ordered combination of steps gather and process the
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data in an unconventional way and therefore provide an “inventive concept.”
Eligibility Guidance, 84 Fed. Reg. 56.
The claim, as explained by the Examiner, comprises using monthly
tables, each table listing items and item numbers processed (step [2]),
generating frequency data based on the historical monthly data (steps [4],
[6], updating the table in real-time by adding or subtracting from the item
count in the historical table (step [8]), and then ranking the update numbers
ranked by sorting them by value (step [9]). Ans. 13–14. We summarize the
specific steps here, so while our words might deviate from the words in the
claim, we are aware of the plain language recited in the claim. The ranking
is apparently faster, according to Appellant, because the historical data is
already calculated and filled into the tables, and then updated in real-time.
Assuming this is an actual improvement, the improvement does not change
the way the computer operates; rather it changes the way a generic computer
performs a calculation and sorts calculated values. As explained in Step 2A,
Prong One, these steps are abstract, alone, and abstract in the ordered
combination in which they are performed. Appellant did not establish that
the database structure with rows and columns is unconventional nor
unconventional in the way that the values in the table are calculated (step
[6]), updated (step [8]), and displayed (step [9]). The improvement is to the
way in which the calculation is performed, which is the abstract idea of
mathematical concepts and the fundamental economic practice, and
therefore cannot confer eligibility to the claim.
Further, as discussed in the § 103 rejection, Berger expressly discloses
partitioning data into months (41) and the benefit of pre-aggregating data in
reducing response time (27). Therefore, the improvement in ranking asserted
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by Appellant is based on a feature expressly disclosed in Berger (27:
“Accordingly, data store 110 stores pre-aggregated or pre-calculated data
with respect to distinct count queries. Aggregation of data prior to receiving
a query is an important factor in reducing overall query response time.”).
Appellant also argues the benefits of updating in real-time as evidence that
abstract idea is integrated into a practical application (Reply Br. 13), but did
dispute the Examiner’s finding in the context of obviousness that this aspect
is described in Banerjee (Final Act. 9).
After reviewing all Appellant’s arguments, we conclude that they do
not persuasively establish that the claims are not directed to an abstract idea.
All the claims were argued together. Appeal Br. 36. Therefore, the rejection
of claim 1–27 as patent ineligible under 35 U.S.C. § 101 is affirmed.

INDEFINITENESS REJECTION
The Examiner found claims 1, 10, and 19 indefinite in the recitation of
“the real-time data comprising items processed and items to be processed”
because “real time data” is intangible and purportedly comprises ‘items’
which are described in the Specification as tangible (e.g., ‘snowboards,’
‘hats,’ ‘jackets,’ and ‘sleds’).” Ans. 18. We do not agree. The claim refers to
a database comprising such data, not the actual items themselves. Thus, it
clear that the database comprises the real-time data corresponding to items
which have been processed or which are to be processed.
The Examiner also found the claim indefinite for the recitation of
“processing real-time data” in step [7] because it is unclear whether the latter
is the same as the “real-time data” recited in step [1]. Final Act. 3–4. We do
not agree that the claim is indefinite. It is clear from the claim language that
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step [1] is directed to the database where the real-time data of step [7] is
stored.
Accordingly, the indefiniteness rejection is reversed.

CONCLUSION
In summary:
Claims
Rejected
35 U.S.C.
§
Reference(s)/Basis Affirmed Reversed
1–8, 10–17,
19–26
103(a) Banerjee, BIRT,
Berger
1–8, 10–17,
19–26

2–5, 8, 11–
14, 17, 20–
23, 26
103(a) Banerjee, BIRT,
Berger, Hassine
2–5, 8, 11–
14, 17, 20–
23, 26

1–27 101 Eligibility 1–27
1–27 112(b) Indefiniteness 1–27
Overall
Outcome
1–27

TIME PERIOD
No time period for taking any subsequent action in connection with
this appeal may be extended under 37 C.F.R. § 1.136(a)(1)(iv).

AFFIRMED