DETAILED ACTION
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 .
Response to Arguments
Applicant’s arguments, filed 02/23/26, with respect to the rejection(s) of claim(s) 1-5, 7-15, 17-21 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of Lott (Pub No 20130003552) further in view of Tsukahara (JP 2023135696 A) and newly cited Lu (WO 2012116540 A1)
Regarding claim 1,
The applicant argues that the prior art do not teach the amended limitation.
The examiner relies on newly cited Lu to teach the amended limitation.
All other arguments are fully addressed above.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art before the effective filing date of the invention to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-3, 7-13, 17-20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lott (Pub No 20130003552) further in view of Tsukahara (JP 2023135696 A) and Lu (WO 2012116540 A1)
Regarding claim 1 and 11 and 20,
Lott teaches A computer server system comprising:
A non-transitory computer readable storage medium comprising processor-executable instructions which, when executed, configure a processor to: (a computer program product for wireless communications in a wireless network includes a computer-readable medium having non-transitory program code recorded thereon, see para [0012])
a communications module; (para [0033])
a processor coupled with the communications module; and (para [0033])
a memory coupled to the processor and storing processor-executable instructions which, when executed by the processor, configure the processor to: (para [0033])
identify a volume target for a queue based on a recent queue throughput; (interpreted as determining a target queue length based on the rate of throughput at the link, see para [0048])
select a rule set based on the volume target; and (interpreted as When the BSC 230 does not have enough data to fill the open windows or queue target sizes, a strict priority rule can be implemented. The rule allows for the improved or optimal throughput to be allocated to the corresponding users (i.e., AT) to fill up the window sizes, see para [0065])
implement the selected rule set to populate the queue. (interpreted as For example, an up ramping rule may include an additive factor of 1.0, see para [0069])
However Lott does not teach the rule is determined based on a maximizing the fraud detection value.
Tsukahara teaches and at least one other parameter includes detected fraud value, the rule set (e.g. model) selected to maximize the detected fraud value (interpreted as The optimization model 68 uses the number of rules, the number of detections, and the precision rate to create a model that maximizes the number of fraud detections when rules are set to be applied (“1”) or not applied (“0”)., see pg 6 line 1-10) subject to the volume target. (interpreted as This is a model that finds the solution to the objective function… The constraint conditions are the inspection time per case included in the resource information 66 and the constraint time, see pg 6 line 1-10. The examiner interprets the volume as the inspection time per case since the higher the volume the less time to inspect each case and therefore is a model constraint based on volume.)
It would have been obvious to modify before the effective filing date of the invention the rule based on volume as taught by Lott with the rule for maximizing fraud detection based on volume as taught by Tsukahara with the motivation being to optimize the throughput while maintaining a certain quality.
However Lott in view of Tsukahara do not teach a plurality of predefined rule sets.
Lu teaches a plurality of predefined rule sets. (interpreted as The management device may assign a token to the queue of messages to be scheduled in the board based on a plurality of predetermined policies. The predetermined policy can be set in the management device in advance, or can be dynamically adjusted according to the statistics of the data traffic in each board, see pg 5 line 1-8)
It would have been obvious to modify before the effective filing date of the invention the rule as taught by Lott in view of Tsukahara with the plurality of rules as taught by Lu with the motivation being to select the most optimal rule from the plurality of rules.
Regarding claim 2 and 12,
Lott teaches the computer server system of claim 1, wherein the instructions, when executed by the processor, configure the processor to: detect a change in the recent queue throughput; and responsive to detecting the change in the recent queue throughput: identify an updated volume target for the queue based on the change in the recent queue throughput; select the rule set based on the updated volume target and the at least one other parameter; and implement the selected rule set to re-populate the queue. (interpreted as the apparatus 600 for wireless communication includes means for periodically adjusting a target queue length based on an estimated throughput of a network link and based on a measured underflow on the network link. The periodically adjusting means may be the adjusting module 608 and/or the enhanced flow control system 614 of the apparatus 600 configured to perform the functions recited by the periodically adjusting means, see para [0075]. Also see For example, an up ramping rule may include an additive factor of 1.0, see para [0069])
Regarding claim 3 and 13,
Lott teaches the computer server system of claim 1, however does not teach wherein the rule set is selected based on linear programming.
Tsukahara teaches wherein the rule set is selected based on linear programming. (interpreted as The optimization model 68 is, for example, an algorithm based on mathematical programming (linear programming, integer programming, etc.) see pg. 6 line 6-9)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to combine the policy taught by Lott with the linear program for determining policies as taught by Tsukahara with the motivation being to use mathematical programming for calculating the most optimal system for performing a certain task (e.g. maximizing inspection time per case to increase fraud detection).
Regarding claim 7 and 17,
Lott teaches the computer server system of claim 1, however does not teach wherein the instructions, when executed by the processor, configure the processor to: prior to selecting the rule set, determine a total amount of expected fraud value for each available rule set.
Tsukahara teaches wherein the instructions, when executed by the processor, configure the processor to: prior to selecting the rule set, determine a total amount of expected fraud value for each available rule set. (interpreted as The optimization model 68 uses the number of rules, the number of detections, and the precision rate to create a model that maximizes the number of fraud detections when rules are set to be applied (“1”) or not applied (“0”)., see pg 6 line 1-10)
It would have been obvious to modify before the effective filing date of the invention the rule based on volume as taught by Lott with the rule for maximizing fraud detection based on volume as taught by Tsukahara with the motivation being to optimize the throughput while maintaining a certain quality.
Regarding claim 8,
Lott teaches the computer server system of claim 1, wherein the queue is populated with a plurality of entities. (interpreted as The target queue length represents an amount of data being buffered at a network element, see para [0012])
Regarding claim 9 and 18,
Lott teaches the computer server system of claim 8, however does not teach wherein the plurality of entities includes data transfers flagged as being potentially fraudulent.
Tsukahara teaches wherein the plurality of entities includes data transfers flagged as being potentially fraudulent. (interpreted as Rule 1 is a rule for determining that the determination target information A and B are suspected of being fraudulent. For example, Rule 2 is a rule for determining that the determination target information C and D are suspected of being fraudulent. For example, Rule 3 is a rule for determining that the determination target information E and F are suspected of being fraudulent, see pg 7 line 35-45)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to combine the system taught by Lott with the fraud flagging taught by Tsukahara with the motivation being to have a more secure system
Regarding claim 10 and 19,
Lott teaches the computer server system of claim 1, wherein the volume target includes a count of data transfers. (interpreted as The target queue length may represent an amount of data being buffered at a base station, see para [0046])
Claim(s) 4-5, and 14-15, is/are rejected under 35 U.S.C. 103 as being unpatentable over Lott (Pub No 20130003552) further in view of Tsukahara (JP 2023135696 A), Lu (WO 2012116540 A1), and Ordorica (Pub No 20230206372)
Regarding claim 4 and 14,
Lott in view of Tsukahara teaches the computer server system of claim 1, however does not teach wherein the queue includes a secondary review queue.
Ordorica teaches wherein the queue includes a secondary review queue. (interpreted as The analysis performed would typically be different than for audit data, and hence a weight function may be used to optimized the weights given to audit data and secondary review outcome data in retraining the fraud detector model, see para [0060])
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to combine the system taught by Lott in view of Tsukahara with the secondary review as taught by Ordorica with the motivation being to reduce risk by having a second filtering of the data for errors.
Regarding claim 5 and 15,
Lott in view of Tsukahara teaches the computer server system of claim 1, however does not teach wherein the queue is associated with a particular data bucket.
Ordorica teaches wherein the queue is associated with a particular data bucket. (interpreted as The range 602b may be further sub-classified into a low risk bucket 612a for human review, a medium risk bucket 612b for human review, and a high risk bucket 612c for human review, see para [0078]
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to combine the system taught by Lott in view of Tsukahara with the secondary review as taught by Ordorica with the motivation being to reduce risk by having a second filtering of the data for errors.
Claim(s) 21 is/are rejected under 35 U.S.C. 103 as being unpatentable over Lott (Pub No 20130003552) further in view of Tsukahara (JP 2023135696 A), Lu (WO 2012116540 A1), and Yamasaki (Pub No 20210367893)
Regarding claim 21,
Lott teaches the server computer system of claim 1, however does not teach wherein the instructions, when executed by the processor, configure the processor to engage a classifier to assign each entity to one of a plurality of queues based on the detected fraud value.
Yamasaki teaches wherein the instructions, when executed by the processor, configure the processor to engage a classifier to assign each entity to one of a plurality of queues based on the detected fraud value. (interpreted as The present exemplary embodiment is capable of suppressing loss of communication important to travel of the vehicle 10 by assigning associations to queues based the risk level of the communication in the vehicle 10, see para [0110])
It would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to combine the system taught by Lott in view of Tsukahara with the queue assignment as taught by Yamasaki with the motivation being to prioritize data based on the risk level.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). 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 BAO G NGUYEN whose telephone number is (571)272-7732. The examiner can normally be reached M-F 10pm - 6:30pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Huy Vu can be reached at 571-272-3155. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/BAO G NGUYEN/Examiner, Art Unit 2461
/HUY D VU/Supervisory Patent Examiner, Art Unit 2461