DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This action is in reply to the communications filed on May 26, 2026. The Applicant’s Amendment and Request for Reconsideration has been received and entered.
Claims 1-20 are currently pending and have been examined. Claims 1, 4, 5, 12, 14, and 19 have been amended.
Response to Arguments
Applicant’s amendments necessitated the new grounds of rejection.
Regarding the rejection of claims 1-20 under 35 USC 101, Applicant’s arguments have been fully considered but they are not persuasive for the reasons set forth infra.
Applicant’s remaining arguments have been fully considered but they are not persuasive. Particularly, Applicant’s arguments are directed to the instantly amended claims, and are thus moot in view of the new grounds of rejection.
Claim Interpretation Note
Claim 1 recites the limitation “in response to receiving a first content request associated with a first content delivery opportunity, generating a first bid request indicative of a first bid floor;” (emphasis added). However, the claims do not positively recite receiving a first content request associated with a first content delivery opportunity. Accordingly, this “in response to” limitation is merely conditional and not necessarily performed.
Further, claim 1 recites the limitation “in response to receiving a second content request associated with a second content delivery opportunity, generating a second bid request indicative of a second bid floor different than the first bid floor” (emphasis added). However, the claims do not positively recite receiving a second content request associated with a second content delivery opportunity. Accordingly, this “in response to” limitation is merely conditional and not necessarily performed.
Claims 2-13 depend from claim 1 and thus inherit the interpretation of claim 1.
Given the conditional nature of the claim language noted above, such language has been afforded appropriate patentable weight during examination.
Claim 3 recites the limitation “determining the third bid floor comprises setting the third bid floor to the first bid floor value in response to determining that a set of features associated with the third content request matches the first set of features” (emphasis added). However, the claims do not positively recite determining that a set of features associated with the third content request matches the first set of features. Accordingly, this “in response to” limitation is merely conditional and not necessarily performed.
Given the conditional nature of the claim language noted above, such language has been afforded appropriate patentable weight during examination.
Claim 10 recites the limitation “in response to receiving the first content request associated with the first content delivery opportunity, generating a third bid request indicative of a third bid floor” (emphasis added). However, the claims do not positively recite receiving the first content request associated with the first content delivery opportunity. Accordingly, this “in response to” limitation is merely conditional and not necessarily performed.
Further, claim 10 recites the limitation “in response to receiving the second content request associated with the second content delivery opportunity, generating a fourth bid request indicative of a fourth bid floor” (emphasis added). However, the claims do not positively recite receiving the second content request associated with the second content delivery opportunity. Accordingly, this “in response to” limitation is merely conditional and not necessarily performed.
Claims 2-13 depend from claim 1 and thus inherit the interpretation of claim 1.
Given the conditional nature of the claim language noted above, such language has been afforded appropriate patentable weight during examination.
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.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
Step 1. When considering subject matter eligibility under 35 U.S.C. 101, it must be determined whether the claim is directed to one of the four statutory categories of invention, i.e., process, machine, manufacture, or composition of matter.
Step 2A – Prong One. If the claims fall within one of the statutory categories, it must then be determined whether the claims recite an abstract idea, law of nature, or natural phenomenon.
Step 2A – Prong Two. If the claims recite an abstract idea, law of nature, or natural phenomenon, it must then be determined whether the claims recite additional elements that integrate the judicial exception into a practical application. If the claims do not recite additional elements that integrate the judicial exception into a practical application, then the claims are directed to a judicial exception.
Step 2B. If the claims are directed to a judicial exception, it must be evaluated whether the claims recite additional elements that amount to an inventive concept (i.e. “significantly more”) than the recited judicial exception.
In the instant case, claims 1-13 are directed to a process; claims 14-18 are directed to a manufacture; and claims 19 and 20 are directed to a machine.
A claim “recites” an abstract idea if there are identifiable limitations that fall within at least one of the groupings of abstract ideas enumerated in MPEP 2106. In the instant case, claim 1, and similarly claims 14 and 19, recites the steps of:
in response to receiving a first content request associated with a first content delivery opportunity, generating a first bid request indicative of a first bid floor; transmitting the first bid request to a first bidder; receiving, from the first bidder, a first bid response responsive to the first bid request, wherein the first bid response is indicative of a first bid for submission to a first auction associated with the first content delivery opportunity; determining a first result of the first auction; in response to receiving a second content request associated with a second content delivery opportunity, generating a second bid request indicative of a second bid floor different than the first bid floor; transmitting the second bid request to the first bidder; receiving, from the first bidder, a second bid response responsive to the second bid request, wherein the second bid response is indicative of a second bid for submission to a second auction associated with the second content delivery opportunity; assigning a first subset of content delivery opportunities to a training bucket and a second subset of content delivery opportunities to a production bucket; for content delivery opportunities assigned to the training bucket: generating bid requests comprising bid floors that are randomly generated according to a predefined distribution; transmitting the bid requests comprising the randomly generated bid floors to the first bidder; and receiving bid responses from the first bidder responsive to the randomly generated bid floors; determining a first bidder profile associated with the first bidder based upon (i) a plurality of bid floors comprising the first bid floor, the second bid floor and the randomly generated bid floors and (ii) at least one of corresponding bid responses or corresponding auction results associated with the plurality of bid floors, wherein the first bidder profile characterizes a relationship between bid floor values and bid behavior of the first bidder; and for content delivery opportunities assigned to the production bucket, determining a bid floor to be included in a subsequent bid request transmitted to the first bidder based upon the first bidder profile -- these claim limitations set forth certain methods of organizing human activity, particularly commercial interactions including advertising, marketing, and sales activities/behaviors.
Further, the limitations of the claims are not indicative of integration into a practical application. Taking the independent claim elements separately, the additional elements of performing the steps via a processor and memory comprising processor-executable instructions that when executed by the processor cause performance of operations -- merely implement the abstract idea on a computer environment. Considered in combination, the steps of Applicant’s method add nothing that is not already present when the steps are considered separately.
The remaining claim limitations recited in dependent claims merely narrow the abstract idea and do not recite further additional elements. Thus, claims 1-20 are directed to an abstract idea.
Regarding the independent claims, the technical elements of performing the steps via a processor and memory comprising processor-executable instructions that when executed by the processor cause performance of operations merely implement the abstract idea on a computer environment. Additionally, the dependent claims do not recite further technical elements.
When considering the elements and combinations of elements, the claim(s) as a whole, do not amount to significantly more than the abstract idea itself. This is because the claims do not amount to an improvement to another technology or technical field; the claims do not amount to an improvement to the functioning of a computer itself; the claims do not move beyond a general link of the use of an abstract idea to a particular technological environment; the claims merely amounts to the application or instructions to apply the abstract idea on a computer; or the claims amounts to nothing more than requiring a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known to the industry.
The analysis above applies to all statutory categories of invention. Accordingly, claims 1-20 are rejected as ineligible for patenting under 35 USC 101 based upon the same rationale.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
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 of this title, 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 to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Guermas (US PGP 2017/0330245) in view of Newnham (US PGP 2022/0374944).
As per claim 1, Guermas teaches [a] method, comprising:
in response to receiving a first content request associated with a first content delivery opportunity, generating a first bid request indicative of a first bid floor; (Guermas: [0028]-[0031] (Beginning with step 502, in the context of delivering webpage content, when a user visits a webpage hosted, for example, by CDS 10, the user device 200 sends a corresponding webpage request to the CDS 10. In response to receiving the webpage request, in step 504, the webpage code (e.g., HTML, JavaScript or the like) makes an ad call to fill an impression associated with the requested webpage. . . . In step 508, the advertising management platform 100 performs auction optimization—namely, determining whether an auction should be held and, if so, which of the potential impression provider systems 300 will be permitted to participate in the auction for the impression and thus receive a bid request.); [0044]-[0048] (In step 514, once the platform 100 determines which provider systems 300 will receive bid requests, it then performs pricing optimization—namely, determining the floor or reserve price for each of such competitive bidders 300.))
transmitting the first bid request to a first bidder; (Guermas: [0048]-[0049] (Once the floor estimation engine 110 and the targeting engine 130 have completed running their respective models 112, 132 for each of the potential impression providers 300, in step 516, the platform 100 generates and issues the bid requests to the subset of selected bidders 300.))
receiving, from the first bidder, a first bid response responsive to the first bid request, wherein the first bid response is indicative of a first bid for submission to a first auction associated with the first content delivery opportunity; (Guermas: [0048]-[0049] (The bid responses preferably include a price as well as information regarding the ad (creative), and are preferably compatible with the Open RTB 2.3 specification, as set forth at www.iab.com/guidlines/real-time-bidding-rtb-project (as may be updated or replaced). Bid requests may also include bidder-specific extensions, such as “recommended price,” the recommended price to win the impression, or “screen resolution.” The extensions can allow for custom parameters that the seller wants to send to the buyer to improve efficiency. In generating the bid responses, the participant bidders 300 may utilize their own or third party data sources 400, which may provide further information on the user/user device 200 and/or impression.); [0008] (Bid responses are received from at least a portion of the subset of potential impression providers in response to the bid requests ); [0063])
determining a first result of the first auction; (Guermas: [0051] (In step 522, the bidding engine of advertising management platform 100 reviews the tendered bids and determines the “winning” bid. Such determination may be based on the highest price bid, subject to ad quality or other rules manually established by the publisher and effected by the platform 100, such as whether the user device 200 permits or is compatible with the type of media contained in the ad proposed to be served by the bid.))
in response to receiving a second content request associated with a second content delivery opportunity, generating a second bid request indicative of a second bid floor different than the first bid floor; (Guermas: [0028]-[0031] (Beginning with step 502, in the context of delivering webpage content, when a user visits a webpage hosted, for example, by CDS 10, the user device 200 sends a corresponding webpage request to the CDS 10. In response to receiving the webpage request, in step 504, the webpage code (e.g., HTML, JavaScript or the like) makes an ad call to fill an impression associated with the requested webpage. . . . In step 508, the advertising management platform 100 performs auction optimization—namely, determining whether an auction should be held and, if so, which of the potential impression provider systems 300 will be permitted to participate in the auction for the impression and thus receive a bid request.); [0044]-[0048] (In step 514, once the platform 100 determines which provider systems 300 will receive bid requests, it then performs pricing optimization—namely, determining the floor or reserve price for each of such competitive bidders 300.); [0052] (In an optional step 523, the system 100 may cause the winning bid from step 522 to be submitted as a floor or reserve in a secondary auction, thereby allowing various bidders a “last look” to decide if they want the impression at a higher price. Such a secondary auction may include, for example, all or some of the same bidders and/or allow new bidders. For example, the initial ad call may indicate that a secondary auction should be performed. Or, the web page content may include instructions causing the browser of the user device 200 to initiate the secondary auction.); [0083] (auctions are performed in parallel. Hence, although the above loops are described as being serial in their execution, in practice these loops can be “unwound” to execute asynchronously); Fig. 6; [0077] (iterative process))
transmitting the second bid request to the first bidder; (Guermas: [0048] (Once the floor estimation engine 110 and the targeting engine 130 have completed running their respective models 112, 132 for each of the potential impression providers 300, in step 516, the platform 100 generates and issues the bid requests to the subset of selected bidders 300.); [0052]; [0083]; Fig. 6; [0077])
receiving, from the first bidder, a second bid response responsive to the second bid request, wherein the second bid response is indicative of a second bid for submission to a second auction associated with the second content delivery opportunity; (Guermas: [0048]-[0049] (The bid responses preferably include a price as well as information regarding the ad (creative), and are preferably compatible with the Open RTB 2.3 specification, as set forth at www.iab.com/guidlines/real-time-bidding-rtb-project (as may be updated or replaced). Bid requests may also include bidder-specific extensions, such as “recommended price,” the recommended price to win the impression, or “screen resolution.” The extensions can allow for custom parameters that the seller wants to send to the buyer to improve efficiency. In generating the bid responses, the participant bidders 300 may utilize their own or third party data sources 400, which may provide further information on the user/user device 200 and/or impression.); [0008] (Bid responses are received from at least a portion of the subset of potential impression providers in response to the bid requests ); [0063]; [0050]-[0052]; [0083]; Fig. 6; [0077])
determining a second result of the second auction; and (Guermas: [0051] (In step 522, the bidding engine of advertising management platform 100 reviews the tendered bids and determines the “winning” bid. Such determination may be based on the highest price bid, subject to ad quality or other rules manually established by the publisher and effected by the platform 100, such as whether the user device 200 permits or is compatible with the type of media contained in the ad proposed to be served by the bid.); [0052]; [0083]; Fig. 6; [0077])
assigning a first subset of content delivery opportunities to a training bucket and a second subset of content delivery opportunities to a production bucket; (Guermas: [0038] (For training purposes, a random percentage of the impressions, such as 15%-25%, more preferably 20%, may be selected in which all potential bidders 300 are allowed to participate in the auction for the impression, and the corresponding bidding data collected from these selected impressions can later be used to train behavior models 132. Subsequently, the behavior models 132 can then be applied to the remaining percentage of impressions (e.g., 80%) to select only those potential impression providers 300 that are most likely to submit a bid.))
determining a first bidder profile associated with the first bidder based upon (i) a plurality of bid floors comprising the first bid floor, the second bid floor and . . . and (ii) at least one of corresponding bid responses or corresponding auction results associated with the plurality of bid floors, wherein the first bidder profile characterizes a relationship between bid floor values and bid behavior of the first bidder; and (Guermas: [0048]-[0051] (For example, with specific reference to FIG. 3, the advertising management platform 100 has determined, based upon the behavior model(s) 132, that four advertising network agencies 302, “AdNetwork A” to “AdNetwork D” are likely to submit the highest bids for the impression, and thus proffers respective bid requests to each of these agencies 302. Further, the floor estimation engine 110 has computed respective floor prices (or reserve prices, if an impression provider 300 is a second auction bidder) for each agency 302, with the highest floor being set for “AdNetwork A” at $1.00, and the lowest floor being set for “AdNetwork D” at $0.75. Turning back to FIG. 2, the bidding engine 140 of platform 100 uses the bid responses (in step 520) to update the profile database 120, thus providing a learning or feedback loop, for the platform 100. Hence, when running, the models 112, 132 effected as part of the floor estimation engine 110 and targeting engine 130, respectively, are able to make use of the most recent and up-to-date information available concerning each potential impression provider system 300, thereby avoiding the need to manually update floor and reserve prices.); [0032] (To facilitate bidder 300 determination in step 508, the platform 100 preferably includes a profile database 120 and a targeting engine 130. The targeting engine 130 can be provided by, for example, program code configured to provide the methods and functions discussed herein. The profile database 120 stores information about each of the potential impression provider systems 300, including, for example, past bidding history. For purposes of the discussion herein, it is assumed that profile database 120 also stores information about user devices 200. It will be appreciated, however, that more than one database may be used to store this information. Bidding history can include, for example, all information about each impression, user and user device 200 associated with the impression, the impression information (including information about the content (e.g., web page)), and all information about the bidding landscape, such as the number of bidders, the respective bid amounts (and associated metrics that can be calculated therefrom), the winning bid, the amount and timing of the bid responses and from who received, etc. In addition, the profile database 120 can store information about the user and user device 200 associated with each impression, which can be aggregated with the impression information to provide additional information or features about the user and user device 200 and to assist in selecting potential impression providers 300 for bidding.); [0036]-[0038] (The behavior model 132 can be trained at predetermined intervals, such as once every day, using the most recently obtained data, which may be stored in profile database 120, since the last training session to cause the behavior model 132 to predict the related bidding behavior of potential bidder 300, such as highest bid. The behavior model 132 can be fine-tuned to minimize the error in doing such a prediction, and can thereafter be applied to all following impressions, with the behavior model 132 predicting the possible highest bid on any given impression based on, for example, its features and data from the previous impressions to determine an expected bid amount); [0065]; [0068];[0074]; [0078] (Simultaneously, in step 626, impression logger 170, which can run asynchronously, extracts feedback from each of the auctions performed in the above steps to update the profile database 120. This feedback can include, for example, the data for each user device 200. Impression and auction information can be written to a data store, such as profile database 120, and associated together by a unique identifier assigned to each of the records. In this manner, each of the models 112, 132 is also updated, and, in the context of machine learning-based models 112, 132, helps the models 112, 132 to improve with time as more and more data is accumulated in profile database 120.))
for content delivery opportunities assigned to the production bucket, determining a bid floor to be included in a subsequent bid request transmitted to the first bidder based upon the first bidder profile. (Guermas: [0038] (For training purposes, a random percentage of the impressions, such as 15%-25%, more preferably 20%, may be selected in which all potential bidders 300 are allowed to participate in the auction for the impression, and the corresponding bidding data collected from these selected impressions can later be used to train behavior models 132. Subsequently, the behavior models 132 can then be applied to the remaining percentage of impressions (e.g., 80%) to select only those potential impression providers 300 that are most likely to submit a bid.); [0044]-[0046] (In step 514, once the platform 100 determines which provider systems 300 will receive bid requests, it then performs pricing optimization—namely, determining the floor or reserve price for each of such competitive bidders 300. The platform 100 includes a floor estimation engine 110, which may be implemented as a module in platform 100. The floor estimation engine 110 can use, for example, a machine learning floor model 112 that is trained on past impressions to determine the floor price of new impressions of “similar” features.); [0050])
Guermas does not explicitly disclose the following known technique which is taught by Newnham:
for content delivery opportunities assigned to the training bucket: (Newnham: [0040] (The exploration controller 125 is further configured randomly to assign the advertising request 122 received by the exploration controller 125 into one of three advertising request groups, 1) an exploration group comprising exploration advertising requests, the exploration group usable by the exploration controller 125 to gather a useful set of training data regarding the advertising requests; . . . ); [0043]; [0062]-[0064])
generating bid requests comprising bid floors that are randomly generated according to a predefined distribution; (Newnham: Fig. 2; [0046] (If the advertising request 122 was assigned by the exploration controller 125 to the exploration group, the bid parameter controller 130 applies to the advertising request 122 a range of candidate exploration group bid floors, the bid floor range centered on the optimized bid floor, to explore an outcome of different candidate exploration group bid floors within the bid floor range and thereby to identify the optimized bid floor. Similarly, for the advertising request 122 that was assigned by the exploration controller 125 to the exploration group, the bid parameter controller 130 applies to the advertising request 122 a range of candidate exploration group shading factors, the shading factor range centered on the optimized shading factor, to explore an outcome of different candidate exploration group shading factors within the shading factor range and thereby to identify the optimized shading factor. For example, the bid parameter controller 130 comprises a random number generator that the bid parameter controller 130 uses to select one or more of the candidate exploration group bid floors within the bid floor range, and the candidate exploration group shading factors within the shading factor range. The outcome comprises one or more of an SSP auction result and hybrid, optimized profit that the hybrid, optimized exchange realizes in the winning SSP auction. Preferably, the outcome comprises both the SSP auction result and the hybrid, optimized profit. For example, if the optimized bid floor equals five dollars, the bid floor range comprises four dollars to six dollars. This means that the range of possible bid floors comprises four dollars to six dollars.); [0071]-[0073] (For example, the hybrid, optimized exchange, using the bid parameter controller, uses a random number generator comprised in the bid parameter controller to select one or more of the candidate exploration group bid floors within the bid floor range and the candidate exploration group shading factors within the shading factor range. For example, the bid parameter controller, using the random number generator, calculates the exploration group bid floor as equal to (a random number between 0.5 and 2.0)*(the exploitation group bid floor). For example, the bid parameter controller, using the random number generator calculates the exploration group shading factor as equal to (a random number between 0.5 and 2.0)*(the exploitation group shading factor))
transmitting the bid requests comprising the randomly generated bid floors to the first bidder; and (Newnham: [0018] (The hybrid, optimized exchange provides a curated set of advertising requests that are likely to be relevant to the respective DSPs to whom the advertising requests are provided. The hybrid, optimized exchange forwards the advertising requests to the DSPs.); [0039]; [0071]-[0073] (In step 267, the hybrid, optimized exchange, if the advertising request was assigned to the exploration group, using the bid parameter controller, and using the optimized values for the bid parameters, does one or more of applying to the advertising request a range of candidate exploration group bid floors, the bid floor range centered on the optimized bid floor, to explore an outcome of different candidate exploration group bid floors within the bid floor range and thereby to identify the optimized bid floor, and applying to the advertising request a range of candidate exploration group shading factors, the shading factor range centered on the optimized shading factor, to explore an outcome of different candidate exploration group shading factors within the shading factor range and thereby to identify the optimized shading factor. . . . For example, the hybrid, optimized exchange, using the bid parameter controller, uses a random number generator comprised in the bid parameter controller to select one or more of the candidate exploration group bid floors within the bid floor range and the candidate exploration group shading factors within the shading factor range. For example, the bid parameter controller, using the random number generator, calculates the exploration group bid floor as equal to (a random number between 0.5 and 2.0)*(the exploitation group bid floor). For example, the bid parameter controller, using the random number generator calculates the exploration group shading factor as equal to (a random number between 0.5 and 2.0)*(the exploitation group shading factor).))
receiving bid responses from the first bidder responsive to the randomly generated bid floors; (Newnham: [0021]-[0025] (The bid floor and the shading factor comprise two parameters that the hybrid, optimized exchange uses in determining a hybrid, optimized bid to place on behalf of the DSP to the SSP. Each of the upstream DSPs can bid in real-time on an advertisement placement being auctioned by the hybrid, optimized exchange. . . . The bid floor comprises a minimum bid that a DSP can make in the hybrid, optimized auction.); [0039]; [0076]-[0077])
. . . the randomly generated bid floors and . . . characterizes a relationship between bid floor values and bid behavior of the first bidder; and (Newnham: [0049]-[0057] (For at least one advertising request 122, the hybrid, optimized exchange logs advertising request data 155 to the database 145. The advertising request data 155 comprises one or more of request data, the bid floor, the shading factor, the assigned advertising request group, and whether the advertising request 122 resulted in a winning SSP bid and thus in an advertisement placement on the end user's device. The hybrid, optimized exchange 105 further comprises a learning engine 160, the learning engine 160 operably connected to the database 145. The advertising request data 155 becomes the training data for the learning engine 160. . . . For example, the hybrid, optimized exchange calculates the optimized bid floor and the optimized shading factor for a given subset of advertising requests . . .); [0074]-[0078] (In step 269, the hybrid, optimized exchange, using the bid parameter controller, if the advertising request was assigned to the exploration group, stores one or more of the exploration group advertising request, the exploration group bid floor and the exploration group shading factor. . . . In step 272, the hybrid, optimized exchange, using the exchange controller, stores one or more of the winning DSP bid and the winning DSP.); [0020]-[0022] (The hybrid, optimized exchange determines the hybrid, optimized bid that the hybrid, optimized exchange places in the SSP auction by dividing a winning DSP bid in the hybrid, optimized DSP auction by the shading factor. The hybrid, optimized bid maximizes profit that the hybrid, optimized exchange realizes in a winning SSP auction. In order to learn one or more of the bid floor and the shading factor in a dual censored environment, the hybrid, optimized exchange takes into account the DSPs' distribution of bids on the hybrid, optimized exchange as well as feedback from the downstream SSP on winning bids in past auctions.); [0032]-[0034]; [0036]-[0038])
This known technique is applicable to the method of Guermas as they both share characteristics and capabilities, namely, they are directed to bidding in auctions.
One of ordinary skill in the art at the time of filing would have recognized that applying the known technique of Newnham would have yielded predictable results and resulted in an improved method. It would have been recognized that applying the technique of Newnham to the teachings of Guermas would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such randomly generated bid floors features into similar methods. Further, applying the for content delivery opportunities assigned to the training bucket: generating bid requests comprising bid floors that are randomly generated according to a predefined distribution; transmitting the bid requests comprising the randomly generated bid floors to the first bidder; and receiving bid responses from the first bidder responsive to the randomly generated bid floors; a plurality of bid floors comprising the randomly generated bid floors, and characterizing a relationship between bid floor values and bid behavior of the first bidder to the teachings of Guermas would have been recognized by those of ordinary skill in the art as resulting in an improved method that would allow optimizing a bid floor (Newnham: Para [0002]-[0006).
As per claim 2, Guermas/Newnham teach comprising:
receiving a third content request associated with a third content delivery opportunity; Guermas: [0028]-[0031] (Beginning with step 502, in the context of delivering webpage content, when a user visits a webpage hosted, for example, by CDS 10, the user device 200 sends a corresponding webpage request to the CDS 10. In response to receiving the webpage request, in step 504, the webpage code (e.g., HTML, JavaScript or the like) makes an ad call to fill an impression associated with the requested webpage. . . . In step 508, the advertising management platform 100 performs auction optimization—namely, determining whether an auction should be held and, if so, which of the potential impression provider systems 300 will be permitted to participate in the auction for the impression and thus receive a bid request.); [0044]-[0048]; [0083] (auctions are performed in parallel. Hence, although the above loops are described as being serial in their execution, in practice these loops can be “unwound” to execute asynchronously); Fig. 6; [0077] (iterative process))
determining a third bid floor, different than at least one of the first bid floor or the second bid floor, based upon the first bidder profile; and (Guermas: [0044]-[0048] (In step 514, once the platform 100 determines which provider systems 300 will receive bid requests, it then performs pricing optimization—namely, determining the floor or reserve price for each of such competitive bidders 300.); [0052] (In an optional step 523, the system 100 may cause the winning bid from step 522 to be submitted as a floor or reserve in a secondary auction, thereby allowing various bidders a “last look” to decide if they want the impression at a higher price. Such a secondary auction may include, for example, all or some of the same bidders and/or allow new bidders. For example, the initial ad call may indicate that a secondary auction should be performed. Or, the web page content may include instructions causing the browser of the user device 200 to initiate the secondary auction.); [0048]-[0051] (For example, with specific reference to FIG. 3, the advertising management platform 100 has determined, based upon the behavior model(s) 132, that four advertising network agencies 302, “AdNetwork A” to “AdNetwork D” are likely to submit the highest bids for the impression, and thus proffers respective bid requests to each of these agencies 302. Further, the floor estimation engine 110 has computed respective floor prices (or reserve prices, if an impression provider 300 is a second auction bidder) for each agency 302, with the highest floor being set for “AdNetwork A” at $1.00, and the lowest floor being set for “AdNetwork D” at $0.75. Turning back to FIG. 2, the bidding engine 140 of platform 100 uses the bid responses (in step 520) to update the profile database 120, thus providing a learning or feedback loop, for the platform 100. Hence, when running, the models 112, 132 effected as part of the floor estimation engine 110 and targeting engine 130, respectively, are able to make use of the most recent and up-to-date information available concerning each potential impression provider system 300, thereby avoiding the need to manually update floor and reserve prices.); [0032]; [0083] (auctions are performed in parallel. Hence, although the above loops are described as being serial in their execution, in practice these loops can be “unwound” to execute asynchronously); Fig. 6; [0077] (iterative process))
transmitting a third bid request, indicative of the third bid floor, to the first bidder. (Guermas: [0048]-[0049] (Once the floor estimation engine 110 and the targeting engine 130 have completed running their respective models 112, 132 for each of the potential impression providers 300, in step 516, the platform 100 generates and issues the bid requests to the subset of selected bidders 300.))
As per claim 3, Guermas/Newnham teach wherein:
the first bidder profile comprises:
a first bid floor value associated with a first set of features; and (Guermas: [0044]-[0049])
a second bid floor value associated with a second set of features; and (Guermas: [0044]-[0049])
determining the third bid floor comprises setting the third bid floor to the first bid floor value in response to determining that a set of features associated with the third content request matches the first set of features. (Guermas: [0044]-[0049])
As per claim 4, Guermas/Newnham teach comprising:
receiving content requests associated with a plurality of content delivery opportunities; (Guermas: [0028]-[0031]; Fig. 6; [0071])
for each content delivery opportunity of the first subset assigned to the training bucket:
accessing a bid floor training profile different than the first bidder profile; (Guermas: [0048]-[0051]; [0032]; [0065]; [0068]; [0074])
determining a bid floor based upon the bid floor training profile, . . . (Guermas: [0048]-[0051]; [0032]; [0065]; [0068]; [0074])
transmitting a bid request, to the first bidder, indicative of the bid floor; (Guermas: [0048]-[0049])
receiving, from the first bidder, a bid response responsive to the bid request; and (Guermas: [0048]-[0049]; [0008]; [0063])
determining a result of the auction. (Guermas: [0051])
Guermas/Newnham further teach
. . . wherein determining the bid floor comprises generating the bid floor as a random value according to a predefined distribution; (Newnham: [0071]-[0073])
The motivation for applying the known techniques of Newnham to the teachings of Guermas is the same as that set forth above, in the rejection of Claim 1.
As per claim 5, Guermas/Newnham teach wherein:
assigning the first subset to the training bucket is performed according a first predefined share, of the plurality of content delivery opportunities, to assign to the training bucket; and (Guermas: Fig. 6; [0071]-[0080])
assigning the second subset to the production bucket is performed according a second predefined share, of the plurality of content delivery opportunities, to assign to the production bucket. (Guermas: Fig. 6; [0071]-[0080])
As per claim 6, Guermas/Newnham teach wherein:
determining the third bid floor based upon the first bidder profile is performed in response to the third content delivery opportunity being assigned to the production bucket. (Guermas: Fig. 6; [0071]-[0080]; [0044]-[0049])
As per claim 7, Guermas/Newnham teach wherein:
determining the bid floor based upon the bid floor training profile comprises generating a random value within a predefined range using a floor randomization function of the bid floor training profile. (Guermas: Fig. 6; [0071]-[0080]; [0044]-[0049])
As per claim 8, Guermas/Newnham teach comprising:
determining a second bidder profile associated with the first bidder based upon:
bid floors determined based upon the bid floor training profile for the second subset of content delivery opportunities; and(Guermas: [0048]-[0051]; [0032]; [0065]; [0068];[0074])
at least one of:
bids received from the first bidder in association with the second subset of content delivery opportunities; or (Guermas: [0048]-[0051]; [0032]; [0065]; [0068];[0074])
results of auctions associated with the second subset of content delivery opportunities. (Guermas: [0048]-[0051]; [0032]; [0065]; [0068];[0074])
As per claim 9, Guermas/Newnham teach wherein the second bidder profile is usable to determine a bid floor associated with the first bidder during a second period of time after a first period of time during which (i) the first bidder profile was usable and (ii) the content requests associated with the plurality of content delivery opportunities were received. (Guermas: [0048]-[0051]; [0032]; [0065]; [0068]; Fig. 6; [0071]-[0077])
As per claim 10, Guermas/Newnham teach wherein:
in response to receiving the first content request associated with the first content delivery opportunity, generating a third bid request indicative of a third bid floor; (Guermas: [0028]-[0031]; [0044]-[0048]; [0052]; [0083]; Fig. 6; [0077])
transmitting the third bid request to a second bidder; (Guermas: [0048]; [0052]; [0083]; Fig. 6; [0077])
receiving, from the second bidder, a third bid response responsive to the third bid request, wherein the third bid response is indicative of a third bid for submission to the first auction associated with the first content delivery opportunity; (Guermas: [0044]-[0048]; [0008]; ; [0063]; [0050]-[0052]; [0083]; Fig. 6; [0077])
in response to receiving the second content request associated with the second content delivery opportunity, generating a fourth bid request indicative of a fourth bid floor; (Guermas: [0028]-[0031]; [0044]-[0048]; [0052]; [0083]; Fig. 6; [0077])
transmitting the fourth bid request to the second bidder; (Guermas: [0048]; [0052]; [0083]; Fig. 6; [0077])
receiving, from the second bidder, a fourth bid response responsive to the fourth bid request, wherein the fourth bid response is indicative of a fourth bid for submission to the second auction associated with the second content delivery opportunity; and (Guermas: [0044]-[0048]; [0008]; ; [0063]; [0050]-[0052]; [0083]; Fig. 6; [0077])
determining a second bidder profile associated with the second bidder based upon the third bid floor and the fourth bid floor and at least one of the third bid, the fourth bid, the first result, or the second result, wherein the second bidder profile is usable to determine a bid floor associated with the second bidder. (Guermas: [0048]-[0051]; [0032]; [0065]; [0068];[0074])
As per claim 11, Guermas/Newnham teach wherein: the second bidder profile is different than the first bidder profile. (Guermas: [0046]; [0049]-[0052])
As per claim 12, Guermas/Newnham teach comprising:
receiving a third content request associated with a third content delivery opportunity; (Guermas: [0028]-[0031]; [0044]-[0048]; [0052]; [0083]; Fig. 6; [0077])
in response to the third content request: (Guermas:
determining a fifth bid floor associated with the first bidder based upon the first bidder profile; (Guermas: [0028]-[0031]; [0044]-[0048]; [0052]; [0083]; Fig. 6; [0077])
transmitting a fifth bid request, indicative of the fifth bid floor, to the first bidder; (Guermas: [0048]; [0052]; [0083]; Fig. 6; [0077])
determining a sixth bid floor associated with the second bidder based upon the second bidder profile, wherein the sixth bid floor is different than the fifth bid floor; and (Guermas: [0028]-[0031]; [0044]-[0048]; [0052]; [0083]; Fig. 6; [0077])
transmitting a sixth bid request, indicative of the sixth bid floor, to the second bidder. (Guermas: [0048]; [0052]; [0083]; Fig. 6; [0077])
As per claim 13, Guermas/Newnham teach comprising:
determining a distribution of bids of the first bidder as a function of one or more features comprising a bid floor feature based upon the first bid floor and the second bid floor and at least one of the first bid, the second bid, the first result, or the second result; (Guermas: [0048]-[0051]; [0032]; [0065]; [0068];[0074])
using the distribution of bids to generate an updated bid floor value associated with increased bid values of bid responses from the first bidder; and (Guermas: [0048]-[0051]; [0032]; [0065]; [0068];[0074])
including the updated bid floor value in the first bidder profile. (Guermas: [0048]-[0051]; [0032]; [0065]; [0068];[0074])
As per claims 14-18, these claims are substantially similar to claims 1-5, respectively, and are therefore rejected in the same manner as these claims, as set forth above.
As per claims 19 and 20, these claims are substantially similar to claims 1 and 2, respectively, and are therefore rejected in the same manner as these claims, as set forth above.
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.
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/JENNIFER V LEE/Examiner, Art Unit 3688
/VICTORIA E. FRUNZI/Primary Examiner, Art Unit 3689 8/28/2026
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