Ex Parte Lee

Board of Patent Appeals and Interferences

Feb 25, 2010

09782149 (B.P.A.I. Feb. 25, 2010)

UNITED STATES PATENT AND TRADEMARK OFFICE
____________
BEFORE THE BOARD OF PATENT APPEALS
AND INTERFERENCES
____________
Ex parte YUNG-SEOP LEE
____________
Appeal 2009-007352
Application 09/782,149
Technology Center 3600
____________
Decided: February 25, 2010
____________

Before KENNETH W. HAIRSTON, TERRY J. OWENS, and
HUBERT C. LORIN, Administrative Patent Judges.

LORIN, Administrative Patent Judge.

DECISION ON APPEAL
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STATEMENT OF THE CASE
Yung-Seop Lee (Appellant) seeks our review under 35 U.S.C.
§ 134 (2002) of the final rejection of claims 1-7 and 10-16. We have
jurisdiction under 35 U.S.C. § 6(b) (2002).

SUMMARY OF DECISION
We AFFIRM-IN-PART.
THE INVENTION
The invention “relates generally to a computer implemented
method and apparatus for evaluating records indicative of
contributions of a customer to a business, such as an airline.”
Specification 1:4-6.
Claim 1, reproduced below, is illustrative of the subject matter
on appeal.
1. A computer implemented method of evaluating a plurality of
customer records stored in a computer database to identify high
value customers to be targeted by a customer retention or
reward program, each customer record having at least a first
attribute and a second attribute, each of the first attribute and
the second attribute having an associated attribute value, the
method comprising:
a) first sorting the plurality of customer records
based on the first attribute and assigning a first
discretized attribute to each customer record where the
first discretized attribute is based on the sorted rank of
the customer record;
b) second sorting the plurality of customer records
based on the second attribute and assigning a second
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discretized attribute to each customer record where the
second discretized attribute is based on the sorted rank of
the customer record;
c) third sorting the plurality of customer records in
to an order based on the assigned first discretized
attribute scores associated with the first attribute;
d) fourth sorting the ordered plurality of customer
records resulting from the third sorting in to an order
where the customer records having the same first
discretized attribute scores are further sorted based on the
assigned second discretized attribute scores associated
with the second attribute;
e) fifth sorting the ordered plurality of customer
records resulting from the fourth sorting in to an order
based on the attribute values associated with at least the
first attribute and the second attribute, until customer
records, which have different attribute values associated
with at least the first attribute or the second attribute,
have been sorted to different ranks;
f) assigning an evaluation score to each customer
record based on the rank of each customer record after
the fifth sorting and independent of the discretized
attribute scores; and
g) identifying the high value customers by
selecting the customer records that have the highest
assigned evaluation scores.

THE REJECTIONS
The Examiner relies upon the following as evidence of
unpatentability:
Jones III US 6,925,441 B1 Aug. 2, 2005

Hughes, Arthur Middleton, Quick Profits with RFM Analysis,
http://web.archive.org/web/19990208211536/www.dbmarketin
g.com/articles/rfmtools.html, Database Marketing Institute,
archived Feb. 8, 1999. (Hughes)
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RFM for Windows, Database Marketing Institute Software,
http://www.dbmarketing.com/ams.html, Database Marketing
Institute, archived Feb. 3, 1999. (RFM)

The following rejections are before us for review:
1. Claims 1-7, 10, and 14-16 are rejected under 35 U.S.C. §101 as
being directed to non-statutory subject matter.
2. Claims 1-7, 10, and 14-16 are rejected under 35 U.S.C. §103(a)
as being unpatentable over Hughes and Jones III.
3. Claims 11-13 are rejected under 35 U.S.C. §103(a) as being
unpatentable over Hughes, Jones III, and RFM.

ISSUES
The first issue is whether the Examiner has shown the processes
claimed in claims 1-7, 10, and 14-16 fail to pass the Bilski machine-
or-transformation test determining patent-eligibility of processes
under 35 U.S.C. §101.
The second issue is whether the record supports the Examiner’s
finding that Hughes discloses the step of
fifth sorting the ordered plurality of customer records
resulting from the fourth sorting in to an order based on
the attribute values associated with at least the first
attribute and the second attribute, until customer records,
which have different attribute values associated with at
least the first attribute or the second attribute, have been
sorted to different ranks
(claim 1) and, as a consequence, whether the rejections of claims 1-7,
10, and 14-16 under 35 U.S.C. §103(a) as being unpatentable over
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Hughes and Jones III and claims 11-13 under 35 U.S.C. §103(a) as
being unpatentable over Hughes, Jones III, and RFM are tenable.

FINDINGS OF FACT
We find that the following enumerated findings of fact (FF) are
supported by at least a preponderance of the evidence. Ethicon, Inc. v.
Quigg, 849 F.2d 1422, 1427 (Fed. Cir. 1988) (explaining the general
evidentiary standard for proceedings before the Office).
Claim construction
1. The first step of the method of claim 1 calls for a sorting of
customer records based on a “first attribute” and assigning “a
first discretized attribute” to each record, “where the first
discretized attribute is based on the sorted rank of the customer
record.”
2. The Specification does not appear to provide express
definitions for “attribute” or “discretized attribute.”
3. But the Specification (Pp. 6-7) provides an example of data for
each customer record with respect to the airline industry (Table
10) where the “attributes listed in the header row of Table 1” (p.
7) are labels descriptive of the type of information contained in
each record.
4. Two attributes the Specification discusses are “Net Revenue
(CV) and No. of Flights (FV)” (p. 8).
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5. Accordingly, “attributes” mean labels describing certain
information contained by the data gathered in each record of a
computerized database.
6. The data that is gathered can be in any form “includ[ing], but
are not limited to, number, currency, data, time, text, sound, and
image” (p. 7).
7. The Specification appears to define “discretized attribute” as a
score applied to the records for a particular attribute. In the
following example, the data is sorted either by the CV or FV
and given a score:
In the preferred embodiment, the records/customers are
sorted, in step 30, in ascending order of CV or FV values.
Next, in step 32, the sorted CV or FV values are split into
quartiles, with break points of 25%, 50% and 75%. ... In
particular, CV or FV of the lowest value up to 25% are
grouped into quartile 1, CV or FV of values between
25%-50% are grouped into quartile 2, CV or FV values
between 50%-75% are grouped into quartile 3, and CV or
FV values of 75% and up are grouped into quartile 4.
Each quartile is then assigned a corresponding score of
from 1 to 4, in step 34. In particular, all the CV or FV
which belongs to quartile 1 will have the same attribute
score of 1, all the CV or FV which belongs to quartile 2
will have the same attribute score of 2, and so one.
Specification: Pp. 8-9.
8. The second step of the method of claim 1 calls for the customer
records to be sorted based on a “second attribute” and “a second
discretized attribute” is assigned to each record.
The attribute scores [for the CV attribute] are stored in
Table 1 as Net Contribution Score (CS). Similarly, the
attribute scores which correspond to FV values are stored
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in Table 1 as Gross Frequency Score (FS). The CS and
FS scores constitute a pair in the form of (CS,FS) . . . .
Specification: p. 9, ll. 15-18.
9. The third step of the method of claim 1 calls for the records to
be sorted for a third time “to an order based on the assigned
first discretized attribute scores associated with the first
attribute.” In the example of Table 1 of the Specification,
where CV is the first attribute, the third claim step would sort
the records according to CS.
10. According to the fourth step of the method of claim 1, the result
of the third sorting is further sorted “to an order where the
customer records having the same first discretized attribute
scores are further sorted based on the assigned second
discretized attribute scores associated with the second scores
associated with the second attribute.”
11. The fourth claim step is condition-precedent on the existence of
“customer records having the same first discretized attribute
scores.”
12. In the example of Table 1 of the Specification, where CV is the
first attribute and FV is the second attribute, the fourth claim
step would sort the records according to FS, if more than one
record has the same CS.
13. According to the fifth step of the method of claim 1, the result
of the fourth sorting is further sorted based on the first and
second attributes until records having different first and second
attribute values have been sorted into different ranks.
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14. In the example of Table 1 of the Specification, where CV is the
first attribute and FV is the second attribute, the fifth claim step
would sort the records according to CV and FV and into
different ranks.
15. According to the sixth step of the method of claim 1, the
different ranks are assigned evaluation scores. See
Specification: Table 1.
16. According to the seventh step of the method of claim 1, the
records having the highest evaluation scores are identified as
the high value customers.

The scope and content of the prior art
17. Hughes (para. 30 relates to a method for analyzing records in a
computerized customer database.
18. Hughes (para. 2) describes applying a RFM [Recency,
Frequency, Monetary] analysis to customer records in computer
databases.
19. Hughes (para. 4) explains the RFM analysis process, when
applied for the purpose of direct marketing, this way:
This can easily be illustrated by anyone with a customer
database that includes purchase history. The database
has to keep one piece of information in every customer
record: the most recent discretionary purchase data. The
database is sorted by that date, and the top 20% (in terms
of recency) is given a code of “5”, The next 20% in terms
of recent purchases is coded as “4”, etc. Everyone in the
database now is either 5, 4, 3, 2, 1 in terms of recency.
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20. In describing the RFM analysis process, Hughes (para. 4)
describes sorting records by an attribute (Recency) and
assigning attribute scores to the sorted records corresponding to
a resultant ranking.
21. Hughes describes a similar sorting/assigning of records by
Frequency (para. 6) or Monetary (para. 8).
22. Hughes (para. 10) describes combining assigned Recency,
Frequency, and Monetary scores based on their individual
sorting such that each database record is given “a three digit
RFM “cell code” . . . all customers end up with three digits in
their database records.”
23. Hughes (para. 35) describes an example of a RFM sorting
whereby five groups of records are first sorted by Recency, then
each Recency-sorted group is further sorted by Frequency
resulting in 25 Frequency groups, which are then further sorted
by Monetary to create 125 RFM cells.
24. Jones, III is directed to target marketing of consumers through
information provided via a computer database.
25. Jones, III (col. 12, ll. 35-66, discloses calculating the best value
to the customer, the “net present value” [NPV], and a customer
valuation score, “customer value scoring” derived from
information in a database about individual customers and their
propensity to accept an offer (col. 11, ll. 37-45).

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Any differences between the claimed subject matter and the
prior art
26. The difference between the claimed subject matter and the
prior art is that the prior art does not disclose the claim step
“fifth sorting the ordered plurality of customer records resulting
from the fourth sorting in to an order based on the attribute
values associated with at least the first attribute and the second
attribute, until customer records, which have different attribute
values associated with at least the first attribute or the second
attribute, have been sorted to different ranks” (claim 1).
27. Databases are old in the art.
28. Storing records and sorting stored records are known functions
of databases.
The level of skill in the art
29. Neither the Examiner nor the Appellant has addressed the level
of ordinary skill in the pertinent art of using a computer
database to evaluate records. We will therefore consider the
cited prior art as representative of the level of ordinary skill in
the art. See Okajima v. Bourdeau, 261 F.3d 1350, 1355 (Fed.
Cir. 2001) (“[T]he absence of specific findings on the level of
skill in the art does not give rise to reversible error ‘where the
prior art itself reflects an appropriate level and a need for
testimony is not shown’”) (quoting Litton Indus. Prods., Inc. v.
Solid State Sys. Corp., 755 F.2d 158, 163 (Fed. Cir. 1985)).

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Secondary considerations
30. There is no evidence on record of secondary considerations of
non-obviousness for our consideration.

PRINCIPLES OF LAW
§ 101 - Patentable Subject Matter - Process
[T]he proper inquiry under § 101 is not whether the process
claim recites sufficient “physical steps,” but rather whether the
claim meets the machine-or-transformation test. [fn]25 As a
result, even a claim that recites “physical steps” but neither
recites a particular machine or apparatus, nor transforms any
article into a different state or thing, is not drawn to patent-
eligible subject matter. Conversely, a claim that purportedly
lacks any “physical steps” but is still tied to a machine or
achieves an eligible transformation passes muster under § 101.
In re Bilski, 545 F.3d 943, 961 (Fed. Cir. 2008) (en banc).
Obviousness
Section 103 forbids issuance of a patent when ‘the
differences between the subject matter sought to be patented
and the prior art are such that the subject matter as a whole
would have been obvious at the time the invention was made to
a person having ordinary skill in the art to which said subject
matter pertains.’
KSR Int'l Co. v. Teleflex Inc., 550 U.S. 398, 406 (2007). The question
of obviousness is resolved on the basis of underlying factual
determinations including (1) the scope and content of the prior art, (2)
any differences between the claimed subject matter and the prior art,
and (3) the level of skill in the art. Graham v. John Deere Co., 383
U.S. 1, 17-18 (1966). See also KSR, 550 U.S. at 407 (“While the
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sequence of these questions might be reordered in any particular case,
the [Graham] factors continue to define the inquiry that controls.”)
The Court in Graham further noted that evidence of secondary
considerations “might be utilized to give light to the circumstances
surrounding the origin of the subject matter sought to be patented.”
Graham, 383 U.S. at 17-18.

ANALYSIS
The rejection of claims 1-7, 10, and 14-16 under 35 U.S.C. §101 as
being directed to non-statutory subject matter.
The Examiner rejected the claims as being directed to
nonstatutory subject matter under §101 because the claimed process is
not tied to a particular apparatus, notwithstanding that the claims
recite the phrase “computer-implemented”, which the Examiner
viewed as a nominal recitation, and does not transform underlying
subject matter. Answer 3. The Examiner’s reasoning follows the
Bilski machine-or-transformation test (see supra) for determining
patent-eligibility of processes under 35 U.S.C. §101.
The Appellant argues that the claimed process is tied to
particular machine, that is, a computer with a database for sorting
database records, and transforms underlying subject matter, “i.e.,
records stored in a computer database” (Reply Br. 4).
As to the transformation prong the Examiner’s position that the
claimed process fails to transform underlying subject matter is well
reasoned. We are not persuaded by the Appellant’s argument as to
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error in the Examiner’s reasoning (Reply Br. 4). The Appellant
argues that the various claim steps of sorting the database records
necessarily transforms the records stored in the computer database. A
careful reading of the claims reveals no express step of using the
computer database to sort the records. The claims reasonably broadly
cover sorting the records separate from the database that stores them.
Also, we fail to understand in what way the act of sorting
“transforms” the underlying records. As best we can understand, the
sorting causes the records to change location, but the records
themselves do not change.
As to the machine prong, the Examiner’s position that the
phrase “computer-implemented” is a nominal recitation of structure
which would not tie the claimed process to a particular apparatus is
also reasonable.
However, as to claims 1-7 and 14-16, the Examiner does not
explain why the additional recitation of a “computer database” in the
claims for storing “customer record[s] having at least a first attribute
and a second attribute” is insufficient to meet the machine prong of
the (Bilski) machine-or-transformation test. As a result, the Examiner
has not made out in the first instance a prima facie case that the
claimed subject matter is not a statutory process under §101 for failing
to satisfy the machine prong of the (Bilski) machine-or-transformation
test.
We reach the opposite conclusion as to claim 10. Like claims
1-7 and 14-16, claim 10 recites “computer-implemented”. This is a
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nominal recitation of structure which would not tie the claimed
process to a particular apparatus. But unlike claims 1-7 and 14-16,
claim 10 recites no “computer database” and no such database capable
of any particular function. All that is recited is a step of “storing the
records in a database.” A “database” per se is not necessarily a
“computer database.” According to the Webster’s New World
Dictionary of Computer Terms 142 (8th Ed. 2000.)(Entry for
“database.”), a “database” is defined as
A collection of related information about a subject organized in
a useful manner that provides a base or foundation for
procedures, such as retrieving information, drawing
conclusions, making decisions. Any collection of information
that serves these purposes qualifies as a database, even if the
information isn’t stored on a computer. In fact, important
predecessors of today’s sophisticated business database systems
were files kept on index cards and stored in file cabinets.
Information usually is divided into data records, each with one
or more data fields.
Emphasis added. Thus, the recitation of using a “database” per se in
the claimed computer-implemented method does not necessarily tie
the claimed process to a particular machine. Accordingly, we are not
persuaded by the Appellant’s argument that claim 10 necessarily
passes the machine prong of the (Bilski) machine-or-transformation
test and is thereby necessarily a statutory process under §101.

The rejection of claims 1-7, 10, and 14-16 under 35 U.S.C. §103(a) as
being unpatentable over Hughes and Jones III.
The Examiner states that Hughes discloses the fifth step of the
process of claim 1. According to the Examiner,
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[t]o summarize, after the customer records have been sorted and
assigned attribute scores, the customers are segmented
according to their corresponding RFM codes. Hughes teaches
the additional step of sorting customer records according to
recency, where records are divided into quintiles and assigned
attribute values of 1-5. Thus, the Examiner asserts that the
placement of customers into their respective three digit RFM
cell codes, which is based on the attribute values associated
with both the first and second attributes and a third attribute,
meets the claimed limitation of “fifth sorting the ordered
plurality of customer records resulting from the fourth sorting
in to an order based on the attribute values associated with at
least the first attribute and the second attribute, until customer
records, which have different attribute values associated with at
least the first attribute or the second attribute, have been sorted
to different ranks.”
Answer 25-26.
The Appellant disagrees. See App. Br. 14 and Reply Br. 5.
We agree with the Appellant.
Hughes sorts the records independently by Recency, Frequency,
and Monetary. The passage at para.10 of Hughes (FF 22) that the
Examiner is relying upon describes attaching to each record a number
based on each of the Recency, Frequency, and Monetary sortings.
This yields a three-digit code to be assigned to each cell. The fifth step
of the claimed method is doing something different. By that step, the
result of the fourth sorting is further sorted based on the first and
second attributes until records having different first and second
attribute values have been sorted into different ranks. FF 13. The
fourth step involved sorting the third sorting further sorted “to an
order where the customer records having the same first discretized
attribute scores are further sorted based on the assigned second
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discretized attribute scores associated with the second scores
associated with the second attribute.” FF 10. Looking at Table 1 of
the Specification, in effect, the fifth step of the method of claim 1
would sort the records according to attributes CV and FV into
different ranks after they had been sorted by the attributes CV (first
step) and FV (step 2) and assigned respective first and a second
discretized attribute scores CS and FS (first and second steps), sorted
by CS (third step), and by FS if more than one record has the same
CS. FF. 7-9, 12, and 14. While there appears to be no dispute that
Hughes discloses assigning attribute scores to the sorted records (see
FF 19), nothing in Hughes speaks to sorting the records by those
scores. Accordingly, Hughes does not disclose those claim steps
where such a sorting is to be performed and that would include the
fifth sorting step.
Because the evidence does not support the Examiner’s basis for
rejecting the claims over the cited prior art combination, we find that a
prima facie case of obviousness has not been made out in the first
instance. While our discussion above is focused on claim 1, the other
independent process claim 10 also provides for steps by which the
records are sorted by assigned discretized attribute scores. Since the
Examiner’s position that Hughes discloses such a sorting is not
supported by the evidence, the rejection as to that claim is also not
sustained. The rejection of the dependent claims is not sustained for
the same reasons. Cf. In re Fritch, 972 F.2d 1260, 1266 (Fed. Cir.
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1992) ("[D]ependent claims are nonobvious if the independent claims
from which they depend are nonobvious.").

The rejection of claims 11-13 under 35 U.S.C. §103(a) as being
unpatentable over Hughes, Jones III, and RFM.
Independent claims 11, 12, and 13 provide for a computer
architecture, system, and an article, respectively, comprising means
and instructions paralleling the steps of the process claims. The
Examiner takes the same position as to the means and instructions
corresponding to the steps of the claimed processes by which the
records are sorted by assigned discretized attribute scores that was
taken when addressing that limitation in claim 1. See Answer 19, 20,
and 22. Since, for the foregoing reason, the evidence does not support
the finding that Hughes discloses such a sorting, the rejection as to
these claims is also not sustained.
CONCLUSIONS
We conclude that the Appellant has shown that the Examiner
erred in rejecting claims 1-7 and 14-16 under 35 U.S.C. §101 as being
directed to non-statutory subject matter.
We conclude that the Appellant has not shown that the
Examiner erred in rejecting claim 10 under 35 U.S.C. §101 as being
directed to non-statutory subject matter.
The rejection of claims 1-7, 10, and 14-16 under 35 U.S.C.
§103(a) as being unpatentable over Hughes and Jones III and the
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rejection of claims 11-13 under 35 U.S.C. §103(a) as being
unpatentable over Hughes, Jones III, and RFM are not sustained.
DECISION
The decision of the Examiner to reject claims 1-7 and 10-16 is
affirmed-in-part
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)
(2007).

AFFIRMED-IN-PART

mev

JAMES M. STOVER
TERADATA CORPORATION
2835 MIAMI VILLAGE DRIVE
MIAMISBURG OH 45342