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 .
General Remarks
This communication is considered fully responsive to Applicant’s application filed 04/04/2025.
Application filed: 04/04/2025
Applicant’s PgPUB: N/A
Claims:
Claims 1-20 are pending.
Claims 1, 10 and 19 are independent.
Continuity/Priority Data:
This Application claims priority to Chinese Application No. CN202510191755.2 filed 02/02/2025.
Examiner Note:
The claims appears to be translated from Chinese. There may be need to “clean up” the language of the claims to bridge the translation gap.
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 may not be obtained though the invention is not identically disclosed or described as set forth in section 102 of this title, if 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. Patentability shall not be negatived by the manner in which the invention was made.
Claims 1, 2, 4-7, 9-11, 13-16 and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over Chinese Application No. CN 116684377 A to Cao et al. (“Cao”) in view of Chinese Application No. CN 11921203 A to Yan et al. (“Yan”).
As to claim 1, Cao discloses:
a method for message allocation, comprising:
obtaining respective verification pass rates of a plurality of message channels and respective unit costs of message transmissions of the plurality of message channels (¶0015, ¶0016 – Cao teaches determining candidate channels that satisfy the cost selection interval from the remaining channels and a pre-trained quality prediction model is used to predict the success rate of sending the message to each candidate channel to determine the target channel with the highest success rate.);
determining, based at least on the respective verification pass rates and the respective unit costs of the plurality of message channels, respective message allocation weights of the plurality of message channels according to a message allocation objective, the message allocation objective being associated with at least a total cost of the message transmissions of the plurality of message channels (¶0073 – Cao teaches to determine the target channel with the highest success rate, and resend the message using the target channel. This embodiment combines cost progression and quality prediction methods to gradually reduce the weight of cost in the scheduling process and gradually increase the weight of quality in the scheduling process during the process of multiple retries of the same message); and
allocating verification code messages to the plurality of message channels (¶0070, ¶0071 - Cao teaches after determining the cost selection interval, the communication platform can determine a target channel from the remaining channels according to the cost selection interval, and resend the message using the target channel and the communication platform can determine candidate channels that satisfy the cost selection interval from the remaining channels, then randomly select one from the candidate channels as the target channel, and use the target channel to resend the message)
Yan discloses what Cao does not expressly disclose.
Yan discloses:
based on the respective message allocation weights of the plurality of message channels, wherein a verification code message is sent via an allocated message channel (¶0007 – Yan teaches purpose of the present invention is to provide an optimal route selection method based on routing cost, by weighting the cost factors of all routing nodes on the message forwarding path and adding them together).
Cao and Yan are analogous arts because they are from the same field of endeavor with respect to network routing.
Before the effective filing date, it would have been obvious to a person of ordinary skill in the art to incorporate routing weights as discussed in Yan with a system of message channel allocation as discussed in Cao by adding the functionality of Yan to the system/method of Cao in order to provide an optimal route selection method based on routing cost, by weighting the cost factors of all routing nodes on the message forwarding path (Yan, ¶0007).
As to claim 2, Cao and Yan discloses:
method of claim 1, and
Cao discloses:
wherein determining the respective message allocation weights of the plurality of message channels comprises:
determining, in response to at least one constraint condition being satisfied, the respective message allocation weights of the plurality of message channels according to the message allocation objective, wherein the at least one constraint condition is determined (¶0067 – Cao teaches The number of times the message is sent determines the upper limit of the cost selection interval, and the upper limit of the cost selection interval is positively correlated with the number of times of sending.) based on at least one of the following:
the respective verification pass rates of the plurality of message channels, or
the respective unit costs of the plurality of message channels (¶0067 – Cao teaches The number of times the message is sent determines the upper limit of the cost selection interval, and the upper limit of the cost selection interval is positively correlated with the number of times of sending.).
As to claim 4, Cao and Yan discloses:
method of claim 1, and
Cao discloses:
wherein obtaining the respective verification pass rates of the plurality of message channels comprises:
for a first message channel of the plurality of message channels,
obtaining a first number of verification code messages sent via the first message channel within a first time range, and a second number of verification code messages determined to be passed among the first number of verification code messages; and
determining a verification pass rate of the first message channel based on a ratio of the second number to the first number.
(¶0016-¶0019 – Cao teaches using a prediction model to help determine success rates (i.e., verification pass rates) and the prediction is built using historical messages and their sending results)
As to claim 5, Cao and Yan discloses:
method of claim 1, and
Cao discloses:
wherein obtaining the respective verification pass rates of the plurality of message channels comprises:
for a second message channel of the plurality of message channels,
obtaining a first number of verification code messages sent via the second message channel within a first time range;
obtaining, in response to the first number reaching a threshold transmission number, a second number of verification code messages determined to be passed in the first number of verification code messages; and
determining a verification pass rate of the second message channel based on a ratio of the second number to the first number.
(¶0016-¶0019 – Cao teaches using a prediction model to help determine success rates (i.e., verification pass rates) and the prediction is built using historical messages and their sending results)
As to claim 6, Cao and Yan discloses:
method of claim 5, and
Cao discloses:
wherein obtaining the respective verification pass rates of the plurality of message channels further comprises:
obtaining, in response to the first number not reaching the threshold transmission number, a third number of verification code messages sent via the second message channel within a second time range, and a fourth number of verification code messages determined to be passed in the third number of verification code messages, the second time range being greater than the first time range; and
determining the verification pass rate of the second message channel based on a ratio of the fourth number to the third number.
(¶0061-¶0063 – Cao teaches a message is resent using the target channel. A cost-progressive approach is used to achieve a balance between cost and quality. In the process of multiple retries of a message, the cost is gradually increased to increase the success rate of sending the message. For a message sent for the first time, the communication platform may select the lowest-cost target channel from all channels and use the target channel to send the message. This embodiment allows low-quality but low-price channel resources to be fully utilized, and then in the case of subsequent transmission failure, the cost is gradually increased to increase the range of channel options, and the message transmission is maximized while ensuring the cost. Success rate of getting out.)
As to claim 7, Cao and Yan discloses:
method of claim 1, and
Cao discloses:
wherein the message allocation objective is configured to at least one of the following:
minimize or decrease the total cost of the message transmissions of the plurality of message channels to satisfy a first target value, or
maximize or increase a ratio of an average verification pass rate of the message transmissions of the plurality of message channels to the total cost to satisfy a second target value,
wherein the total cost of the message transmissions of the plurality of message channels is determined based on the respective message allocation weights and the respective unit costs of the plurality of message channels, and wherein the average verification pass rate is determined based on the respective message allocation weights and the respective verification pass rates of the plurality of message channels.
(¶0063 – Cao teaches This embodiment allows low-quality but low-price channel resources to be fully utilized, and then in the case of subsequent transmission failure, the cost is gradually increased to increase the range of channel options, and the message transmission is maximized while ensuring the cost. Success rate of getting out.)
As to claim 9, Cao and Yan discloses:
method of claim 1, and
Cao discloses:
wherein the respective message allocation weights of the plurality of message channels is valid for a period of time, and wherein allocating verification code messages to the plurality of message channels comprises:
allocating, in response to receiving transmission requests for the verification code messages within the period of time, the verification code messages to the plurality of message channels based on the respective message allocation weights valid for the period of time.
(¶0073 – Cao teaches combines cost progression and quality prediction methods to gradually reduce the weight of cost in the scheduling process and gradually increase the weight of quality in the scheduling process during the process of multiple retries of the same message, thereby making low quality but low price)
As to claim 10, similar rejection as to claim 1.
As to claim 11, similar rejection as to claim 2.
As to claim 13, similar rejection as to claim 4.
As to claim 14, similar rejection as to claim 5.
As to claim 15, similar rejection as to claim 6.
As to claim 16, similar rejection as to claim 7.
As to claim 18, similar rejection as to claim 9.
As to claim 19, similar rejection as to claim 1.
As to claim 20, similar rejection as to claim 2.
Claims 3 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Chinese Application No. CN 116684377 A to Cao et al. (“Cao”) in view of Chinese Application No. CN 11921203 A to Yan et al. (“Yan”) in further view of Chinese Application No. CN 119922499 A to Hong et al. (“Hong”).
As to claim 3, Cao and Yan discloses:
method of claim 1,
Hong discloses what Cao and Yan do not expressly disclose.
Hong discloses:
wherein determining the respective message allocation weights of the plurality of message channels comprises:
determining, in response to at least one constraint condition being satisfied, the respective message allocation weights of the plurality of message channels according to the message allocation (¶0076-¶0078 – Hong teaches an adjustment range of the channel weight value is set according to the degree of deviation of the corresponding indicator from the threshold value. Specifically, the calculation formula of the adjustment range of the channel weight value is as follows: Adjustment range = (current indicator value - preset threshold) × (cost-effectiveness / cost-effectiveness threshold) × adjustment coefficient. The adjustment coefficient is a constant, which is set according to the test requirements and is used to dynamically adjust the corresponding adjustment range.), wherein the at least one constraint condition comprises at least one of the following:
a first constraint condition indicating that a message allocation weight of a message channel is within a specified range;
a second constraint condition indicating that a total message allocation weight of the plurality of message channels satisfies a predetermined value;
a third constraint condition indicating that an average verification pass rate of the plurality of message channels reaches a threshold verification pass rate; or
a fourth constraint condition indicating that the total cost of the message transmissions of the plurality of message channels is lower than a threshold cost.
(¶0076-¶0078 – Hong teaches an adjustment range of the channel weight value is set according to the degree of deviation of the corresponding indicator from the threshold value. Specifically, the calculation formula of the adjustment range of the channel weight value is as follows: Adjustment range = (current indicator value - preset threshold) × (cost-effectiveness / cost-effectiveness threshold) × adjustment coefficient. The adjustment coefficient is a constant, which is set according to the test requirements and is used to dynamically adjust the corresponding adjustment range.)
Cao, Yan and Hong are analogous arts because they are from the same field of endeavor with respect to network weighting.
Before the effective filing date, it would have been obvious to a person of ordinary skill in the art to incorporate network channel weighting as discussed in Hong with routing weights as discussed in Yan with a a system of message channel allocation as discussed in Cao by adding the functionality of Hong to the system/method of Cao and Yan in order to adjustment range of the channel weight value (Hong, ¶0076).
As to claim 12, similar rejection as to claim 3.
Claims 8 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Chinese Application No. CN 116684377 A to Cao et al. (“Cao”) in view of Chinese Application No. CN 11921203 A to Yan et al. (“Yan”) in further view of U.S. Patent Application Publication No. 2025/0299219 A1 to Rashidian et al. (“Rashidian”).
As to claim 8, Cao and Yan discloses:
method of claim 1,
Rashidian discloses what Cao and Yan do not expressly disclose.
Rashidian discloses:
wherein the message allocation objective is represented as an objective function associated with at least the respective message allocation weights of the plurality of message channels, and wherein determining the respective message allocation weights of the plurality of message channels based on the message allocation objective comprises:
determining, based on at least the respective verification pass rates and the respective unit costs of the plurality of message channels, the respective message allocation weights of the plurality of message channels by solving the objective function with a convex optimization algorithm.
(Abstract – Rashidian teaches the multiple resource distribution parameters for the connection model in a subsequent period can be learned and updated using an online reinforcement learning algorithm. The computing device determines optimized resource allocations for the predetermined number of communication channels in the subsequent period based on the connection model and the current connection data using one or more convex optimization algorithms.)
Cao, Yan and Rashidian are analogous arts because they are from the same field of endeavor with respect to network communication.
Before the effective filing date, it would have been obvious to a person of ordinary skill in the art to incorporate convex optimization algorithms as discussed in Rashidian with routing weights as discussed in Yan with a a system of message channel allocation as discussed in Cao by adding the functionality of Hong to the system/method of Cao and Yan in order to determine optimized resource allocations for different digital communication channels by minimizing connection cost (Rashidian, ¶0029).
As to claim 17, similar rejection as to claim 8.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to TAYLOR A ELFERVIG whose telephone number is (571)270-5687. The examiner can normally be reached Monday (10:00 AM CST) - Friday (4:00 PM CST).
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/TAYLOR A ELFERVIG/Primary Examiner, Art Unit 2445
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