Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
DETAILED ACTION
Status of the Application
The following is a Final Office Action.
In response to Examiner's communication of 9/17/2025, Applicant responded on 2/19/2026. Amended claim 1, 4, 6. Cancelled claim 7-27. Added 28-34.
Claims 1-6, 28-34 are pending in this application and have been examined.
Response to Amendment
Applicant's cancellation to claims 19-27 render 35 USC 112(f) and 35 USC 112(b) rejections and software per se rejections moot.
Applicant's amendments to claims 1, 4, 6 are not sufficient to overcome the 35 USC 101 rejections set forth in the previous action.
Applicant's amendments to claims 1, 4, 6 are sufficient to overcome the prior art rejections set forth in the previous action.
Response to Arguments – 35 USC § 101
Applicant’s arguments with respect to the rejections have been fully considered, but they are not persuasive.
Applicant submits, “…amended claim 1 satisfies the criteria for subject matter eligibility for at least the reason that the claim as a whole integrates the recited judicial exception into a practical application of the exception. See MPEP § 2106.04(d)(II)...The invention described in amended claim 1 provides a specific technical solution to a problem inherent in prior audience measurement computing systems: inefficient computational overhead when correcting large-scale inaccurate probability distributions. The application explains that the claimed methods improve computer functioning in at least three ways:…Computing the Jacobian Matrix more efficiently using linear combinations, which reduces the overhead and instruction cycles used compared to "prior methods". See par. 118…Explicitly incorporating a normalization constraint to handle multiple probability distributions simultaneously, which allows the system to solve for probability distributions where only a small number of probabilities are known. See par. 118….Allocating less memory to compute adjustments, directly addressing technical limitations when correcting incorrect probability data. See par. 118.….in Ex Parte Desjardins, eligibility is credited when the specification identifies improvements as to how the system itself operates-such as reduced storage and reduced complexity...Amended claim 1 reflects these improvements by requiring a specific technical constraint (the normalization constraint) and a specific computational method (linear combination) that improves the efficiency of a computing device. Hence, amended claim 1 as a whole integrates any alleged judicial exception into a practical application at Step 2A Prong Two, and is patent eligible. And for largely the same reasons, new claims 28 and 34 are also patent eligible...” The Examiner respectfully disagrees.
While Applicant’s amendments further prosecution, unlike Desjardins and 2025 Memo, the claims and the argued elements, are directed to, …prior audience measurement…Computing the Jacobian Matrix more efficiently using linear combination… incorporating a normalization constraint to handle multiple probability distributions simultaneously… solve for probability distributions where only a small number of probabilities are known…correcting incorrect probability data…(the normalization constraint) and a specific computational method (linear combination) that improves the efficiency…, is a problem directed to mental process (i.e. human managing and predicting human demographic media impression data using mathematical concepts), organizing human activities (i.e. human managing and predicting human demographic media impression data using mathematical concepts), mathematical concepts (i.e. human managing and predicting human demographic media impression data using mathematical concepts), as established in Step 2A Prong 1. This problem does not specifically arise in the realm of computer technology, but rather, this problem existed and was addressed long before the advent of computers. Thus, the claims do not recite a technical improvement to a technical problem. Additionally, pursuant to the broadest reasonable interpretation, as an ordered combination, each of the additional elements are computing elements recited at high level of generality implementing the abstract idea, and thus, are no more than applying the abstract idea with generic computer components, i.e. computer. Further, these additional elements generally link the abstract idea to a technical environment, namely the environment of a computer, performing extra solution activities. Therefore, as a whole, the additional elements do not integrate the abstract ideas into a practical application in Step 2A Prong 2 or amount to significantly more in Step 2B.
Even novel and newly discovered judicial exceptions are still exceptions, despite their novelty. July 2015 Update, p. 3; see SAP America Inc. v. Investpic, LLC, No. 2017-2081, slip op. at 2 (Fed Cir. May 15, 2018).
Simply reciting specific limitations that narrow the abstract idea does not make an abstract idea non-abstract. 79 Fed. Reg. 74631; buySAFE Inc. v. Google, Inc., 765 F.3d 1350, 1355 (2014); see SAP America at p. 12. As discussed in SAP America, no matter how much of an advance the claims recite, when “the advance lies entirely in the realm of abstract ideas, with no plausibly alleged innovation in the non-abstract application realm,” “[a]n advance of that nature is ineligible for patenting.” Id. at p. 3.
Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone); TLI Communications LLC v. AV Auto, LLC, 823 F.3d 607, 613, 118 USPQ2d 1744, 1748 (Fed. Cir. 2016) (computer server and telephone unit). Similarly, “claiming the improved speed or efficiency inherent with applying the abstract idea on a computer” does not integrate a judicial exception into a practical application or provide an inventive concept. Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 115 USPQ2d 1636, 1639 (Fed. Cir. 2015).
Response to Arguments – Prior Art
Applicant’s arguments with respect to the rejections have been fully considered. Examiner find persuasive Applicant’s remarks on pg12-13.
Further, Applicant’s amendments are sufficient to overcome the closest prior art US Patent Publication to US20150193816A1 to Toupet et al., (hereinafter referred to as “Toupet”) in view of US Patent Publication to US20170091656A1 to Sheppard et al., (hereinafter referred to as “Sheppard”).
The prior art rejections are hereby withdrawn.
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, 28-34 is/are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter.
Claim 1 (similarly 28, 34) recite, “…perform a set of operations comprising:
logging a plurality of impressions at a first …of a first entity based on receiving a plurality of first … communications at the … of the first entity from first client … and second client …, the impressions indicative of accesses to media;
instructing the second client …, via …, to send third … communications to a second … of a database proprietor, the third … communications to be indicative of the accesses to the media at the second client …;
generating a reference demographic impression distribution based on first impressions of the logged impressions at the first … corresponding to the first client …, the first impressions indicative of accesses to media, the reference demographic impression distribution representative of reference impression counts distributed across different demographic segments; and
accessing an inaccurate demographic impression distribution based on second impressions corresponding to second client …, the second impressions indicative of accesses to media, and the inaccurate demographic impression distribution representative of first impression counts distributed across the different demographic segments;
determining an estimated demographic impression distribution based on the inaccurate demographic impression distribution, the estimated demographic impression distribution representative of the second impressions distributed across the different demographic segments;
determining a Jacobian matrix utilizing a linear combination of a constraint matrix and the estimated demographic impression distribution, wherein the constraint matrix is based on the reference demographic impression distribution, and wherein the Jacobian matrix incorporates a normalization constraint to simultaneously handle multiple probability distributions;
determining an error indicator value comprising a Lagrange multiplier change value based on the Jacobian matrix;
generating, in response to the error indicator value satisfying a threshold, an accuracy-improved demographic impression distribution by computing the Jacobian matrix using less … and allocating less … than calculating the Jacobian matrix using prior methods; and
storing, in the …, the accuracy-improved demographic impression distribution.”
Analyzing under Step 2A, Prong 1:
The limitations regarding, …logging a plurality of impressions at a first …of a first entity based on receiving a plurality of first … communications at the … of the first entity from first client … and second client …, the impressions indicative of accesses to media; instructing the second client …, via …, to send third … communications to a second … of a database proprietor, the third … communications to be indicative of the accesses to the media at the second client …; generating a reference demographic impression distribution based on first impressions of the logged impressions at the first … corresponding to the first client …, the first impressions indicative of accesses to media, the reference demographic impression distribution representative of reference impression counts distributed across different demographic segments; and accessing an inaccurate demographic impression distribution based on second impressions corresponding to second client …, the second impressions indicative of accesses to media, and the inaccurate demographic impression distribution representative of first impression counts distributed across the different demographic segments; determining an estimated demographic impression distribution based on the inaccurate demographic impression distribution, the estimated demographic impression distribution representative of the second impressions distributed across the different demographic segments; determining a Jacobian matrix utilizing a linear combination of a constraint matrix and the estimated demographic impression distribution, wherein the constraint matrix is based on the reference demographic impression distribution, and wherein the Jacobian matrix incorporates a normalization constraint to simultaneously handle multiple probability distributions; determining an error indicator value comprising a Lagrange multiplier change value based on the Jacobian matrix; generating, in response to the error indicator value satisfying a threshold, an accuracy-improved demographic impression distribution by computing the Jacobian matrix using less … and allocating less … than calculating the Jacobian matrix using prior methods; and storing, in the …, the accuracy-improved demographic impression distribution..…., under the broadest reasonable interpretation, can include a human using their mind and using pen and paper to perform the above identified limitations; therefore, the claims are directed to a mental process.
Additionally, the limitations regarding, …logging a plurality of impressions at a first …of a first entity based on receiving a plurality of first … communications at the … of the first entity from first client … and second client …, the impressions indicative of accesses to media; instructing the second client …, via …, to send third … communications to a second … of a database proprietor, the third … communications to be indicative of the accesses to the media at the second client …; generating a reference demographic impression distribution based on first impressions of the logged impressions at the first … corresponding to the first client …, the first impressions indicative of accesses to media, the reference demographic impression distribution representative of reference impression counts distributed across different demographic segments; and accessing an inaccurate demographic impression distribution based on second impressions corresponding to second client …, the second impressions indicative of accesses to media, and the inaccurate demographic impression distribution representative of first impression counts distributed across the different demographic segments; determining an estimated demographic impression distribution based on the inaccurate demographic impression distribution, the estimated demographic impression distribution representative of the second impressions distributed across the different demographic segments; determining a Jacobian matrix utilizing a linear combination of a constraint matrix and the estimated demographic impression distribution, wherein the constraint matrix is based on the reference demographic impression distribution, and wherein the Jacobian matrix incorporates a normalization constraint to simultaneously handle multiple probability distributions; determining an error indicator value comprising a Lagrange multiplier change value based on the Jacobian matrix; generating, in response to the error indicator value satisfying a threshold, an accuracy-improved demographic impression distribution by computing the Jacobian matrix using less … and allocating less … than calculating the Jacobian matrix using prior methods; and storing, in the …, the accuracy-improved demographic impression distribution..., under the broadest reasonable interpretation, is human managing and predicting human demographic media impression data using mathematical concepts, therefore, the claims are directed to certain methods of organizing human activities.
Further, …logging a plurality of impressions at a first …of a first entity based on receiving a plurality of first … communications at the … of the first entity from first client … and second client …, the impressions indicative of accesses to media; instructing the second client …, via …, to send third … communications to a second … of a database proprietor, the third … communications to be indicative of the accesses to the media at the second client …; generating a reference demographic impression distribution based on first impressions of the logged impressions at the first … corresponding to the first client …, the first impressions indicative of accesses to media, the reference demographic impression distribution representative of reference impression counts distributed across different demographic segments; and accessing an inaccurate demographic impression distribution based on second impressions corresponding to second client …, the second impressions indicative of accesses to media, and the inaccurate demographic impression distribution representative of first impression counts distributed across the different demographic segments; determining an estimated demographic impression distribution based on the inaccurate demographic impression distribution, the estimated demographic impression distribution representative of the second impressions distributed across the different demographic segments; determining a Jacobian matrix utilizing a linear combination of a constraint matrix and the estimated demographic impression distribution, wherein the constraint matrix is based on the reference demographic impression distribution, and wherein the Jacobian matrix incorporates a normalization constraint to simultaneously handle multiple probability distributions; determining an error indicator value comprising a Lagrange multiplier change value based on the Jacobian matrix; generating, in response to the error indicator value satisfying a threshold, an accuracy-improved demographic impression distribution by computing the Jacobian matrix using less … and allocating less … than calculating the Jacobian matrix using prior methods; and storing, in the …, the accuracy-improved demographic impression distribution, are mathematical concepts.
Accordingly, the claims are directed to a mental process, certain methods of organizing human activities, mathematical concepts, and thus, the claims are directed to an abstract idea under the first prong of Step 2A.
Analyzing under Step 2A, Prong 2:
This judicial exception is not integrated into a practical application under the second prong of Step 2A.
In particular, the claims recite the additional elements beyond the recited abstract idea identified under Step 2A, Prong 1, such as:
Claim 1, 28, 34: An apparatus comprising: a processor and a memory, the apparatus configured to perform a set of operations comprising: A non-transitory computer-readable medium having stored therein instructions that, when executed by a computing system, cause the computing system to perform a set of operations, server, network communications, client devices, redirect network communications, processing resources, memory
, and pursuant to the broadest reasonable interpretation, as an ordered combination, each of the additional elements are computing elements recited at high level of generality implementing the abstract idea, and thus, are no more than applying the abstract idea with generic computer components.
Further, these additional elements generally link the abstract idea to a technical environment, namely the environment of a computer.
Additionally, with respect to, “…logging…”, “…accessing…”, “…storing…”, “…generating…”, these elements do not add a meaningful limitations to integrate the abstract idea into a practical application because they are extra-solution activity, pre and post solution activity - i.e. data gathering – “…logging…”, “…accessing …”, “…storing…”, data output – “…generating…”
Analyzing under Step 2B:
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception under Step 2B.
As noted above, the aforementioned additional elements beyond the recited abstract idea are not sufficient to amount to significantly more than the recited abstract idea because, as an order combination, the additional elements are no more than mere instructions to implement the idea using generic computer components (i.e. apply it).
Additionally, as an order combination, the additional elements append the recited abstract idea to well-understood, routine, and conventional activities in the field as individually evinced by the applicant’s own disclosure, as required by the Berkheimer Memo, in at least:
[0034] The example client devices104a, 104b are example end user physical devices in which a user may access the media102. The client devices104a, 104b allow the user to interact with the media102. Example client devices104a, 104b include cellular phones, personal computers, laptops, tablets, set top boxes, or any device capable of connecting to the internet. The client devices104a report occurrences of the impressions of the media102 to the database proprietor server106. Likewise, the client devices104b also report occurrences of the impressions of the media102 to the audience measurement entity server108. The quantity of impression indications110, 111 are impressions indicative of accesses to the media102 via the client devices104a, 104b.
[0035] The example database proprietor server106 is a computer that logs impressions of media in response to the reported impression indications110. The database proprietor server106 is owned by, leased by, operated by, and/or operated on behalf of a database proprietor and stores demographic information about the audience utilizing the client devices104a. For example, when users (e.g., audience members) of the client devices104a subscribe to services of the database proprietor, the users provide demographic information (e.g., age, date of birth, gender, residence city/state, street address, etc.) for account creation purposes to gain access to online services of the database proprietor. The database proprietor server106 includes an example impression database112a. The impression database112a in the database proprietor server106 stores and organizes impressions logged in response to the reported impression indications110 from the client devices104a. The quantity of reported impressions in the reported impression indication110 include database proprietor identifiers identifiable by the database proprietor server106. The database proprietor identifiers are identifiers assigned to different ones of the client devices104a. In the illustrated example, the database proprietor identifiers are stored in association with the demographic information of the corresponding subscribers. In some examples disclosed herein, the database proprietor server106 may be a cloud server, a web server, a game server, a file server, or any other device used to store and/or manage information.
[0092] While an example manner of implementing the example probability generator502, the example matrix processor504, the example error determiner506, the example comparator507, the example constraint generator508, the example report generator128, and/or the example demographic impression distribution determiner124, of FIGS. 1-3, and 5 are illustrated in FIG. 5, one or more of the elements, processes and/or devices illustrated in FIGS. 1- 3, and 5 may be combined, divided, re-arranged, omitted, eliminated and/or implemented in any other way. Further, the example probability generator502, the example matrix processor504, the example error determiner506, the example comparator507, the example constraint generator508, the example report generator128, and/or the example demographic impression distribution determiner124, of FIGS. 1-3, and 5 may be implemented by hardware, software, firmware and/or any combination of hardware, software and/or firmware. Thus, for example, any of the example probability generator502, the example matrix processor504, the example error determiner506, the example comparator507, the example constraint generator508, the example report generator128, and/or the example demographic impression distribution determiner124, of FIGS. 1-3, and 5 could be implemented by one or more analog or digital circuit(s), logic circuits, programmable processor(s), programmable controller(s), graphics processing unit(s) (GPU(s)), digital signal processor(s) (DSP(s)), application specific integrated circuit(s) (ASIC(s)), programmable logic device(s) (PLD(s)) and/or field programmable logic device(s) (FPLD(s)). When reading any of the apparatus or system claims of this patent to cover a purely software and/or firmware implementation, at least one of the example probability generator502, the example matrix processor504, the example error determiner506, the example comparator 507, the example constraint generator508, the example report generator128, and/or the example demographic impression distribution determiner124, of FIGS. 1-3, and 5 is/are hereby expressly defined to include a non-transitory computer readable storage device or storage disk such as a memory, a digital versatile disk (DVD), a compact disk (CD), a Blu-ray disk, etc. including the software and/or firmware. Further still, the example demographic impression distribution determiner124 of FIGS. 1-3, and 5 may include one or more elements, processes and/or devices in addition to, or instead of, those illustrated in FIGS. 1-3, and 5, and/or may include more than one of any or all of the illustrated elements, processes and devices. As used herein, the phrase "in communication," including variations thereof, encompasses direct communication and/or indirect communication through one or more intermediary components, and does not require direct physical (e.g., wired) communication and/or constant communication, but rather additionally includes selective communication at periodic intervals, scheduled intervals, aperiodic intervals, and/or one-time events.
[0093] Flowcharts representative of example hardware logic, machine readable instructions, hardware implemented state machines, and/or any combination thereof for implementing the example probability generator502, the example matrix processor504, the example error determiner506, the example comparator507, the example constraint generator508, the example report generator128, and/or the example demographic impression distribution determiner124, of FIGS. 1-3, and 5 is shown in FIGS. 7-10. The machine readable instructions may be one or more executable program(s) or portion(s) of one or more executable programs for execution by a computer processor such as the processor1112 shown in the example processor platform1100 discussed below in connection with FIG. 11. The program(s) may be embodied in software stored on a non-transitory computer readable storage medium such as a CD-ROM, a floppy disk, a hard drive, a DVD, a Blu-ray disk, or a memory associated with the processor1112, but the entire program and/or parts thereof could alternatively be executed by a device other than the processor1112 and/or embodied in firmware or dedicated hardware. Further, although the example program(s) is/are described with reference to the flowcharts illustrated in FIGS. 7-10, many other methods of implementing the example probability generator502, the example matrix processor504, the example error determiner506, the example comparator507, the example constraint generator508, the example report generator128, and/or the example demographic impression distribution determiner124, of FIGS. 1-3, and 5 may alternatively be used. For example, the order of execution of the blocks may be changed, and/or some of the blocks described may be changed, eliminated, or combined. Additionally or alternatively, any or all of the blocks may be implemented by one or more hardware circuits (e.g., discrete and/or integrated analog and/or digital circuitry, an FPGA, an ASIC, a comparator, an operational- amplifier (op-amp), a logic circuit, etc.) structured to perform the corresponding operation without executing software or firmware.
[0094] As mentioned above, the example processes of FIGS. 7-10 may be implemented using executable instructions (e.g., computer and/or machine readable instructions) stored on a non-transitory computer and/or machine readable medium such as a hard disk drive, a flash memory, a read-only memory, a compact disk, a digital versatile disk, a cache, a random-access memory and/or any other storage device or storage disk in which information is stored for any duration (e.g., for extended time periods, permanently, for brief instances, for temporarily buffering, and/or for caching of the information). As used herein, the term non-transitory computer readable medium is expressly defined to include any type of computer readable storage device and/or storage disk and to exclude propagating signals and to exclude transmission media.
[0095]"Including" and "comprising" (and all forms and tenses thereof) are used herein to be open ended terms. Thus, whenever a claim employs any form of "include" or "comprise" (e.g., comprises, includes, comprising, including, having, etc.) as a preamble or within a claim recitation of any kind, it is to be understood that additional elements, terms, etc. may be present without falling outside the scope of the corresponding claim or recitation. As used herein, when the phrase "at least" is used as the transition term in, for example, a preamble of a claim, it is open-ended in the same manner as the term "comprising" and "including" are open ended. The term "and/or" when used, for example, in a form such as A, B, and/or C refers to any combination or subset of A, B, C such as (1) A alone, (2) B alone, (3) C alone, (4) A with B, (5) A with C, (6) B with C, and (7) A with B and with C. As used herein in the context of describing structures, components, items, objects and/or things, the phrase "at least one of A and B" is intended to refer to implementations including any of (1) at least one A, (2) at least one B, and (3) at least one A and at least one B. Similarly, as used herein in the context of describing structures, components, items, objects and/or things, the phrase "at least one of A or B" is intended to refer to implementations including any of (1) at least one A, (2) at least one B, and (3) at least one A and at least one B. As used herein in the context of describing the performance or execution of processes, instructions, actions, activities and/or steps, the phrase "at least one of A and B" is intended to refer to implementations including any of (1) at least one A, (2) at least one B, and (3) at least one A and at least one B. Similarly, as used herein in the context of describing the performance or execution of processes, instructions, actions, activities and/or steps, the phrase "at least one of A or B" is intended to refer to implementations including any of (1) at least one A, (2) at least one B, and (3) at least one A and at least one B.
[00107] FIG. 11 is a block diagram of an example processor platform1100 structured to execute the instructions of FIGS. 7-10 to implement the demographic impression distribution determiner124 of FIGS. 1, 5. The processor platform1100 can be, for example, a server, a personal computer, a workstation, a self-learning machine (e.g., a neural network), a mobile device (e.g., a cell phone, a smart phone, a tablet such as an iPadTM), a personal digital assistant (PDA), an Internet appliance, a DVD player, a CD player, a digital video recorder, a Blu-ray player, a gaming console, a personal video recorder, a set top box, a headset or other wearable device, or any other type of computing device.
[00108] The processor platform1100 of the illustrated example includes a processor1112. The processor1112 of the illustrated example is hardware. For example, the processor1112 can be implemented by one or more integrated circuits, logic circuits, microprocessors, GPUs, DSPs, or controllers from any desired family or manufacturer. The hardware processor may be a semiconductor based (e.g., silicon based) device. In this example, the processor implements the example probability generator502, the example matrix processor504, the example error determiner506, the example comparator507, the example constraint generator508, the example report generator128, and/or, more generally, the example demographic impression distribution determiner124 of FIGS. 1-3 and 5.
[00109] The processor1112 of the illustrated example includes a local memory1113 (e.g., a cache). The processor1112 of the illustrated example is in communication with a main memory including a volatile memory1114 and a non-volatile memory1116 via a bus1118. The volatile memory1114 may be implemented by Synchronous Dynamic Random Access Memory (SDRAM), Dynamic Random Access Memory (DRAM), RAMBUS® Dynamic Random Access Memory (RDRAM®) and/or any other type of random access memory device. The non-volatile memory1116 may be implemented by flash memory and/or any other desired type of memory device. Access to the main memory1114, 1116 is controlled by a memory controller.
[00110] The processor platform1100 of the illustrated example also includes an interface circuit1120. The interface circuit1120 may be implemented by any type of interface standard, such as an Ethernet interface, a universal serial bus (USB), a Bluetooth® interface, a near field communication (NFC) interface, and/or a PCI express interface.
[00111] In the illustrated example, one or more input devices1122 are connected to the interface circuit1120. The input device(s)1122 permit(s) a user to enter data and/or commands into the processor1112. The input device(s) can be implemented by, for example, an audio sensor, a microphone, a camera (still or video), a keyboard, a button, a mouse, a touchscreen, a track-pad, a trackball, isopoint and/or a voice recognition system.
[00112] One or more output devices1124 are also connected to the interface circuit1120 of the illustrated example. The output devices1124 can be implemented, for example, by display devices (e.g., a light emitting diode (LED), an organic light emitting diode (OLED), a liquid crystal display (LCD), a cathode ray tube display (CRT), an in-place switching (IPS) display, a touchscreen, etc.), a tactile output device, a printer and/or speaker. The interface circuit1120 of the illustrated example, thus, typically includes a graphics driver card, a graphics driver chip and/or a graphics driver processor.
[00113] The interface circuit1120 of the illustrated example also includes a communication device such as a transmitter, a receiver, a transceiver, a modem, a residential gateway, a wireless access point, and/or a network interface to facilitate exchange of data with external machines (e.g., computing devices of any kind) via a network1126. The communication can be via, for example, an Ethernet connection, a digital subscriber line (DSL) connection, a telephone line connection, a coaxial cable system, a satellite system, a line-of-site wireless system, a cellular telephone system, etc.
[00114] The processor platform1100 of the illustrated example also includes one or more mass storage devices1128 for storing software and/or data. Examples of such mass storage devices1128 include floppy disk drives, hard drive disks, compact disk drives, Blu-ray disk drives, redundant array of independent disks (RAID) systems, and digital versatile disk (DVD) drives.
[00115] The machine executable instructions1132 of FIGS. 7-10 may be stored in the mass storage device1128, in the volatile memory1114, in the non-volatile memory1116, and/or on a removable non-transitory computer readable storage medium such as a CD or DVD.
[00118] From the foregoing, it will be appreciated that example methods, apparatus and articles of manufacture have been disclosed that update an incorrect and/or inaccurate demographic impression distribution generated by a server. The disclosed methods, apparatus and articles of manufacture improve the efficiency of using a computing device by computing the Jacobian Matrix using less processing resources by executing less instruction cycles than used in prior methods. The disclosed methods, apparatus and articles of manufacture improve the efficiency of using a computing device by incorporating a normalization constraint explicitly in the constraints to handle multiple probability distributions simultaneously. Additionally, examples disclosed herein include even constraints across the probability distributions, thus for example, can solve for two probability distributions in which a small number of probabilities are known, but not the individual components. The disclosed methods, apparatus, and articles of manufacture can estimate any number of probability distributions, each including a different number of probabilities and only known constraints across them, and/or estimate a probability distribution in which the only prior knowledge is one probability. Therefore, the disclosed methods, apparatus and articles of manufacture can solve for fewer probabilities than actually existing. Additionally, the disclosed methods, apparatus and articles of manufacture improve the efficiency by allocating less memory to compute the Jacobin Matrix and correcting incorrect probability data. Furthermore, disclosed methods, apparatus and articles of manufacture improve the efficiency of a computing device by computing the Jacobian Matrix faster and more efficiently, using linear combinations to reduce the overhead used in computing the Jacobian Matrix. The disclosed methods, apparatus and articles of manufacture are accordingly directed to one or more improvement(s) in the functioning of a computer.
[00119] Although certain example methods, apparatus and articles of manufacture have been disclosed herein, the scope of coverage of this patent is not limited thereto. On the contrary, this patent covers all methods, apparatus and articles of manufacture fairly falling within the scope of the claims of this patent.
Furthermore, as an ordered combination, these elements amount to generic computer components receiving or transmitting data over a network, performing repetitive calculations, electronic record keeping, and storing and retrieving information in memory, which, as held by the courts, are well-understood, routine, and conventional. See MPEP 2106.05(d).
Moreover, the remaining elements of dependent claims do not transform the recited abstract idea into a patent eligible invention because these remaining elements merely recite further abstract limitations that provide nothing more than simply a narrowing of the abstract idea recited in the independent claims.
Looking at these limitations as an ordered combination adds nothing additional that is sufficient to amount to significantly more than the recited abstract idea because they simply provide instructions to use a generic arrangement of generic computer components to “apply” the recited abstract idea, perform insignificant extra-solution activity, and generally link the abstract idea to a technical environment. Thus, the elements of the claims, considered both individually and as an ordered combination, are not sufficient to ensure that the claim as a whole amounts to significantly more than the abstract idea itself. Since there are no limitations in these claims that transform the exception into a patent eligible application such that these claims amount to significantly more than the exception itself, claims 1-6, 28-34 are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
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 extension fee 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 date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to PO HAN MAX LEE whose telephone number is (571)272-3821. The examiner can normally be reached on Mon-Thurs 8:00 am - 7:00 pm.
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/PO HAN LEE/Primary Examiner, Art Unit 3623