Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
DETAILED ACTION
Response to Arguments
Applicants arguments regarding the 101 rejection of the claims have ben considered but are not persuasive.
Applicant argues that the re-trained model is improved compared to the initially recited model.
The Office agree that the improvement is the result of the re-training but the re-training, so to speak, is merely training or optimizing the model, but optimizing a model is not a technical improvement since the model itself is not a technical operation, i.e., the analysis may be done by a human using pen and paper. Therefore, the determination of the impact parameter and the optimization of the model is the abstract idea and improving an abstract idea does not make the claims eligible.
Applicant argues the claims are eligible considering Ex Parte Desjardins and SME example 47.
The Office asserts that SME 47 claim 2 is the closest example to the claims but claim 2 is not eligible because it comprises abstract ideas with the words applied by computers recited at a high level of generality.
The Office asserts that the claims are not supported for eligibility by Desjardins because Desjardins recites a technical improvement while the present claims do not for the reasons stated above.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claim(s) 1-19 and 23 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s):
A computer-implemented method comprising:
receiving, with at least one processor, an inquiry request message identifying
a first payment transaction having a first plurality of transaction parameters and a first authorization decision;
filtering, with at least one processor, a plurality of historical payment
transactions stored in a database comprising transaction data to identify a first subset of historical payment transactions from the plurality of historical payment transactions, the transaction data comprising, for each of the plurality of historical payment transactions, a plurality of transaction parameters and an authorization decision, wherein the first subset comprises payment transactions having an authorization decision different from the first authorization decision;
for each of the historical payment transactions in the first subset, generating,
with at least one processor, a similarity score relative to the first payment transaction based on comparing the first plurality of transaction parameters to the plurality of transaction parameters associated with each of the historical payment transactions in the first subset, the similarity score generated only for historical payment transactions in the first subset;
d) filtering, with at least one processor, the first subset to identify a second subset of historical payment transactions from the first subset based on the similarity score for each payment transaction in the second subset of historical payment transactions satisfying a threshold;
e) inputting, with at least one processor, only the second subset of historical payment transactions to a machine-learning model;
f) determining, with the machine learning model, at least one impact parameter of the first plurality of transaction parameters by comparing the first plurality of transaction parameters with the plurality of transaction parameters associated with the plurality of historical payment transactions in the second subset; and
g) retraining, with at least one processor, the machine-learning model based on determining that the at least one impact parameter corresponds to an incorrect reason for the first authorization decision.
The underlined portion of the claims recite a mental process, comprising an evaluation judgement or opinion as the claims use a model to determine an impact parameter by comparing transaction data, and retraining the model based on the impact parameter corresponding to an incorrect reason for the decision.
This judicial exception is not integrated into a practical application because the abstract idea is performed by generic computers (processors, database, CRM with instructions, machine-learning), amounting to adding the words “apply it” to the abstract idea. The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception for the reasons above. Claims 12 and 23 are similarly rejected.
The dependent claims merely narrow the abstract idea and as a whole and in combination do not transform the abstract idea into a practical application or add significantly more.
Conclusion
THIS ACTION IS MADE FINAL. Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to WILLIAM E RANKINS whose telephone number is (571)270-3465. The examiner can normally be reached on 9-530 M-F.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Bennett Sigmond can be reached on 303-297-4411. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative or access to the automated information system, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/WILLIAM E RANKINS/Primary Examiner, Art Unit 3694