DETAILED ACTION
The present application, filed on 5/7/2019 is being examined under the AIA first inventor to file provisions.
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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 1/30/2026 has been entered.
The following is a non-final Office Action on the Merits in response to Applicant’s submission.
a. Claims 11, 20 are amended
b. Claims 1-10 are withdrawn
Overall, Claims 11-20 have been examined below
Claim Rejections - 35 USC § 101
35 USC 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 11-20 are rejected under 35 USC 101 because the claimed invention is not directed to patent eligible subject matter. The claimed matter is directed to a judicial exception (i.e. an abstract idea not integrated into a practical application) without significantly more.
Per Step 1 and Step 2A of the two-step eligibility analysis, independent Claim 11 and Claim 20 and the therefrom dependent claims are directed respectively to a system and to a computer implemented method. Thus, on its face, each such independent claim and the therefrom dependent claims are directed to a statutory category of invention.
However, Claim 20, (which is repeated in Claim 11) is rejected under 35 U.S.C. 101 because the claim is directed to an abstract idea, a judicial exception, without reciting additional elements that integrate the judicial exception into a practical application. The claim recites: identifying an attribution window; analyzing the visit information and the impression information within the attribution window; determining an actual visit rate; determining an actual visit rate; determining a visit lift rate; automatically generating a report detailing the effectiveness of the directed information; providing the report.
The limitations, as drafted, constitute a process that, under its broadest reasonable interpretation, covers commercial activity, but for the recitation of generic computer components. That is, the drafted process is comparable to marketing preparation process, i.e. a process aimed at calculating, assessing the impact of providing information to consumers for marketing purposes, upon the visitation rate of those consumers. If a claim limitation, under its broadest reasonable interpretation, covers performance of marketing activities, but for the recitation of generic computer components, then it falls within the “Certain Methods of Organizing Human Activity – Commercial or Legal Interactions (e.g. advertising, marketing, sales activities or behaviors, business relationships)” grouping of abstract ideas.
Accordingly, the claim recites an abstract idea.
Alternatively, the limitations, as drafted, constitute a process that, under its broadest reasonable interpretation, covers performance of the limitations in the mind, but for the recitation of generic computer components. That is, other than reciting computing components, nothing in the claim element precludes the steps from practically being performed in the mind. For example, “identifying an attribution window associated with the directed information” in the context of this claim encompasses the user manually, verbally or mentally analyzing the visit information, without physical aid; “analyzing the visit information and the impression information within the attribution window” in the context of this claim encompasses the user manually, verbally or mentally analyzing the visit information, without physical aid. Similarly, the limitation “determining an actual visit rate,” as drafted, is a process that, under its broadest reasonable interpretation, covers the user manually or mentally dividing the number of visits by the time window measure, without physical aid. Similarly, the limitation “determining a visit lift rate,” as drafted, is a process that, under its broadest reasonable interpretation, covers the user manually or mentally dividing the number of visits by the time window measure, without physical aid. Finally, “generating a report detailing the effectiveness of the directed information,” respectively “providing the report” without physical aid, in the context of this claim encompasses the user manually or verbally generating the report, respectively providing that report. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind, but for the recitation of generic computer components, then it falls within the “Mental Processes – Concepts Performed in the Human Mind (e.g. observation, evaluation, judgement, opinion)” grouping of abstract ideas (see MPEP 2106.04(a)(2)). The use of a physical aid would not negate the mental nature of this limitation (see MPEP 2106.04(a)(2) iii B).
Accordingly, the claim recites an abstract idea.
This abstract idea is not integrated into a practical application. In particular, stripped of those claim elements that are directed to an abstract idea, (A) remaining elements of the independent claims are directed to: training a predictive machine learning model; generating a merged data set comprising visit information and impression information; training a bias-corrected logistic regression model; receiving visit information; receiving impression information. When considered individually, these additional claim elements represent receipt, transmission and general computation claim elements that serve merely to implement the abstract idea using computing components performing computer functions (adding the words “apply it” or an equivalent), or merely uses a computer as a tool to perform an abstract idea. (MPEP 2106.05(f)) It is readily apparent that the claim elements are not directed to any specific improvements of the claims.
(B) Additional remaining claim elements are: the users; the impression information; the plurality of feature vectors; the training process; the visit lift rate; the machine learning model; the data associated with a plurality of features; the merged data set; the report; the way the machine learning model is trained. While these descriptive elements may provide further helpful context for the claimed invention, they do not serve to integrate the abstract idea into a practical application.
(C) Finally, recited computing elements, i.e. processors; memory are recited at a high-level of generality, i.e. as generic computing elements performing generic computer functions, like obtaining data, interpreting the obtained data and providing results, such that they amount to no more than mere instructions to apply the exception using generic computer components.
Accordingly, these additional claim elements do not integrate the abstract idea into a practical application, because: (1) they do not effect improvements to the functioning of a computer, or to any other technology or technical field (see MPEP 2106.05 (a)); (2) they do not apply or use the abstract idea to effect a particular treatment or prophylaxis for a disease or a medical condition (see the Vanda memo); (3) they do not apply the abstract idea with, or by use of, a particular machine (see MPEP 2106.05 (b)); (4) they do not effect a transformation or reduction of a particular article to a different state or thing (see MPEP 2106.05 (c)); (5) they do not apply or use the abstract idea in some other meaningful way beyond generally linking the use of the identified abstract idea to a particular technological environment, such that the claim as a whole is more than a drafting effort designated to monopolize the exception (see MPEP 2106.05 (e) and the Vanda memo). Therefore, per Step 2A, Prong Two, the claim is directed to an abstract idea not integrated into a practical application.
(A) Step 2B of the eligibility analysis for the independent claims concludes that the claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. Stripped of those claim elements that are directed to an abstract idea, not integrated into a practical application, remaining elements of the independent claims are directed to: training a predictive machine learning model; generating a merged data set comprising visit information and impression information; training a bias-corrected logistic regression model; receiving visit information; receiving impression information.
When considered individually, these additional claim elements represent general processing, receipt and transmission claim elements that serve merely to implement the abstract idea using computer components performing computer functions. The steps only serve to automate the abstract idea. (see MPEP 2106.05(f)) It is readily apparent that the claim elements are not directed to any specific improvements of the claims.
(B) Furthermore, additional remaining elements of the independent claims contain descriptive limitations explaining the nature, structure and/or content of: the users; the training process; the impression information; the plurality of feature vectors; the visit lift rate; the machine learning model; the data associated with a plurality of features; the merged data set; the report; the way the machine learning model is trained. However, these claim elements do not require any steps or functions to be performed and thus do not involve the use of any computing functions. While these descriptive elements may provide further helpful context for the claimed invention, these elements do not serve to confer subject matter eligibility to the claimed invention since their individual and combined significance is still not heavier than the abstract concepts at the core of the claimed invention.
(C) Finally, the recited computing elements of the independent claims are: processors; memory. When considered individually, these additional claim elements serve merely to implement the abstract idea using computer components performing computer functions. They do not constitute “Improvements to the Functioning of a Computer or to Any Other Technology or Technical Field”. (MPEP 2106.05(a)) It is readily apparent that the claim elements are not directed to any specific improvements of any of these areas.
When the independent claims are considered as a whole, as a combination, the claim elements noted above do not amount to significantly more, to any more than they amount to individually. The operations appear to merely apply the abstract concept to a technical environment in a very general sense – i.e. a computer receives information from another computer, processes that information and then sends a response based on processing results. The most significant elements of the claims, that is the elements that really outline the inventive elements of the claims, are set forth in the elements identified as an abstract idea. Therefore, it is concluded that the elements of the independent claims are directed to one or more abstract ideas and do not amount to significantly more. (MPEP 2106.05)
Further, Step 2B of the analysis takes into consideration all dependent claims as well, both individually and as a whole, as a combination.
Dependent Claim 18 is not directed to any additional abstract ideas, but is directed to additional claim elements such as to: dividing the actual visit rate by the expected visit rate. When considered individually, these additional claim elements are comparable to “performing repetitive calculations” “re-computing”, which has been recognized by a controlling court as "well-understood, routine and conventional elements" when claimed generically as they are in these dependent claims. (see MPEP 2106.05(d) II) It is readily apparent that the claim elements are not directed to any specific improvements of the claims.
Dependent Claim 19 is not directed to any additional abstract ideas, but is directed to additional claim elements such as to: performing one or more actions responsive to calculating the visit rate lift, wherein the one or more actions include automatically generating a report. When considered individually, these additional claim elements are comparable to “receiving or transmitting data over a network, e.g., using the Internet to gather data”, which has been recognized by a controlling court as "well-understood, routine and conventional elements" when claimed generically as they are in these dependent claims. (see MPEP 2106.05(d) II) It is readily apparent that the claim elements are not directed to any specific improvements of the claims.
Dependent Claims 12-17 are not directed to any abstract ideas and are not directed to any additional non-abstract claim elements. Rather, these claims provide further descriptive limitations of elements, such as describing the nature, structure and/or content of: the visit information; the attribution window; the machine learning model; the expected visit rate; the actual visit rate; the visit lift rate. However, these elements do not require any steps or functions to be performed and thus do not involve the use of any computing functions. While these descriptive elements may provide further helpful context for the claimed invention, these elements do not serve to confer subject matter eligibility to the invention since their individual and combined significance is still not heavier than the abstract concepts at the core of the claimed invention.
Moreover, the claims in the instant application do not constitute significantly more also because the claims or claim elements only serve to implement the abstract idea using computer components to perform computing functions (Enfish, see MPEP 2106.05(a)). Specifically, the computing system encompasses general purpose hardware and software modules, as disclosed in the application specification in fig5 and [0046]-[0050], including among others: processing unit; system memory; removable storage; non-removable storage; output devices; input devices; communication connections.
When the dependent claims are considered as a whole, as a combination, the claim elements noted above appear to merely apply the abstract concept to a technical environment in a very general sense – i.e. a computer receives information from another computer, processes that information and then sends a response based on processing results. The most significant elements of the claims, that is the elements that really outline the inventive elements of the claims, are set forth in the elements identified in the independent claims as an abstract idea. The fact that the computing devices are facilitating the abstract concept is not enough to confer statutory subject matter eligibility. In sum, the additional elements do not serve to confer subject matter eligibility to the invention since their individual and combined significance is still not heavier than the abstract concepts at the core of the claimed invention. Therefore, it is concluded that the dependent claims of the instant application do not amount to significantly more either. (see MPEP 2106.05)
In sum, Claims 11-20 are rejected under 35 USC 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 112(b)
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION – The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
Claims 12, 14 and 26 are rejected under 35 U.S.C. 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor regards as the invention. Whether the positive outcomes are “rare” or not is a matter of opinion; reasonable people would reasonably disagree as to the positive outcomes being rare or not. See MPEP 2173.05(b) and authorities cited therein.
Claim Rejections - 35 USC § 103
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the 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, if the difference 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 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(a) are summarized as follows:
i. Determining the scope and contents of the prior art.
ii. Ascertaining the differences between the prior art and the claims at issue.
iii. Resolving the level of ordinary skill in the pertinent art.
iv. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 11-20 are rejected under 35 U.S.C. 103 as being unpatentable over Liang et al (US 2018/0260393), in view of Luo et al (WO 2017/062912), in further view of Worthington (WO 2020/107100).
Regarding Claims 11, 20 – Liang discloses: A system comprising: one or more processors; and memory coupled to at least one of the one or more processors, the memory comprising computer executable instructions that, when executed by the at least one processor, performs a method comprising:
generating a merged data set comprising visit information and impression information, … {see at least fig5A, rc166, rc512, rc540, rc542, [0067] As shown in FIG. 5A, the evaluation module 170 further includes a filter 540 configured to obtain data related to each of the impressed mobile devices in the data store 512, to query the events database 166 for site visit events related to the document, and to store data associated with the site visit events in a data store 542. FIG. 5B illustrates examples of the site visit events in the data store 542 grouped by each document and listed by the UID's of the mobile devices impressed with the document. As shown each of the mobile devices having had at least one impression event can have none or one or more site visit events related to the document with different time stamps (Day/Hour) (site visits rc542 are merged with impressions 512)}
receiving visit information associated with one or more users, {see at least fig6B, [0069] history window; [0077] users who visited the target location}
wherein the one or more users have been exposed to directed information; {see at least fig6B, [0069] time lag between impression and visited location (reads on users exposed to direct impressions}
receiving impression information relating to the directed information, wherein the impression information is associated with at least a portion of the one or more users; {see at least fig5A, rc164, rc166, [0064] impression-based performance (reads on impression information)}
identifying an attribution window associated with the directed information; {see at least FIG6d, FIG6e, [0074]-[0080] exposure window, attribution window}
analyzing the visit information and the impression information within the attribution window … to determine an expected visit rate for the one or more users for each day of attribution window; {see at least fig10, [0100] “behavior window” reads on visit and impression information within the time window; predicts (reads on analyzing) a visitation likelihood based on known behavior; normalized visitation frequency; fig4C, rc473, [0106] visit projections based on visitation estimated; fig7, rc730-rc750, [0081]-[0082]; ]; [0063] a SVR (location visitation rate) estimation system; [0071]-[0073] PM|.sub.SV=CPV*SVRest*1000, or PM|.sub.SV=CPV*SVRest*(freqv/freqi)*1000, SVRest is an estimated site visit rate; location visit rate per window (based on the broadest reasonable interpretation requirement (MPEP 2111), reads on visit rate per day); fig11A, rc1140, [0102] computing a site visit rate (reads on visit rate per day)}
determining an actual visit rate for the one or more users; and {see at least fig7, rc720, [0080] compute visitation rate}
Liang does not disclose, however, Luo discloses:
… the merged data set comprising a combined data set of users who were exposed to prior directed information and users who were not exposed to prior directed information; and {see at least fig5, fig6, [0034]-[0035] exposed users (reads on users previously exposed), qualified users, request users (reads on users not prior exposed)}
determine a visit lift rate using the expected visit rate and the actual visit rate, {see at least fig5, rc540, rc550, [0035] obtain lift results}
determining a visit lift rate based upon an evaluation of the expected visit rate, … against the actual visit rate; {see at least fig5, rc510-rc550] obtain lift results from store visitation rates (reads on lift rate); [0057] store visitation rate used to calculate visits lift (reads on visit lift rate)}
wherein the visit lift rate represents an increase in visit rate attributable to exposure to the directed information. {see at least fig5, rc540, rc550, [0035] (based on the broadest reasonable interpretation requirement (see MPEP 2111), exposure to direct information is construed as test group, which is compared to the control group, i.e. baseline visitation)}
evaluating the expected visit rate against the actual visit rate to calculate a visit lift rate. {see at least fig5, rc540, rc550, [0035] (based on the broadest reasonable interpretation requirement (see MPEP 2111), exposure to direct information is construed as test group, which is compared to the control group, i.e. baseline visitation)}
automatically generating a report comprising at least the subset of the plurality of features; and {see ta least fig5, rc550, [0034]-[0035] obtain and output the lift results from the store visitation rates (reads on report on effectiveness); [0079] report on store visitation rates}
providing the report. {see ta least fig5, rc550, [0034] obtain and output the lift results from the store visitation rates (reads on report on providing the report); [0079] report on store visitation rates}
It would have been obvious to one of ordinary skill in the art, at the time of filing, to modify Liang to include the elements of Luo. One would have been motivated to do so, in order to provide a success measure of providing impressions. In the instant case, Liang evidently discloses determining an actual visit rate based on received information. Luo is merely relied upon to illustrate the functionality of calculating and evaluating the visit rate in the same or similar context. Since both determining an actual visit rate based on received information, as well as calculating and evaluating the visit rate are implemented through well-known computer technologies in the same or similar context, combining their features as outlined above using such well-known computer technologies (i.e., conventional software/hardware configurations), would be reasonable, according to one of ordinary skill in the art. Moreover, since the elements disclosed by Liang, as well as Luo would function in the same manner in combination as they do in their separate embodiments, it would be reasonable to conclude that their resulting combination would be predictable. Accordingly, the claimed subject matter is obvious over Liang / Luo.
Liang, Luo does not disclose, however, Worthington discloses:
training a predictive machine learning model, wherein training the predictive machine learning model comprises: {see at least [0007] training a machine learning model; model predictor}
training a bias-corrected logistic regression model using the merged data set, wherein the training process includes a plurality of rare positive outcome examples; {see at least [0117] discloses training a machine learning model using a “single target linear regression” technique. Worthington does not explicitly disclose: training the machine learning model by using a bias-corrected logistic regression technique. The claim element “a bias-corrected logistic regression technique” is given no patentable weight because it is not directed to the subject of the claim, i.e., “analyzing visit information”. The specification does not disclose that only the bias-corrected logistic regression technique can be used to achieve the desired results. In addition, the Supreme Court has supported that substituting one known element for another, to obtain predictable results, is sufficient to determine an invention obvious over such combination (see KSR International Co. v. Teleflex Inc. (KSR), 550 U.S.,82 USPQ2d 1385 (2007) & MPEP 2143 (B)). Therefore, the machine learning technique disclosed by Worthington could successfully replace bias-corrected logistic regression technique.}
… determined by the machine learning model, … {see at least fig6, [0109] Machine Learning Training Module 5014}
… using machine learning model … {see at least fig6, [0109] Machine Learning Training Module 5014}
It would have been obvious to one of ordinary skill in the art, at the time of filing, to modify Liang, Luo to include the elements of Worthington. One would have been motivated to do so, in order to improve visit prediction accuracy by using an efficient prediction tool. In the instant case, Liang, Luo evidently discloses determining and evaluating an actual visit rate based on received information. Worthington is merely relied upon to illustrate the functionality of training a machine learning model in the same or similar context. Since both determining and evaluating an actual visit rate based on received information, as well as training a machine learning model are implemented through well-known computer technologies in the same or similar context, combining their features as outlined above using such well-known computer technologies (i.e., conventional software/hardware configurations), would be reasonable, according to one of ordinary skill in the art. Moreover, since the elements disclosed by Liang, Luo, as well as Worthington would function in the same manner in combination as they do in their separate embodiments, it would be reasonable to conclude that their resulting combination would be predictable. Accordingly, the claimed subject matter is obvious over Liang, Luo / Worthington.
Regarding Claim 12 – Liang, Luo, Worthington discloses the limitations of Claim 11. Liang further discloses:
wherein the visit information is collected from a contextual awareness engine that records user visitation patterns to locations. {see at least fig5A, rc542, site visitation events}
Regarding Claim 13 – Liang, Luo, Worthington discloses the limitations of Claim 11. Liang further discloses:
wherein the attribution window defines a date of exposure to the directed information and a number of days subsequent to the date of exposure. {see at least fig6D, fig6E, [0074]-[0080] attribution window vs exposure window}
Regarding Claim 14 – Liang, Luo, Worthington discloses the limitations of Claim 11. Liang further discloses:
wherein the machine learning model is a binary logistic regression model. {see at least fig10, [0100] training window (reads on machine learning model) … logistic regression}
Regarding Claim 15 – Liang, Luo discloses the limitations of Claim 11. Liang further discloses:
wherein the expected visit rate represents a probability that the one or more users visited one or more locations on one or more days had the one or more users not been exposed to the directed information. {see at least fig7, fig8, [0080]-[0082] estimating the visitation rate (reads on probability); rc710 the complement to exposed users is “not been exposed” users)}
Regarding Claim 16 – Liang, Luo, Worthington discloses the limitations of Claim 11. Liang further discloses:
wherein the actual visit rate represents a number of visits that actually occurred by users during the attribution window. {see at least [0071] estimated visit rate within a time window after impressions are made}
Regarding Claim 17 – Liang, Luo, Worthington discloses the limitations of Claim 11. Liang further discloses:
wherein the visit lift rate represents a percentage increase in visit rate attributable to the directed information. {see at least [0071] estimated visit rate within a time window after impressions are made}
Regarding Claim 18 – Liang, Luo, Worthington discloses the limitations of Claim 11. Luo further discloses: wherein calculating the visit lift rate comprises
dividing the actual visit rate by the expected visit rate. {see at least fig5, rc540, rc550, [0035]}
It would have been obvious to one of ordinary skill in the art, at the time of filing, to modify Liang, Luo, Worthington to include additional elements of Luo. One would have been motivated to do so, in order to provide a value for the success of providing impressions. In the instant case, Liang, Luo, Worthington evidently discloses determining and evaluating an actual visit rate based on received information. Luo is merely relied upon to illustrate the additional functionality of calculating visit rate lift in the same or similar context. Since the subject matter is merely a combination of old elements, and in the combination each element would have performed the same function it performed separately, one having ordinary skill in the art before the effective filing date would have recognized that the results of the combination were predictable.
Regarding Claim 19 – Liang, Luo, Worthington discloses the limitations of Claim 11. Luo further discloses: wherein the method further comprises:
performing one or more actions responsive to calculating the visit rate lift, wherein the one or more actions include automatically generating a report. {see at least fig5, rc550, [0035] outputting test visitation lift results}
It would have been obvious to one of ordinary skill in the art, at the time of filing, to modify Liang, Luo, Worthington to include additional elements of Luo. One would have been motivated to do so, in order to publicize the results. In the instant case, Liang, Luo, Worthington evidently discloses determining and evaluating an actual visit rate based on received information. Luo is merely relied upon to illustrate the additional functionality of generating a report with the results in the same or similar context. Since the subject matter is merely a combination of old elements, and in the combination each element would have performed the same function it performed separately, one having ordinary skill in the art before the effective filing date would have recognized that the results of the combination were predictable.
The prior art made of record and not relied upon which, however, is considered pertinent to applicant's disclosure:
US 20160253689 A1 2016-09-01 34 Milton; Stephen et al. PROBABILISTIC CROSS-DEVICE PLACE VISITATION RATE MEASUREMENT AT SCALE - Provided is a process including: obtaining network traffic logs; matching a set of a plurality of the user computing devices; obtaining an indicator of content to be measured for effectiveness in driving place visits; selecting from the network traffic logs records of network exchanges in which the indicator is present; obtaining a device identifier from each of the selected records; matching the obtained device identifiers to respective matching sets including the respective obtained identifier; obtaining respective mobile device identifiers from the respective matching sets; selecting from the network traffic logs records indicating communications from mobile computing devices identified by the obtained mobile device identifiers; obtaining geolocations from the records indicating communications from the mobile computing devices identified; determining that a subset of the records have geolocations that correspond to at least one of a set of geographic areas; and determining an effectiveness of the content in driving visits.
US 20180260393 A1 2018-09-13 41 LIANG; Can et al. USING ON-LINE AND OFF-LINE PROJECTIONS TO CONTROL INFORMATION DELIVERY TO MOBILE DEVICES - A system for processing information requests associated with mobile devices comprises an information server configured to build a search query for an information request based on the location features and other data therein and to search an information database for matching information documents. The matching information documents including information documents having different types of performance measure, including a first document using an impression-based performance measure, a second document using a click/call-based performance measure and a third document using an off-line site-visit-based performance measure. The information server is further configured rank the matching documents based on their respective performance measures and to select a matching document based on their respective rankings. The information server is further configured to generate a projected probability of an off-line site visit in response to the second document being selected to fulfill the each request and impressed on an associated mobile device, and to adjust a budget of the second document based on the projected probability.
US 10165402 B1 2018-12-25 30 Davis; Brent et al. System to track engagement of media items - An engagement tracking system monitors user interactions with media items to calculate an engagement score of the media item. The engagement tracking system may be or include a group of one or more server machines configured to detect an exposure of a client device to a media item maintained by the engagement tracking system. In response to detecting the exposure of the client device to the media item, the engagement tracking system tracks a location of the client device based on access requests to location based media items. The engagement tracking system may thereby monitor client devices exposed to the media item in order to calculate an engagement score of the media item.
US 10115124 B1 2018-10-30 36 Kamvysselis; Peter Kellis Systems and methods for preserving privacy - A system collects information from different sources regarding online activities of users and information regarding presentation of additional content. The user online activity information can include an indication of a web page visited (e.g., URL), a time when the web page was visited, and an anonymized identifier for a user device. Additional content service information can include an additional content identifier, a time the additional content was served, and an anonymized identifier for a user device to which the additional content was served. An optimizing engine uses this information to correlate additional content presentation to user online activity while preserving privacy of users. The system can use the correlation information to perform various statistical analyses, including determining the effects of presentation of particular additional content on user online activity, while preserving the privacy of individual users and preventing the information from being linked to a particular user.
CA 2975471 A1 2019-01-05 34 SWEENEY NEIL SYSTEMS AND METHODS FOR FIRST PARTY MOBILE ATTRIBUTION - A method, systems and computer program product for first party mobile attribution are described. Impression data, mobile device locations, beacon data/information and other data points are collected and converted by an Analytics Server to determine the effectiveness of a marketing or advertising campaign and how the campaign influenced a visit to a store and subsequent purchase as a result of the campaign.
WO 2017062912 A2 2017-04-13 47 LUO HUITAO et al. METHOD AND APPARATUS FOR MEASURING EFFECT OF INFORMATION DELIVERED TO MOBILE DEVICES - The present disclosure provides method and apparatus for measuring effect of information delivered to mobile devices. In certain embodiments, a method performed by one or more computer systems coupled to a packet-based network comprises receiving a first plurality of request data packets via the packet-based network, receiving panel data packets via the packet-based network, and selecting a set of calibration mobile devices from the first plurality of mobile devices, each of the set of calibration mobile device having transmitted at least one of the panel data packets. The calibration mobile devices are used to derive a calibration factor. The method further comprises tracking a first number of mobile devices that have been served specific information to determine a second number of exposed memory devices having visited at least one of one or more pre-defined places, and calculating a measure of an effect of the specific information delivered to the first number of mobile devices using the first number, the second number and the calibration factor.
Response to Amendments/Arguments
Applicant’s submitted remarks and arguments have been fully considered.
Applicant disagrees with the Office Action conclusions and asserts that the presented claims fully comply with the requirements of 35 U.S.C. § 101 regrading judicial exceptions. Further, Applicant is of the opinion that the prior art fails to teach Applicant’s invention.
Examiner respectfully disagrees in both regards.
With respect to Applicant’s Remarks as to the claims being rejected under 35 USC § 101.
Applicant submits:
a. The pending claims are not directed to an abstract idea.
b. The identified abstract idea is integrated into a practical application.
c. The pending claims amount to significantly more.
Furthermore, Applicant asserts that the Office has failed to meet its burden to identify the abstract idea and to establish that the identified abstract idea is not integrated into a practical application and that the pending claims do not amount to significantly more.
Examiner responds – The arguments have been considered in light of Applicants’ amendments to the claims. The arguments ARE NOT PERSUASIVE. Therefore, the rejection is maintained.
The pending claims, as a whole, are directed to an abstract idea not integrated into a practical application. This is because (1) they do not effect improvements to the functioning of a computer, or to any other technology or technical field (see MPEP 2106.05 (a)); (2) they do not apply or use the abstract idea to effect a particular treatment or prophylaxis for a disease or a medical condition (see the Vanda memo); (3) they do not apply the abstract idea with, or by use of, a particular machine (see MPEP 2106.05 (b)); (4) they do not effect a transformation or reduction of a particular article to a different state or thing (see MPEP 2106.05 (c)); (5) they do not apply or use the abstract idea in some other meaningful way beyond generally linking the use of the identified abstract idea to a particular technological environment, such that the claim as a whole is more than a drafting effort designated to monopolize the exception (see MPEP 2106.05 (e) and the Vanda memo).
In addition, the pending claims do not amount to significantly more than the abstract idea itself.
As such, the pending claims, when considered as a whole, are directed to an abstract idea not integrated into a practical application and not amounting to significantly more.
More specific:
Applicant submits “Applicants maintain that the claims are not directed towards a method for generating human activity.”
Examiner has carefully considered, but doesn’t find Applicant’s arguments persuasive.
The eligibility analysis in the instant Office Action does not make such an allegation.
Thus, the rejection is proper and has been maintained.
Applicant submits “In doing so, the Office Action completely disregards the above claim features. To be sure, the claims are directed towards training a specific machine learning model to perform a specific task, which does not fall under one of the enumerated categories of "organizing human activity."”
Examiner has carefully considered, but doesn’t find Applicant’s arguments persuasive.
The claim features Applicant is referring to have not been identified as falling in the “Organizing Human Activity” category of abstract ideas by the instant Office Action.
Thus, the rejection is proper and has been maintained.
Applicant submits “No do the claims recite a mental process, as alleged by the Office Action.”
Examiner has carefully considered, but doesn’t find Applicant’s arguments persuasive.
See response immediately above.
Thus, the rejection is proper and has been maintained.
Applicant submits “Furthermore, the Guidelines explicitly state that USPTO Example 39 shows that training a neural network does not recite an abstract idea.”
Examiner has carefully considered, but doesn’t find Applicant’s arguments persuasive.
The eligibility analysis in the instant Office Action does not make such an allegation.
Thus, the rejection is proper and has been maintained.
Applicant submits “Furthermore, even if the claims were directed towards an abstract idea, which they are not, Applicants maintain that the claims are embodied in a practical application, namely, the generation of advance models as described in paragraph [0019] recited above.”
Examiner has carefully considered, but doesn’t find Applicant’s arguments persuasive.
MPEP 2106.04(d)(1) discloses:
An important consideration to evaluate when determining whether the claim as a whole integrates a judicial exception into a practical application is whether the claimed invention improves the functioning of a computer or other technology .... In short, first the specification should be evaluated to determine if the disclosure provides sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. The specification need not explicitly set forth the improvement, but it must describe the invention such that the improvement would be apparent to one of ordinary skill in the art .... Second, if the specification sets forth an improvement in technology. the claim must be evaluated to ensure that the claim itself reflects the disclosed improvement. (Emphasis added)
That is, the claimed invention may integrate the judicial exception into a practical application by demonstrating that it improves the relevant existing technology although it may not be an improvement over well-understood, routine, conventional activity. (Emphasis added)
Thus, the rejection is proper and has been maintained.
It follows from the above that there are no meaningful limitations in the claims that transform the judicial exception into a patent eligible application such that the claims amount to significantly more than the judicial exception itself. Therefore, the rejection under 35 U.S.C. § 101 is maintained.
With respect to Applicant’s Remarks as to the claims being rejected under 35 USC § 103.
Applicant submits remarks and arguments geared toward the amendments. Examiner has carefully reviewed and considered Applicant’s remarks, however they ARE MOOT in light of the fact that they are geared towards the amendments.
The other arguments presented by Applicant continually point back to the above arguments as being the basis for the arguments against the other 103 rejections, as the other arguments are presented only because those claims depend from the independent claims, and the main argument above is presented against the independent claims. Therefore, it is believed that all arguments put forth have been addressed by the points above.
Examiner has reviewed and considered all of Applicant’s remarks. The changes of the grounds for rejection, if any, have been necessitated by Applicant’s extensive amendments to the claims. Therefore, the rejection is maintained, necessitated by the extensive amendments and by the fact that the rejection of the claims under 35 USC § 101 has not been overcome.
Inquiries
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Radu Andrei whose telephone number is 313.446.4948. The examiner can normally be reached on Monday – Friday 8:30am – 5pm EST. If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, John Hayes can be reached at 571.272.6708. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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Any response to this action should be mailed to:
Commissioner of Patents and Trademarks
P.O. Box 1450
Alexandria, VA 22313-1450
or faxed to 571-273-8300
/Radu Andrei/
Primary Examiner, AU 3698
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