DETAILED ACTION
Status of Claims
The present application, filed on or after 3/16/2013, is being examined under the first inventor to file provisions of the AIA .
This action is in reply to the RCE, Remarks, and Amendments filed on 12/04/2025.
Claims 7-10, 14, 17, and 21 remain canceled.
Claims 1, 13, 18 are amended.
Claims 1-6, 11-13, 15-16, and 18-20 have been examined and are pending.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 12/4/2025, has been entered.
(AIA ) Examiner Note
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned at the time any inventions covered therein were effectively filed absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned at the time a later invention was effectively filed in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
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 1-6, 11-13, 15-16, and 18-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea (i.e. a judicial exception) without significantly more.
Per step 1 of the 2019 Revised Patent Subject Matter Eligibility Guidance, the claims are directed towards a process, machine, or manufacture.
Per step 2A Prong One, the claims recite specific limitations which fall within at least one of the groupings of abstract ideas enumerated in MPEP 2106, as follows:
Per Independent claims 1, 13, and 18:
Processing… the likelihoods, including determining that the likelihoods provided by a first outcome model conflict with the likelihoods provided by a second outcome model;
Resolving… the conflict between the likelihoods of the first outcome model and the second outcome model by computationally modifying a value of one or more of the likelihoods based on the set of data that was not available to the first outcome model or the second outcome model, resulting in a set of updated likelihoods;
determining, based on the set of likelihoods, a new attribution of a respective outcome from the set of unattributed outcomes to a corresponding exposure.
As noted supra, these limitations fall within at least one of the groupings of abstract ideas enumerated in MPEP 2106. Specifically, these limitations fall within a combination of the group Mathematical Concepts (e.g. mathematical relationships; mathematical formulas or equations; mathematical calculations) and Certain Methods Of Organizing Human Activity (e.g. fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions).
That is, the “Processing… the likelihoods, including determining that the likelihoods provided by a first outcome model conflict with the likelihoods provided by a second outcome model” step as drafted is nothing more than a generic mathematical concept when recited at this high-level of generality; it is akin to receiving two inputs, each from a different undisclosed mathematical model, and these inputs are determined to be the same or have the same value [i.e. the two likelihoods are the same] and then performing an undisclosed mathematical operation on these two inputs [i.e. the processing] to draw a conclusion, e.g. a belief, that they should not be the same [i.e. determine there is a conflict]; i.e. there is an undisclosed mathematical operation being performed [i.e. the processing] to determine a “conflict” between two apparent facts/inputs and this outcome of this undisclosed mathematical operation is used as context, or pretext, to determine a resolution – “resolving” what is actually believed to be true as opposed to what the models are suggesting to be true, all of which lies squarely within Mathematical Concepts. An argument may also be made that at this high level of generality, such a step is nothing more than a mental exercise. There is no technical solution here and no technical problem being solved.
Regarding the “resolving” and “determining” steps, these steps are nothing more than a business decision; i.e. once a conflict is determined to exist (either by mental exercise or undisclosed mathematical operation), the limitations claim a business decision to “resolve” such conflict where resolution is the decision to collect more data to support a decision to “computationally modifying a value” which is abstract and nothing more than an undisclosed “adjustment”, when recited at this high-level of generality, one of the models to give a new answer (with a hope that the new answer is not “conflicting”) and make a new business decision regarding “attribution” based on the new model output answer. Again, this is very generic and extremely high-level descriptions of business decisions regarding use of modeled data pertaining to advertisement conversion attributions (e.g. a click or online purchase, etc…) to particular exposures of an advertisement (e.g. advertising impression). Stated another way: Applicant’s claim limitations are nothing more than the idea that output received from generic models, may be in conflict with expected beliefs and a business decision is therefore necessary to resolve such conflicts a natural path for conflict resolution is to collect more data for a model which may alter (hopefully improve) the model outcome and then a supposedly more informed business decision may be made based upon this updated information – all of which lies squarely within Certain Methods Of Organizing Human Activity. There is no technical solution here and no technical problem being solved.
Thus, the claims recite an abstract idea.
Per step 2A Prong 2, the Examiner finds that the judicial exception is not integrated into a practical application. Although there are additional elements, other than those noted supra, recited in the claims, none of these additional element(s) or a combination of elements as recited in the claims apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that it is more than a drafting effort designed to monopolize the exception. As drafted, the claims as a whole merely describe how to generally “apply” the aforementioned concepts using generic computer components (e.g. one or more computers and one or more storage devices) to execute generic software (e.g. model orchestrator) and link them to a field of use (i.e. in this case business decision regarding online advertisement impression data and conversion attribution) or serve as insignificant extra-solution activity (e.g. generic data gathering such as “receiving” data). The claimed computer components are recited at a high level of generality and are merely invoked as tools to implement the idea but are not technical in nature. Simply implementing the abstract idea on or with generic computer components is not a practical application of the abstract idea. Likewise generic data-gathering is not is not a practical application of the abstract idea. These additional limitations are as follows:
“receiving, by a model orchestrator including one or more processors, outcome data [i.e. conversion data] representing a set of unattributed outcomes [e.g. conversions], wherein an unattributed outcome of the set of unattributed outcomes does not have an observed attribution to an exposure of a set of predetermined exposures [i.e. exposure to an advertisement];
receiving, by the model orchestrator and from each of two or more different outcome models, likelihoods of a given unattributed outcome [e.g. conversion], from the set of unattributed outcomes, being attributed to corresponding exposures in different content channels, wherein the likelihoods generated by each of the different outcome models are generated based on different data streams of the different content channels;
[…]
obtaining, by the model orchestrator, a set of data that was not available to the first outcome model or the second outcome model;
However, these elements do not present a technical solution to a technical problem; i.e. Applicant’s invention is not a technique nor technical solution for “receiving” or “obtaining” data regardless of what the data is intended to represent. The invention is not directed towards an improvement in modeling. The description that wherein the likelihoods generated by each of the different outcome models are generated based on different data streams of the different content channels does not alter the system or method as claimed as the “content channels” and “different data streams” are not a positively recited aspect of the invention; i.e. the claimed “model orchestrator” receives data but a description of what external system (not claimed as an inventive aspect) provides such data does not, as currently claimed, alter the step of “receiving” this generically described data nor any of the other method steps or system components. The additional elements do not recite a specific manner of performing any of the steps core to the already identified abstract idea. Instead, these features merely serve to generally “apply” the aforementioned concepts using generic computer components, link them to a field of use (business decision regarding online advertisement impression data and conversion attribution) or are insignificant extra-solution activity (e.g. generic data gathering) to the already identified abstract idea and do not integrate the abstract idea into a practical application thereof.
Per Step 2B, the Examiner does not find that the claims provide an inventive concept, i.e., the claims do not recite additional element(s) or a combination of elements that amount to significantly more than the judicial exception recited in the claim. As discussed with respect to Step 2A Prong Two, the additional elements in the independent claims were considered as merely serving to generally “apply” the aforementioned concepts via generically described computer components, and “link” them to a field of use (i.e. business decision regarding online advertisement impression data and conversion attribution), or as insignificant extra-solution activity. For the same reason these elements are not sufficient to provide an inventive concept; i.e. the same analysis applies here in 2B. Mere instructions to apply an exception using a generic computer component and conventional data gathering cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B. So, upon revaluating here in step 2B, these elements are determined to amount to no more than mere instructions to apply the exception using generic computer components (i.e. a server) and/or gather and transmit data which is well-understood, routine, conventional activity in the field; i.e. note the Symantec, TLI, and OIP Techs Court decisions cited in MPEP 2106.05(d)(ll) indicate that mere receipt or transmission of data over a network is a well-understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here).
Accordingly, alone and in combination, these elements do not integrate the abstract idea into a practical application, as found supra, nor provide an inventive concept, and thus the claims are not patent eligible.
As for the dependent claims, the dependent claims do recite a combination of additional elements. However, these claims as a whole, considered either independently or in combination with the parent claims, do not integrate the identified abstract idea into a practical application thereof nor do they provide an inventive concept.
For example, dependent claims 2, 15, 19 each recite the following: “…wherein a modeled attribution of the sets of modeled attributions indicates an attribution of an unattributed outcome to an exposure of the set of predetermined exposures.” However, this is merely a restating of the description of the generic modeled data – i.e. the modeled data which is received is intended to indicate an attribution of an unattributed outcome [e.g. an unattributed conversion, such as a click or online purchase] to an exposure [e.g. to an ad impression] of the set of predetermined exposures. Restating the generic description (i.e. purpose) of the generic modeled data is part of the abstract idea but not significantly more.
Therefore, the Examiner does not find that these additional claim limitations integrate the abstract idea into a practical application nor provide an inventive concept. Instead, these limitations, as a whole and in combination with the already recited claim elements of the parent claims, are not significantly more than the already identified abstract idea. A similar finding is found for the remaining dependent claims.
For these reasons, the claims are not found to include additional elements that are sufficient to amount to significantly more than the judicial exception and are therefore patent ineligible.
Please see the 2019 Revised Patent Subject Matter Eligibility Guidance published in the Federal Register (84 FR 50) on January 7, 2019 (found at http://www.uspto.gov/patent/laws-and-regulations/examination-policy/examination-guidance-and-training-materials).
Claim Rejections - 35 USC § 103 (AIA )
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.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or non-obviousness.
Claims 1-6, 11-13, 15-16, and 18-20 are rejected under 35 U.S.C. 103 as obvious over Elmquist et al. (U.S. 2018/0316546 A1; hereinafter, "Elmquist") in view of Bannur et al. (U.S. 2015/0302112 A1; hereinafter, "Bannur").
Claims 1, 13, 18 (previously presented)
Pertaining to claims 1, 13, 18 exemplified in the limitations of method claim 1, Elmquist as shown teaches the following:
A computer-implemented method, comprising:
receiving, by a model orchestrator including one or more processors, outcome data representing a set of unattributed outcomes, wherein an unattributed outcome of the set of unattributed outcomes does not have an observed attribution to an exposure of a set of predetermined exposures associated with corresponding content channels, wherein an outcome corresponds to a specified target action completed by a user (Elmquist, see at least [0033] in view of [0038] and [0092], teaching: e.g. per [0092]: “…For example, the event server 140 may detect the second event [unattributed outcome] and send a message to the attribution server 150 [model orchestrator] with information [outcome data] such as one or more identifiers (e.g., device identifier and application identifier) and event type. As described below, in reference to FIG. 3, the attribution server 150 [model orchestrator] then sends a request to the coordination server 160 for attribution of the second event…”; i.e. the “second event” is not yet attributed and there is an “unattributed outcome”. Also, as previously noted per at least [0033]-[0038], the “second event is a conversion [unattributed outcome]. A conversion may include downloading and/or installing a user application, performing a purchase of a good and/or service, watching a video, subscribing to a server, etc…[an outcome corresponds to a specified target action completed by a user]”; see also [0092]-[0097]);
receiving, by the model orchestrator, and from each of two or more different outcome models, likelihoods a given unattributed outcome[,] from the set of unattributed outcomes[,] being attributed to corresponding exposures in different content channels, wherein the likelihoods generated by each of the different outcome models are generated based on different data streams of the different content channels (Elmquist, see at least [0092]-[0097] teaching: An “attribution server” [model orchestrator] sends to one or more “coordination servers” [outcome models] “a request for attribution of a second event” [request to receive a likelihood that an unattributed outcome is attributed to a corresponding exposure at coordination server]; the “attribution server” [model orchestrator] then receives from two or more different “coordination servers” [outcome models] “return attribution claims” [e.g. likelihoods] regarding a given “second event” [unattributed outcome], from a set of events, that such “second event” [unattributed outcome] is/being attributed to a corresponding exposures of a content channel managed by each respective “coordination server”; each of the “return attribution claims” [e.g. likelihoods] generated by each of the “coordination servers” [outcome models] are generated based on different “stored confirmation message data, e.g., data corresponding to each of the large number of confirmation messages which can include data for the confirmation message received in stage 210” [data streams]. Note that at least per [0109] Elmquist teaches: “…the two coordination servers [outcome models] may be distinct and may be operated by different entities…”; the only difference between the claim limitation and the teachings of Elmquist is that Elmquist may not explicitly use the terminology “likelihood” as a representation of his “return attribution claims” regarding each given “second event” [unattributed outcome] even though it is implied that such a “claim” represents some “likelihood” threshold being met in order to honestly establish a valid “claim” that the “second event” [unattributed outcome] should be attributed to a first event [exposure] as being claimed by a coordination server [outcome model]. Furthermore, because Examiner finds that calculating a likelihood or probability is within the level of ordinary skill in the art before the effective filing date of the claimed invention, it therefore would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to have either inferred that Elmquist’s received “attribution claims” represented some threshold likelihood that the “second event” should be attributed as claimed and/or obvious to assign such a likelihood to such claim because per MPEP 2143(I) (G) Some teaching, suggestion, or motivation in the prior art that would have led one of ordinary skill to modify the prior art reference teachings to arrive at the claimed invention is obvious. The motivation may be implicit and may be found in the knowledge of one of ordinary skill in the art, or, in some cases, from the nature of the problem to be solved. Id. at 1366, 80 USPQ2d at 1649.);
processing, by the model orchestrator, the likelihoods, including determining that the likelihoods provided by a first outcome model conflict with the likelihoods provided by a second outcome model (Elmquist, see citations noted supra, e.g. [0092]-[0097], teaching: “…For example, in some implementations, if multiple coordination servers 160 [first outcome model and second outcome model] return attribution claims (i.e., each returns an identified candidate event for attribution [determining that the likelihoods provided by a first outcome model conflict with the likelihoods provided by a second outcome model]), then the attribution server [model orchestrator] selects one of the attribution claims for confirmation…”; i.e. the system determines there exists a conflict in attribution claims [conflict is likelihoods provided by outcome models] if multiple coordination servers each claim attribution to one of their exposures because such claims are mutually exclusive);
obtaining, by the model orchestrator, a set of data that was not available to the first outcome model or the second outcome model (Elmquist, see citations noted supra, e.g. per: [0096]: “…FIG. 3, described below, illustrates an example method 300 of confirming attribution to a predecessor event, such as may be performed by the attribution server 150 [model orchestrator]. In some implementations, for example, the attribution server 150 [model orchestrator] selects the last candidate event (i.e., the candidate event with the date and time stamp closest in time to the second event)…”; i.e. none of the “coordination servers” [outcome models] knows which “time stamp is closest in time to the second event [unattributed outcome]” and therefore this information is “data that was not available to the “coordination servers” [outcome models].);
resolving, by the model orchestrator, the conflict between the likelihoods of the first
outcome model and the second outcome model by computationally modifying a value of one or more of the likelihoods based on the set of data that was not available to the first outcome model or the second outcome model, resulting in a set of updated likelihoods (Elmquist, teaches the aforementioned features in bold typeface but may not explicitly teach the feature which is not in bold. Elmquist, see citations noted supra, e.g. per at least [0097] and [0102]-[0103], teaching: the attribution server 150 [model orchestrator] determines [resolves] whether there was an intervening event that should receive attribution; this determination is a resolution between conflicting claims for attribution. For example, the attribution server 150 [model orchestrator] performs this determination [resolving], by sending requests to multiple different coordination servers in stage 330, receiving contenders [values of one or more likelihoods] in response, and then using a “time stamp… closest in time to the second event [unattributed outcome]” which is “data that was not available to” the “coordination servers” [outcome models], to modify his decision regarding which attribution should be accepted and which are rejected. This implies there is some computation performed on, or with the received attributions [likelihoods], to facilitate this selection between such likelihoods.
The difference between the teachings of Elmquist and the feature in question is only that Elmquist may not explicitly use the language computationally modifying a value of one or more of the likelihoods to describe his resolution process. However, Bannur teaches, e.g. per [0037] a technique by which: “…As suggested above, this “change” in the likelihood values from FIG. 7A to FIG. 7B is based on the particular filtering/constraints provided with regard to the user…”; i.e. Bannur teaches a technique of changing [computationally modifying] likelihood values [a value of one or more of the likelihoods], by using supplied filtering constraints, which is applicable to the system/method of Elmquist. Furthermore, Bannur and Elmquist are in the same field of endeavor.
Therefore, because the Examiner finds that Elmquist already provides some motivation to modify, e.g. computationally in some manner, his received attribution values [likelihood values] based upon updated data, i.e. based upon his time stamp found to be closest in time [which is information not available to coordination servers akin to applicant’s outcome models] to the second event [unattributed outcome], and Bannur teaches such a technique of modifying likelihoods, the Examiner finds that it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed in invention to use Elmquist’s time stamp data, as filtering data per Bannur’s technique to computationally modifying a value of one or more of Elmquist’s attributions [likelihood] because per MPEP 2143(I) (G) Some teaching, suggestion, or motivation in the prior art that would have led one of ordinary skill to modify the prior art reference teachings to arrive at the claimed invention is obvious. The motivation may be implicit and may be found in the knowledge of one of ordinary skill in the art, or, in some cases, from the nature of the problem to be solved. Id. at 1366, 80 USPQ2d at 1649, and/or because according to MPEP 2143(I) (C) and/or (D), the use of known technique to improve a known device, methods, or products in the same way (or which is ready for improvement) is obvious);
determining, based on the set of updated likelihoods a new attribution of a respective outcome from the set of unattributed outcomes to a corresponding exposure (Elmquist, see citations noted supra, e.g. per: [0097] “At stage 260, the coordination server 160 [outcome model] receives agreement from the attribution server 150 [model orchestrator] to attribute the second event to the described first event…”; applicant’s “determining a new attribution” reads on Elmquist’s agreement to attribute the second event to the described first event is which Elmquist does teach is based on his determination that attribution should not be granted to another coordination server [i.e based on updated set of likelihoods]. See also at least Elmquist [0102]-[0103]);
Claims 2, 15, 19 (original / previously presented)
Elmquist/Bannur teaches the limitations upon which these claims depend. Furthermore, Elmquist as shown teaches the following:
…wherein a modeled attribution of the sets of modeled attributions indicates an attribution of an unattributed outcome to an exposure of the set of predetermined exposures (Elmquist, see citations noted supra, e.g. again per [0092]-[0097]: e.g. the coordination server responds with an attribution claim [indicates an attribution of an unattributed outcome to an exposure of the set of predetermined exposures]).
Claims 3, 16, 20 (previously presented)
Elmquist/Bannur teaches the limitations upon which these claims depend. Furthermore, Elmquist as shown teaches the following:
…further comprising: retracting a modeled attribution so that a corresponding outcome is no longer attributed to an exposure indicated by the modeled attribution (Elmquist, see citations noted supra, e.g. again per [0092]-[0097]: e.g. when the attribution server 150 [model orchestrator] determines that attribution should not be granted, the coordination server 160 alternatively receives a message declining attribution [retracting the modeled attribution].)
Claim 4: (previously presented)
Elmquist/Bannur teaches the limitations upon which these claims depend. Furthermore, Elmquist as shown teaches the following:
The method of claim 1, further comprising: providing the new attributions for one or more downstream operations that generate a report based at least on the one or more updated attributions (Elmquist, see citations noted supra, e.g. again per [0092]-[0097] teaching, e.g.: The
coordination server 160 may retain data about attributions, e.g., for reporting or decision making purposes)
Claim 5: (previously presented)
Elmquist/Bannur teaches the limitations upon which these claims depend. Furthermore, Elmquist as shown teaches the following:
The method of claim 1, further comprising: generating an attribution report based on the new attributions (Elmquist, again see citations noted supra, e.g. again per [0092]-[0097] teaching, e.g.: The coordination server 160 may retain data about attributions, e.g., for reporting or decision making purposes… This report can be configured, for example, to omit events that did not receive attribution, or to highlight (or otherwise indicate) events that specifically did receive attribution.).
Claim 6: (previously presented)
Elmquist/Bannur teaches the limitations upon which these claims depend. Furthermore, Elmquist as shown teaches the following:
The method of claim 1, further comprising: determining digital content to be provided to a client device based on the new attribution, and transmitting data including the digital content to the client device (Elmquist, see citations noted supra including at least [0092]-[0097], e.g.: “…The coordination server 160 may retain data about attributions [i.e. new attributions], e.g., for reporting or decision making purposes. In some implementations, a campaign administrator may request, for example, a report [digital content] of invitations attributed with subsequent events. This report can be configured, for example, to omit events that did not receive attribution, or to highlight (or otherwise indicate) events that specifically did receive attribution…”; administrator’s device [a client device] receives requested reports [digital content]; applicant’s claim feature are very broad and read on Elmquist’s teachings).
Claim 11: (previously presented)
Elmquist/Bannur teaches the limitations upon which these claims depend. Furthermore, Elmquist as shown teaches the following:
The method of claim 1, wherein the set of data includes one or more of a geographical location associated with the at least one unattributed outcome in the set of unattributed outcomes at least one unattributed outcome in the set of unattributed outcomes or times when the corresponding exposures occurred (Elmquist, see again citations noted supra, including [0021] teaching receipt of “a first time stamp” and “third timestamp” [times when the corresponding exposures occurred])
Claim 12: (previously presented)
Elmquist/Bannur teaches the limitations upon which these claims depend. Furthermore, Elmquist as shown teaches the following:
The method of claim 1, further comprising: receiving a request from an entity for determining attributions of the set of unattributed outcomes to the set of predetermined exposures, and responsive to receiving the request, generating an output based on the new attribution corresponding to the request (Elmquist, see citations noted supra including at least [0092]-[0097], e.g.: “…The coordination server 160 may retain data about attributions, e.g., for reporting or decision making purposes. In some implementations, a campaign administrator may request, for example, a report of invitations attributed with subsequent events. This report can be configured, for example, to omit events that did not receive attribution, or to highlight (or
otherwise indicate) events that specifically did receive attribution…”).
Response to Arguments
Applicant’s arguments, regarding filed claim amendments, received 12/04/2025 have been fully considered but are moot in view of the new grounds of rejection necessitated by applicant’s amendments. Note the new 101, and 103 rejections with Elmquist in view of Bannur. Also note the following:
Regarding the 35 USC 101 rejection, applicant’s arguments and assertions are not convincing. Applicant argues (Remarks, pgs. 7-14) the claims, in view of new claim amendments, are not directed towards an abstract idea and are significantly more than an abstract idea. Respectfully, the Examiner disagrees. The claims do recite an abstract idea and are nothing significantly more than this abstract idea, as shown in the rejection provide supra, as well as hereinbelow for ease of reference:
For example, Per step 2A Prong One, the claims recite specific limitations which fall within at least one of the groupings of abstract ideas enumerated in MPEP 2106, as follows:
Per Independent claims 1, 13, and 18:
Processing… the likelihoods, including determining that the likelihoods provided by a first outcome model conflict with the likelihoods provided by a second outcome model;
Resolving… the conflict between the likelihoods of the first outcome model and the second outcome model by computationally modifying a value of one or more of the likelihoods based on the set of data that was not available to the first outcome model or the second outcome model, resulting in a set of updated likelihoods;
determining, based on the set of likelihoods, a new attribution of a respective outcome from the set of unattributed outcomes to a corresponding exposure.
As noted supra, these limitations fall within at least one of the groupings of abstract ideas enumerated in MPEP 2106. Specifically, these limitations fall within a combination of the group Mathematical Concepts (e.g. mathematical relationships; mathematical formulas or equations; mathematical calculations) and Certain Methods Of Organizing Human Activity (e.g. fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions).
That is, the “Processing… the likelihoods, including determining that the likelihoods provided by a first outcome model conflict with the likelihoods provided by a second outcome model” step as drafted is nothing more than a generic mathematical concept when recited at this high-level of generality; it is akin to receiving two inputs, each from a different undisclosed mathematical model, and these inputs are determined to be the same or have the same value [i.e. the two likelihoods are the same] and then performing an undisclosed mathematical operation on these two inputs [i.e. the processing] to draw a conclusion, e.g. a belief, that they should not be the same [i.e. determine there is a conflict]; i.e. there is an undisclosed mathematical operation being performed [i.e. the processing] to determine a “conflict” between two apparent facts/inputs and this outcome of this undisclosed mathematical operation is used as context, or pretext, to determine a resolution – “resolving” what is actually believed to be true as opposed to what the models are suggesting to be true, all of which lies squarely within Mathematical Concepts. An argument may also be made that at this high level of generality, such a step is nothing more than a mental exercise. There is no technical solution here and no technical problem being solved.
Regarding the “resolving” and “determining” steps, these steps are nothing more than a business decision; i.e. once a conflict is determined to exist (either by mental exercise or undisclosed mathematical operation), the limitations claim a business decision to “resolve” such conflict where resolution is the decision to collect more data to support a decision to “computationally modifying a value” which is abstract and nothing more than an undisclosed “adjustment”, when recited at this high-level of generality, one of the models to give a new answer (with a hope that the new answer is not “conflicting”) and make a new business decision regarding “attribution” based on the new model output answer. Again, this is very generic and extremely high-level descriptions of business decisions regarding use of modeled data pertaining to advertisement conversion attributions (e.g. a click or online purchase, etc…) to particular exposures of an advertisement (e.g. advertising impression). Stated another way: Applicant’s claim limitations are nothing more than the idea that output received from generic models, may be in conflict with expected beliefs and a business decision is therefore necessary to resolve such conflicts a natural path for conflict resolution is to collect more data for a model which may alter (hopefully improve) the model outcome and then a supposedly more informed business decision may be made based upon this updated information – all of which lies squarely within Certain Methods Of Organizing Human Activity. There is no technical solution here and no technical problem being solved.
Thus, the claims recite an abstract idea.
Per step 2A Prong 2, the Examiner finds that the judicial exception is not integrated into a practical application. Although there are additional elements, other than those noted supra, recited in the claims, none of these additional element(s) or a combination of elements as recited in the claims apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that it is more than a drafting effort designed to monopolize the exception. As drafted, the claims as a whole merely describe how to generally “apply” the aforementioned concepts using generic computer components (e.g. one or more computers and one or more storage devices) to execute generic software (e.g. model orchestrator) and link them to a field of use (i.e. in this case business decision regarding online advertisement impression data and conversion attribution) or serve as insignificant extra-solution activity (e.g. generic data gathering such as “receiving” data). The claimed computer components are recited at a high level of generality and are merely invoked as tools to implement the idea but are not technical in nature. Simply implementing the abstract idea on or with generic computer components is not a practical application of the abstract idea. Likewise generic data-gathering is not is not a practical application of the abstract idea. These additional limitations are as follows:
“receiving, by a model orchestrator including one or more processors, outcome data [i.e. conversion data] representing a set of unattributed outcomes [e.g. conversions], wherein an unattributed outcome of the set of unattributed outcomes does not have an observed attribution to an exposure of a set of predetermined exposures [i.e. exposure to an advertisement];
receiving, by the model orchestrator and from each of two or more different outcome models, likelihoods of a given unattributed outcome [e.g. conversion], from the set of unattributed outcomes, being attributed to corresponding exposures in different content channels, wherein the likelihoods generated by each of the different outcome models are generated based on different data streams of the different content channels;
[…]
obtaining, by the model orchestrator, a set of data that was not available to the first outcome model or the second outcome model;
However, these elements do not present a technical solution to a technical problem; i.e. Applicant’s invention is not a technique nor technical solution for “receiving” or “obtaining” data regardless of what the data is intended to represent. The invention is not directed towards an improvement in modeling. The description that wherein the likelihoods generated by each of the different outcome models are generated based on different data streams of the different content channels does not alter the system or method as claimed as the “content channels” and “different data streams” are not a positively recited aspect of the invention; i.e. the claimed “model orchestrator” receives data but a description of what external system (not claimed as an inventive aspect) provides such data does not, as currently claimed, alter the step of “receiving” this generically described data nor any of the other method steps or system components. The additional elements do not recite a specific manner of performing any of the steps core to the already identified abstract idea. Instead, these features merely serve to generally “apply” the aforementioned concepts using generic computer components, link them to a field of use (business decision regarding online advertisement impression data and conversion attribution) or are insignificant extra-solution activity (e.g. generic data gathering) to the already identified abstract idea and do not integrate the abstract idea into a practical application thereof.
Per Step 2B, the Examiner does not find that the claims provide an inventive concept, i.e., the claims do not recite additional element(s) or a combination of elements that amount to significantly more than the judicial exception recited in the claim. As discussed with respect to Step 2A Prong Two, the additional elements in the independent claims were considered as merely serving to generally “apply” the aforementioned concepts via generically described computer components, and “link” them to a field of use (i.e. business decision regarding online advertisement impression data and conversion attribution), or as insignificant extra-solution activity. For the same reason these elements are not sufficient to provide an inventive concept; i.e. the same analysis applies here in 2B. Mere instructions to apply an exception using a generic computer component and conventional data gathering cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B. So, upon revaluating here in step 2B, these elements are determined to amount to no more than mere instructions to apply the exception using generic computer components (i.e. a server) and/or gather and transmit data which is well-understood, routine, conventional activity in the field; i.e. note the Symantec, TLI, and OIP Techs Court decisions cited in MPEP 2106.05(d)(ll) indicate that mere receipt or transmission of data over a network is a well-understood, routine, and conventional function when it is claimed in a merely generic manner (as it is here).
Accordingly, alone and in combination, these elements do not integrate the abstract idea into a practical application, as found supra, nor provide an inventive concept, and thus the claims are not patent eligible.
For these reasons, applicant’s arguments are not convincing and the rejection is maintained.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MICHAEL J SITTNER whose telephone number is (571)270-3984. The examiner can normally be reached M-F; ~9:30-6:30. 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, Waseem Ashraf can be reached on (571) 270-3948. 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.
/Michael J Sittner/
Primary Examiner, Art Unit 3621