DETAILED ACTION
This correspondence is responsive to the application filed on March 22, 2023. Claims 1-20 are pending in the case, with claims 1, 11 and 19 in independent form.
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 .
Summary of Detailed Action
Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite.
Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite
Claims 1-10, 19-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite.
Claims 4, 16 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite.
Claims 3, 15, 20 Claims 10-18 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite.
Claims 10-18 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim Rejections - 35 USC § 112
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.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
I. Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Independent claims 1 and 19 recite subject matter for receiving trigger data defining a trigger event and “logic” to add an enriched event associated with the trigger event; … generating event data describing the execution of the trigger event and the enriched event responsive to the detecting based on the “logic” of the trigger data; storing the event data within an offline simulation environment. It is not clear what the “logic” is or is not nor what the “logic” includes or does not include. For example, is logic an action, process or operation? Or, does logic include one or more Boolean type of logical values or evaluations? Or, is logic some type of pattern to be searched or matched? Or, is logic a type of computer programming language or computer instructions? Or, is logic some type of inference or reasoning. Or, is the logic something else entirely? Claims 4, 6, 9-10, and 20 also recite the logic term that is unclear and indefinite for the same reasons discussed above with respect to claims 1 and 19. Independent claim 11 recites generating “logic,” … to add the enriched event as part of the trigger event in trigger data; executing the “logic” of the trigger data in an online execution environment to generate event data. It is not clear what the “logic” is or is not nor what the “logic” includes or does not include. For example, is logic an action, process or operation? Or, does logic include one or more Boolean type of logical values or evaluations? Or, is logic some type of pattern to be searched or matched? Or, is logic a type of computer programming language or computer instructions? Or, is logic some type of inference or reasoning. Or, is the logic something else entirely? Claims 16-18 also recite the logic term that is unclear and indefinite for the same reasons discussed above with respect to claim 11. Applicant may cancel claims 1, 4, 6, 9-10, 11, 16-18, and 19-20 or amend claims 1, 4, 6, 9-10, 11, 16-18, and 19-20 to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 2-3, 5, 7-8 depend directly or indirectly from claim 1 and are rejected for the same reasons discussed above with respect to their base claim 1.
Claims 12-15 depend directly or indirectly from claim 11 and are rejected for the same reasons discussed above with respect to their base claim 11.
II. Claims 1-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. Independent claims 1, 11, and 19 recite an “enriched event associated with the trigger event.” It is not clear what an enriched event is or is not nor what an enriched event includes or does not include. It is further unclear how an enriched event is associated with a trigger event. It is yet further unclear how to add an enriched event. Applicant may cancel claims 1, 11 and 19 or amend claims 1,11, and 19 to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 2-8 depend directly or indirectly from claim 1 and are rejected for the same reasons discussed above with respect to their base claim 1.
Claims 12-18 depend directly or indirectly from claim 11 and are rejected for the same reasons discussed above with respect to their base claim 11.
Claim 20 depends from claim 19 and is rejected for the same reasons discussed above with respect to their base claim 19.
III. Claims 1-10 and 19-20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. Independent claims 1 and 19 recite receiving trigger data defining a trigger event and logic to “add an enriched event associated with the trigger event”. It is not clear what an enriched event associated with the trigger event is or is not. For example, does the enriched event include the trigger event? Or, is the enriched event an event that is somehow associated with the trigger event but does not include the trigger event? It is yet further unclear what the enriched event is added to or not added to. It is still yet further unclear how to add the enriched event to some thing or another. Applicant may cancel claims 1 and 19 or amend claims 1 and 19 to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 2-10 depend directly or indirectly from claim 1 and include all of the limitations of their base claim 1 and are rejected for the same reasons discussed above with respect to claim 1.
Claim 20 depends from claim 19 and is rejected for the same reasons discussed above with respect to claim 19.
IV. Claims 4 and 16 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. Independent claims 4 and 16 recite wherein the logic of the trigger data defines a “cascading logic” definition of the trigger event with respect to the enriched event. It is not clear what cascading logic means or what cascading logic is or is not. For example, does cascading logic mean or include a succession of logic operations, processes, steps, instructions, patterns, or Boolean values? Or, does cascading logic mean or include stages of logic operations, processes, steps, instructions, patterns, Boolean values? Or, does cascading logic mean or include progressing logic operations, processes, steps, instructions, patterns, or Boolean values? Or, does cascading logic mean or include overlapping logic processes, or operations, or steps, or instructions or patterns, or Boolean values? Or, does cascading logic mean or include an order of logic operations, processes, steps, instructions, patterns, of Boolean values. Or, does cascading logic mean a hierarchy of logic operations, processes, steps, instructions, patterns, or Boolean values? Applicant may cancel claims 4 and 16 or amend claims 4 and 16 to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
V. Claims 3, 15 and 20 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. Independent claims 3, 15 and 20 recite wherein the simulating is configured as an offline “point-in-time feature simulation.” It is not clear what a point-in time feature simulation is or is not. For example, is the point in time a historical point in time, a future point in time, a matching point in time, or any point in time? Further, is the feature a prediction feature or any dataset feature, or some other type of feature? Further, it is not clear what the simulation is simulating. For example, is the simulation simulating an online application? Or, is the simulation simulating a machine learning inference? Or, is the simulation simulating a machine learning model training process? Or, is the simulation simulating a user process or event? Or, is the simulation simulating an online dataset or an online input data or online output data? Or, is simulation simulating something else entirely? Applicant may cancel claims 3, 15 and 20 or amend claims 3, 15 and 20 to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
VI. Claims 10-18 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention. Claim 10 depends from claim 9 and recites wherein the logic is generated automatically and without user intervention responsive to receipt of the input via the user interface. Claim 10 appears to recite conflicting subject matter by requiring that the logic is generated automatically and without user intervention but is responsive to receipt of the input via the user interface. It is not clear how the logic is automatically generated without user intervention when it is responsive to input via the user interface, which appears to be at least some amount of user intervention via apparent user input via the user interface. It is not clear if the input via the user interface is not user input or if there is user input via the user interface, it is not used to automatically generate the logic. Or, does the claim mean something else entirely? Applicant may cancel claim 10 or amend claim 10 to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Independent claim 11, similarly recites “receiving an input via a user interface” defining a trigger event and an enriched event associated with the trigger event; generating logic, “automatically and without user intervention responsive to the input,” to add the enriched event as part of the trigger event in trigger data. Thus, claim 11 is unclear regarding how the logic is automatically generated without user intervention when it is responsive to input via the user interface, which appears to be at least some amount of user intervention via apparent user input via the user interface. It is not clear if the input via the user interface is not user input or if there is user input via the user interface, it is not used to automatically generate the logic. Or, does the claim mean something else entirely? Applicant may cancel claim 11 or amend claim 11 to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 12-18 depend directly or indirectly from claim 11 and include all of the limitations of their base claim 11 and are rejected for the same reasons discussed above with respect to claim 11.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s) subject matter at a general, high-level of a method for defining a trigger event and an enriched event associated with the trigger event (mental processes and mathematical concepts); generating logic, detecting occurrence of the trigger event in execution of one or more digital services of a service provider system based on the trigger data (mental process); generating event data describing the execution of the trigger event and the enriched event responsive to the detecting based on the logic of the trigger data (mental process); simulating operation of the executable service platform offline using the event data (mental process and mathematical concepts); and outputting a result of the simulating (mental process and mathematical concepts), which are mental processes or concepts that can be performed in the human mind, including observation, evaluation, judgment or opinion, or by a human using pen and paper. MPEP 210604(a)(2)(III) and mathematical concepts including mathematical relationships, mathematical formulas or equations, and mathematical calculations. MPEP 210604(a)(2)(I). This judicial exception is not integrated into a practical application and the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception.
Claims 1-20 recite one of the four statutory categories of patent able subject matter and belong to the statutory class(es) of a process (method claims 1-10), a machine (system/apparatus claims 11-18), and an article of manufacture (non-transitory computer readable media claims 19-20).
Claim 1 recites a method, thus a process and one of the four statutory categories of patentable subject matter. However, claim 1 further recites comprising defining a trigger event and logic to add an enriched event associated with the trigger event (mental processes and mathematical concepts); detecting occurrence of the trigger event in execution of one or more digital services of a service provider system based on the trigger data (mental processes and mathematical concepts); generating event data describing the execution of the trigger event and the enriched event responsive to the detecting based on the logic of the trigger data (mental process and mathematical concepts); simulating operation of the executable service platform offline using the event data; and outputting a result of the simulating (mental process and mathematical concepts), which are mental processes or concepts that can be performed in the human mind, including observation, evaluation, judgment or opinion, or by a human using pen and paper (MPEP 210604(a)(2)(III)) and mathematical concepts including mathematical relationships, mathematical formulas or equations, and mathematical calculations (MPEP 210604(a)(2)(I)).
The claim does not include any additional elements which integrate the abstract idea into a practical application since the additional elements consist of:
receiving trigger data; (An additional element of extra-solution activity that courts have identified is well understood, routine and conventional activity for receiving or transmitting data over a network, e.g., using the internet to gather data. See also, MPEP 2106.05(d)(II), MPEP 2106.05(g), 2019 Guidance, 84 FR 50 at 55, 2019 Guidance, 84 FR 50, footnote 31.).
by an executable service platform in an online operational environment (This additional element amounts to merely the words to “apply it” (or an equivalent) or are mere instructions to implement an abstract idea or other exception on a computer. MPEP 2106.05(f).) Also, this additional element amounts to no more than generally linking the use of the judicial exception to a particular technologic environment or field of use - The application or use of the judicial exception in this manner does not meaningfully limit the claim by going beyond generally linking the use of the judicial exception to a particular technological environment. MPEP 2106.05(h)).
storing the event data within an offline simulation environment; (An additional element of extra-solution activity that courts have identified is well understood, routine and conventional activity for receiving or transmitting data over a network, e.g., using the internet to gather data. See also, MPEP 2106.05(d)(II), MPEP 2106.05(g), 2019 Guidance, 84 FR 50 at 55, 2019 Guidance, 84 FR 50, footnote 31.).
for display in a user interface (an additional element merely recites the words “apply it” (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. See also, MPEP 2106.05(f), MPEP 2106.04(d), 2019 Guidance, 84 FR 50 at 55, footnote 30.).
Thus, the claim is directed to the abstract idea.
Further, the additional elements, alone or in combination, do not provide significantly more than the abstract idea itself, because implementation on a computer (MPEP 2106.05(f)) cannot provide significantly more, and transmitting data over a network is well-understood, routine and conventional (MPEP 2106.05(d), and generally linking the use of the judicial exception to a particular technological field of use does not meaningfully limit the claims (MPEP 2106.04(d)) and the combination of additional elements does not provide an inventive concept. Thus, the claim is ineligible.
Claim 2, dependent on claim 1, does not include any additional elements which integrate the abstract idea into a practical application since the additional elements consist of:
wherein the simulating includes training and retraining a machine learning model using the event data as training data (This additional element amounts to merely the words to “apply it” (or an equivalent) or are mere instructions to implement an abstract idea or other exception on a computer. MPEP 2106.05(f).) Also, this additional element amounts to no more than generally linking the use of the judicial exception to a particular technologic environment or field of use - The application or use of the judicial exception in this manner does not meaningfully limit the claim by going beyond generally linking the use of the judicial exception to a particular technological environment. MPEP 2106.05(h)).
Claim 3, dependent on claim 1, recites only additional abstract ideas for wherein the simulating is configured as an offline point-in-time feature simulation, which are mental processes or concepts that can be performed in the human mind, including observation, evaluation, judgment or opinion, or by a human using pen and paper (MPEP 210604(a)(2)(III)) and mathematical concepts including mathematical relationships, mathematical formulas or equations, and mathematical calculations (MPEP 210604(a)(2)(I)).
Claim 4, dependent on claim 1, recites only additional abstract ideas for wherein the logic of the trigger data defines a cascading logic definition of the trigger event with respect to the enriched event, which are mental processes or concepts that can be performed in the human mind, including observation, evaluation, judgment or opinion, or by a human using pen and paper (MPEP 210604(a)(2)(III)) and mathematical concepts including mathematical relationships, mathematical formulas or equations, and mathematical calculations (MPEP 210604(a)(2)(I)).
Claim 5, dependent on claim 1, recites only additional abstract ideas for wherein the trigger data is configured as a domain specific language, which are mental processes or concepts that can be performed in the human mind, including observation, evaluation, judgment or opinion, or by a human using pen and paper (MPEP 210604(a)(2)(III)) and mathematical concepts including mathematical relationships, mathematical formulas or equations, and mathematical calculations (MPEP 210604(a)(2)(I)).
Claim 6, dependent on claim 1, recites only additional abstract ideas for further comprising detecting occurrence of the enriched event responsive to the detecting the occurrence of the trigger event based on the logic of the trigger data, which are mental processes or concepts that can be performed in the human mind, including observation, evaluation, judgment or opinion, or by a human using pen and paper (MPEP 210604(a)(2)(III)) and mathematical concepts including mathematical relationships, mathematical formulas or equations, and mathematical calculations (MPEP 210604(a)(2)(I)).
Claim 7, dependent on claim 1, recites additional abstract ideas for further comprising monitoring execution of the one or more digital services and wherein the detected is based on the monitoring, which are mental processes or concepts that can be performed in the human mind, including observation, evaluation, judgment or opinion, or by a human using pen and paper (MPEP 210604(a)(2)(III)) and mathematical concepts including mathematical relationships, mathematical formulas or equations, and mathematical calculations (MPEP 210604(a)(2)(I)).
The claim does not include any additional elements which integrate the abstract idea into a practical application since the additional elements consist of:
by the executable service platform (an additional element merely recites the words “apply it” (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. See also, MPEP 2106.05(f), MPEP 2106.04(d), 2019 Guidance, 84 FR 50 at 55, footnote 30.).
Claim 8, dependent on claim 1, recites only additional abstract ideas for further comprising determining a level of matching of an output of the online operational environment with an output of the simulating and wherein the outputting indicates the level of matching, which are mental processes or concepts that can be performed in the human mind, including observation, evaluation, judgment or opinion, or by a human using pen and paper (MPEP 210604(a)(2)(III)) and mathematical concepts including mathematical relationships, mathematical formulas or equations, and mathematical calculations (MPEP 210604(a)(2)(I)).
Claim 9, dependent on claim 1, recites only additional abstract ideas for wherein the logic is generated based on an input to expand a definition of the trigger event, which are mental processes or concepts that can be performed in the human mind, including observation, evaluation, judgment or opinion, or by a human using pen and paper (MPEP 210604(a)(2)(III)) and mathematical concepts including mathematical relationships, mathematical formulas or equations, and mathematical calculations (MPEP 210604(a)(2)(I)).
The claim does not include any additional elements which integrate the abstract idea into a practical application since the additional elements consist of:
via a user interface (an additional element merely recites the words “apply it” (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. See also, MPEP 2106.05(f), MPEP 2106.04(d), 2019 Guidance, 84 FR 50 at 55, footnote 30.).
Claim 10, dependent on claim 1, does not include any additional elements which integrate the abstract idea into a practical application since the additional elements consist of:
wherein the logic is generated automatically and without user intervention responsive to receipt of the input via the user interface (an additional element merely recites the words “apply it” (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. See also, MPEP 2106.05(f), MPEP 2106.04(d), 2019 Guidance, 84 FR 50 at 55, footnote 30.).
Claim 11 recites a device, thus a machine and one of the four statutory categories of patentable subject matter. However, claim 11 further recites including defining a trigger event and an enriched event associated with the trigger event (mental processes and mathematical concepts); generating logic (mental processes and mathematical concepts) to add the enriched event as part of the trigger event in trigger data (mental processes and mathematical concepts); generate event data, the event data describing execution of the trigger event and execution of the enriched event as part of operation of one or more digital services (mental processes and mathematical concepts), which are mental processes or concepts that can be performed in the human mind, including observation, evaluation, judgment or opinion, or by a human using pen and paper (MPEP 210604(a)(2)(III)) and mathematical concepts including mathematical relationships, mathematical formulas or equations, and mathematical calculations (MPEP 210604(a)(2)(I)).
The claim does not include any additional elements which integrate the abstract idea into a practical application since the additional elements consist of:
receiving an input via a user interface (an additional element merely recites the words “apply it” (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. See also, MPEP 2106.05(f), MPEP 2106.04(d), 2019 Guidance, 84 FR 50 at 55, footnote 30.).
automatically and without user intervention responsive to the input, to (an additional element merely recites the words “apply it” (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. See also, MPEP 2106.05(f), MPEP 2106.04(d), 2019 Guidance, 84 FR 50 at 55, footnote 30.).
executing the logic of the trigger data in an online execution environment (This additional element amounts to merely the words to “apply it” (or an equivalent) or are mere instructions to implement an abstract idea or other exception on a computer. MPEP 2106.05(f).) Also, this additional element amounts to no more than generally linking the use of the judicial exception to a particular technologic environment or field of use - The application or use of the judicial exception in this manner does not meaningfully limit the claim by going beyond generally linking the use of the judicial exception to a particular technological environment. MPEP 2106.05(h)).
Thus, the claim is directed to the abstract idea.
Further, the additional elements, alone or in combination, do not provide significantly more than the abstract idea itself, because implementation on a computer (MPEP 2106.05(f)) cannot provide significantly more, and generally linking the use of the judicial exception to a particular technological field of use does not meaningfully limit the claims (MPEP 2106.04(d)) and the combination of additional elements does not provide an inventive concept. Thus, the claim is ineligible.
Claim 12, dependent on claim 11, recites only additional abstract ideas for wherein the operations further comprise simulating the operation of the online execution environment, which are mental processes or concepts that can be performed in the human mind, including observation, evaluation, judgment or opinion, or by a human using pen and paper (MPEP 210604(a)(2)(III)) and mathematical concepts including mathematical relationships, mathematical formulas or equations, and mathematical calculations (MPEP 210604(a)(2)(I)).
Claim 13, dependent on claim 12, recites only additional abstract ideas for the operations further comprising determining a level of matching of an output of the online operational environment with an output of the simulating, which are mental processes or concepts that can be performed in the human mind, including observation, evaluation, judgment or opinion, or by a human using pen and paper (MPEP 210604(a)(2)(III)) and mathematical concepts including mathematical relationships, mathematical formulas or equations, and mathematical calculations (MPEP 210604(a)(2)(I)).
Claim 14, dependent on claim 11, does not include any additional elements which integrate the abstract idea into a practical application since the additional elements consist of:
wherein the simulating includes training and retraining a machine learning model using the event data as training data (This additional element amounts to merely the words to “apply it” (or an equivalent) or are mere instructions to implement an abstract idea or other exception on a computer. MPEP 2106.05(f).) Also, this additional element amounts to no more than generally linking the use of the judicial exception to a particular technologic environment or field of use - The application or use of the judicial exception in this manner does not meaningfully limit the claim by going beyond generally linking the use of the judicial exception to a particular technological environment. MPEP 2106.05(h)).
Claim 15, dependent on claim 14, recites only additional abstract ideas for wherein the simulating implements an offline point-in-time feature simulation, which are mental processes or concepts that can be performed in the human mind, including observation, evaluation, judgment or opinion, or by a human using pen and paper (MPEP 210604(a)(2)(III)) and mathematical concepts including mathematical relationships, mathematical formulas or equations, and mathematical calculations (MPEP 210604(a)(2)(I)).
Claim 16, dependent on claim 11, recites only additional abstract ideas for wherein the logic of the trigger data defines a cascading logic definition of the trigger event with respect to the enriched event, which are mental processes or concepts that can be performed in the human mind, including observation, evaluation, judgment or opinion, or by a human using pen and paper (MPEP 210604(a)(2)(III)) and mathematical concepts including mathematical relationships, mathematical formulas or equations, and mathematical calculations (MPEP 210604(a)(2)(I)).
Claim 17, dependent on claim 11, recites additional abstract ideas for wherein the operations further comprise detecting occurrence of the trigger event and the generating is performed responsive to the detecting, which are mental processes or concepts that can be performed in the human mind, including observation, evaluation, judgment or opinion, or by a human using pen and paper (MPEP 210604(a)(2)(III)) and mathematical concepts including mathematical relationships, mathematical formulas or equations, and mathematical calculations (MPEP 210604(a)(2)(I)).
The claim does not include any additional elements which integrate the abstract idea into a practical application since the additional elements consist of:
responsive to the executing of the logic (This additional element amounts to merely the words to “apply it” (or an equivalent) or are mere instructions to implement an abstract idea or other exception on a computer. MPEP 2106.05(f).) Also, this additional element amounts to no more than generally linking the use of the judicial exception to a particular technologic environment or field of use - The application or use of the judicial exception in this manner does not meaningfully limit the claim by going beyond generally linking the use of the judicial exception to a particular technological environment. MPEP 2106.05(h)).
Claim 18, dependent on claim 17, recites additional abstract ideas for wherein the operations further comprise detecting occurrence of the enriched event responsive to the detecting the occurrence of the trigger event based on the trigger data, which are mental processes or concepts that can be performed in the human mind, including observation, evaluation, judgment or opinion, or by a human using pen and paper (MPEP 210604(a)(2)(III)) and mathematical concepts including mathematical relationships, mathematical formulas or equations, and mathematical calculations (MPEP 210604(a)(2)(I)).
The claim does not include any additional elements which integrate the abstract idea into a practical application since the additional elements consist of:
the executing of logic of (This additional element amounts to merely the words to “apply it” (or an equivalent) or are mere instructions to implement an abstract idea or other exception on a computer. MPEP 2106.05(f).) Also, this additional element amounts to no more than generally linking the use of the judicial exception to a particular technologic environment or field of use - The application or use of the judicial exception in this manner does not meaningfully limit the claim by going beyond generally linking the use of the judicial exception to a particular technological environment. MPEP 2106.05(h)).
Claim 19 recites one or more computer-readable storage media, thus an article of manufacture and one of the four statutory categories of patentable subject matter. However, claim 19 further recites including defining a trigger event and logic to add an enriched event associated with the trigger event (mental processes and mathematical concepts); detecting occurrence of the trigger event in execution of one or more digital services based on the trigger data (mental processes and mathematical concepts); generating event data describing the execution of the trigger event and the enriched event responsive to the detecting based on the logic of the trigger data (mental processes and mathematical concepts); and simulating operation of the executable service platform offline using the event data (mental processes and mathematical concepts), which are mental processes or concepts that can be performed in the human mind, including observation, evaluation, judgment or opinion, or by a human using pen and paper (MPEP 210604(a)(2)(III)) and mathematical concepts including mathematical relationships, mathematical formulas or equations, and mathematical calculations (MPEP 210604(a)(2)(I)).
The claim does not include any additional elements which integrate the abstract idea into a practical application since the additional elements consist of:
One or more computer-readable storage media storing instructions that, responsive to execution by a processing device, causes the processing device to perform operations including (an additional element merely recites the words “apply it” (or an equivalent) with the judicial exception, or merely includes instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea. See also, MPEP 2106.05(f), MPEP 2106.04(d), 2019 Guidance, 84 FR 50 at 55, footnote 30.).
receiving trigger data (An additional element of extra-solution activity that courts have identified is well understood, routine and conventional activity for receiving or transmitting data over a network, e.g., using the internet to gather data. See also, MPEP 2106.05(d)(II), MPEP 2106.05(g), 2019 Guidance, 84 FR 50 at 55, 2019 Guidance, 84 FR 50, footnote 31.).
by an executable service platform in an online operational environment of a service provider system (This additional element amounts to merely the words to “apply it” (or an equivalent) or are mere instructions to implement an abstract idea or other exception on a computer. MPEP 2106.05(f).) Also, this additional element amounts to no more than generally linking the use of the judicial exception to a particular technologic environment or field of use - The application or use of the judicial exception in this manner does not meaningfully limit the claim by going beyond generally linking the use of the judicial exception to a particular technological environment. MPEP 2106.05(h)).
executing a machine learning model, the executing (This additional element amounts to merely the words to “apply it” (or an equivalent) or are mere instructions to implement an abstract idea or other exception on a computer. MPEP 2106.05(f).) Also, this additional element amounts to no more than generally linking the use of the judicial exception to a particular technologic environment or field of use - The application or use of the judicial exception in this manner does not meaningfully limit the claim by going beyond generally linking the use of the judicial exception to a particular technological environment. MPEP 2106.05(h)).
Thus, the claim is directed to the abstract idea.
Further, the additional elements, alone or in combination, do not provide significantly more than the abstract idea itself, because implementation on a computer (MPEP 2106.05(f)) cannot provide significantly more, and transmitting data over a network is well-understood, routine and conventional (MPEP 2106.05(d), and generally linking the use of the judicial exception to a particular technological field of use does not meaningfully limit the claims (MPEP 2106.04(d)) and the combination of additional elements does not provide an inventive concept. Thus, the claim is ineligible.
Claim 20, dependent on claim 19, recites only additional abstract ideas for wherein the logic of the trigger data defines a cascading logic definition of the trigger event with respect to the enriched event, which are mental processes or concepts that can be performed in the human mind, including observation, evaluation, judgment or opinion, or by a human using pen and paper (MPEP 210604(a)(2)(III)) and mathematical concepts including mathematical relationships, mathematical formulas or equations, and mathematical calculations (MPEP 210604(a)(2)(I)).
Allowable Subject Matter
Claims 1-20 would be allowable if the rejections of claims under 35 U.S.C. 112(b) as being indefinite are overcome and if the rejections of claims under 35 U.S.C. 101 as being directed to an abstract idea without significantly more are overcome.
The following is a statement of reasons for the indication of allowable subject matter:
The closest known prior arts of record are Li, Lihong, et al (“Unbiased Offline Evaluation of Contextual-bandit-based News Article Recommendation Algorithms”, arXiv:1003.5956v.2), Pueyo et al. (US 9,262,532), Yilmazcoban et al. (US 2020/0324206), Parkhe et al. (US 2022/0374457), Jain et al. (US 2023/0196185), Wisniewski et al. (US 2022/0044144), Polleri et al. (US 2021/0081848), Rossi (US 2024/0004737), Delgado et al. (US Patent 11,244,244), Markey et al. (US 2014/0046777). The examiner notes that Li is cited on applicants Information Disclosure Statement filed November, 27, 2024.
Li, Lihong, et al, (“Unbiased Offline Evaluation of Contextual-bandit-based News Article Recommendation Algorithms”, arXiv:1003.5956v.2). Li teaches Contextual bandit algorithms have become popular for on line recommendation systems such as Digg, Yahoo! Buzz, and news recommendation in general. Offline evaluation of the effectiveness of new algorithms in these applications is critical for protecting online user experiences but very challenging due to their “partial-label” nature. Common practice is to create a simulator which simulates the online environment for the problem at hand and then run an algorithm against this simulator. However, creating simulator itself is often difficult and modeling bias is usually unavoidably introduced. In this paper, we introduce a replay method ology for contextual bandit algorithm evaluation. Different from simulator-based approaches, our method is completely data-driven and very easy to adapt to different applications. More importantly, our method can provide provably unbiased evaluations. Our empirical results on a large-scale news article recommendation dataset collected from Yahoo! Front Page conform well with our theoretical results. Furthermore, comparisons between our offline replay and online bucket evaluation of several contextual bandit algorithms show accuracy and effectiveness of our offline evaluation method.
Regarding independent claims 1 and 19 Li teaches a method comprising: receiving trigger data (in Li the log data is the trigger data. Section 1: “each user visit results in … the log: user information, the displayed news article, and user feedback (click or not). When using the data of this form to evaluate a bandit algorithm offline” to use the log data offline, this is to be received by the offline system), defining a trigger event (in Section 1, the trigger event is the user click, Section 1: “and user feedback (click or not)”) and logic to add an enriched event associated with the trigger event (said logic in Li is the reminder of the data in the log, Section 1: “each user visit results in the following information stored in the log: user information, the displayed news article, and user feedback (click or not).” See also Sections 4.1. - 4.1.3 ); detecting occurrence of the trigger event in execution of one or more digital services by an executable service platform in an online operational environment of a service provider system (Li Section 1: “In our application of news article recommendation on Yahoo! Front Page, for example, each user visit results in the following information stored in the log: user information, the displayed news article, and user feedback (click or not)”) displayed news article, and user feedback (click or not)”); storing the event data within an offline simulation environment (Li Section 3.2: “we consider a situation that may be more relevant to practical evaluation of a static policy when we have a finite data set S containing L logged events (stored event data). Roughly speaking, the algorithm steps through every event in D as in algorithm 1 and obtains an estimate of the policy’s average per-trial payoff based on a random number of valid events. The detailed pseudocode in Algorithm 2 (simulator, in a simulation environment).” For “offline” see Abstract.); simulating operation of the executable service platform offline using the event data (Li Section 3.2: “we consider a situation that may be more relevant to practical evaluation of a static policy when we have a finite data set S containing L logged events (event data). Roughly speaking, the algorithm steps through every event in D as in algorithm 1 and obtains an estimate of the policy’s average per-trial payoff based on a random number of valid events. The detailed pseudocode in Algorithm 2 (simulator simulating operation of executable service platform). For “offline” see Abstract.); and outputting a result of the simulating for display in a user interface (In Li a result of simulating is considered to be the final recommendation visualized to the user (see Figure 1, and Section 4.1: “In this paper, we focus on selecting articles for the story position.”” which is dependent on the recommender algorithm is selected through the offline simulation (Li, Abstract: “ Offline evaluation of the effectiveness of new algorithms in these applications is critical for protecting online user experiences but very challenging due to their “partial-label” nature.” For claim 19 machine learning see section 3.1.).
Li and the prior arts of record do not disclose detecting occurrence of the trigger event in execution of one or more digital services by an executable service platform in an online operational environment of a service provider system “based on the trigger data.” In Li, the trigger event click is detected in order to generate the log trigger data. Thus, in Li, it is the trigger data which is based on the detection of the trigger event, which is the opposite of claim 1.
Regarding independent claim 11, Li teaches:
receiving an input via a user interface defining a trigger event and an enriched event associated with the trigger event; (i.e., Li teaches receiving user feedback click input via a user interface that defines a trigger event. Section 1. Li teaches that “each user visit results in the following information stored in the log: user information, the displayed news article, and user feedback (click or not) (user visit enriched event with user information, displayed news article associated with the user feedback click trigger event). When using the data of this form to evaluate a bandit algorithm offline” to use the log data offline, this input via a user interface is to be received by the offline system. Li, Section 1, see also Sections 4.- 4.3, 3.1-3.2.)
generating logic, automatically and without user intervention responsive to the input, to add the enriched event as part of the trigger event in trigger data;
(i.e., Li teaches that the algorithm generates logic automatically and without user intervention, responsive to the feedback click input trigger event, to add the enriched user visit event user information and displayed news article, which are associated with the user feedback click trigger event and are part of the user feedback click input trigger event in the log trigger data. Li, Section 1, see also Sections 4.- 4.3, 3.1-3.2.)
storing the event data in an offline simulation environment in support of simulating operation of the online execution environment. (Li Section 3.2: “we consider a situation that may be more relevant to practical evaluation of a static policy when we have a finite data set S containing L logged events (stored event data). Roughly speaking, the algorithm steps through every event in D as in algorithm 1 and obtains an estimate of the policy’s average per-trial payoff based on a random number of valid events. The detailed pseudocode in Algorithm 2 (simulator, in a simulation environment, in support of simulating operation of the online execution environment).” For “offline” see Abstract. Li, Abstract, Section 3.2, see also Sections 1, 4.- 4.3, 3.1.).
Li does not specifically disclose “a computing device comprising: a processing device; and a computer-readable storage medium storing instructions that, responsive to execution by the processing device, causes the processing device to perform operations.” However, Pueyo teaches the computing device at Figure 5 and corresponding description col 24:4- col 25:16.
Li and the prior arts of record do not specifically disclose “executing the logic of the logged trigger data in an online execution environment to generate event data, the event data describing execution of the trigger event and execution of the enriched event as part of operation of one or more digital services.” Instead, in Li the trigger data is the logged data that includes event and enriched event data and does not include logic that is executed. In Li the logic being executed is the algorithm simulating the online news article recommendation on Yahoo! Front Page, for example to generate the log event data describing the user feedback click trigger event and the enriched user visit event user information and displayed news article as part of the operation of one or more digital news article recommendation services. Li, Sections 1, 4-4.3.
Pueyo et al. (US 9,262,532) discloses example methods, apparatuses, or articles of manufacture are disclosed that may be implemented using one or more computing devices to facilitate or otherwise support one or more processes or operations associated with ranking entity facets using user-click feedback. Abstract.
Yilmazcoban et al. (US 2020/0324206) discloses a method and system for assisting game-play of a user. The method and system includes a training module to train an Artificial Intelligence (AI)-based learning model based on a plurality of offline features and a plurality of online features. The plurality of offline features are extracted from one or more of data collected by one or more game developers, a plurality of Application Programming Interfaces (APIs) and a plurality of replay files associated with game-play. On the other hand, the plurality of online features are extracted from a screen state of the user. Further, the method and system includes a coaching module to coach the user in game-play utilizing the AI-based learning model using techniques such as, but not limited to, statistics, post-game analysis and progress tracking of game-play for optimizing the performance of the user, and generates one or more game-play suggestions for the user. Abstract.
Parkhe et al. (US 2022/0374457) discloses a method, system, and computer system for managing a plurality of features and storing lineage information pertaining to the features. The method includes obtaining one or more datasets, determining a first feature, wherein the first feature is determined based at least in part on the one or more datasets, and storing the first feature in a feature store. The first feature is stored in association with a dataset indication of the one or more datasets from which the first feature is determined. The feature store comprises a plurality of features. Abstract.
Jain et al. (US 2023/0196185) discloses a feature family system that, as part of an inter-network facilitation system, can intelligently generate and maintain a feature family repository for quickly and efficiently retrieving and providing machine learning features upon request. For example, the disclosed systems can generate a feature family repository as a centralized network location of feature references indicating network locations where different machine learning features are stored. In some cases, the disclosed systems identify a stored feature family that matches the request and retrieves the stored features from their respective network locations. The disclosed systems can generate feature families for online features as well as offline features and can automatically update feature values associated with various machine learning features on a period basis or in response to trigger events. Abstract.
Wisniewski et al. (US 2022/0044144) discloses techniques for a feature management platform to asynchronously implement an ensemble of machine learning models (or AI/ML models). The feature management platform can transmit feature data presently available on the feature queue (e.g., published on the feature queue or retrieved from a persistent data layer). The feature management platform can transmit the feature data to a first group of the machine learning models, capable of inputting the presently available feature data to generate predictions. The predictions can be transmitted back to the feature queue to consume—as well as store in the persistent data layer. The predictions, as well as any newly generated feature data, can be provided to the remaining machine learning models in the ensemble. The prediction of the ensemble can then be provided to a consumer (e.g., an organization). Abstract.
Polleri et al. (US 2021/0081848) discloses systems and methods for an adaptive pipelining composition service that can identify and incorporate one or more new models into the machine learning application. The machine learning application with the new model can be tested off-line with the results being compared with ground truth data. If the machine learning application with the new model outperforms the previously used model, the machine learning application can be upgraded and auto-promoted to production. One or more parameters may also be discovered. The new parameters may be incorporated into the existing model in an off-line mode. The machine learning application with the new parameters can be tested off-line and the results can be compared with previous results with existing parameters. If the new parameters outperform the existing parameters as compared with ground-truth data, the machine learning application can be auto-promoted to production. Abstract.
Rossi (US 2024/0004737) discloses evaluation of automated agents. One example includes a system having a processor and a storage medium. The storage medium can store instructions which, when executed by the processor, cause the system to perform two or more data gathering iterations, which can include distributing experimental units to a plurality of agents having different agent configurations according to a sampling strategy, populating an event log with events representing reactions of an environment to actions taken by individual agents in response to individual experimental units, and adjusting the sampling strategy for use in a subsequent data gathering iteration based at least on the events in the event log. The event log can provide a basis for subsequent evaluation of the plurality of agents with respect to one or more evaluation metrics. Abstract.
Delgado et al. (US Patent 11,244,244) discloses machine learning ranking. An example computing method includes receiving a search query and determining a plurality of machine learning model execution engines based on the search query and a plurality of search result types. The example computing method further includes generating a plurality of subsets of search results based on the search query and the plurality of machine learning model execution engines. The example computing method further includes generating a set of search results comprising at least one search result from each of the plurality of subsets of search results. Abstract. In some embodiments, these and other embodiments described herein provide for at least two techniques for offline model development to influence online model development: (i) publishing a model to flux prod and run an experiment in an optimization and insights platform for paid media channels; and (ii) publishing new features to a feature store, which provides access to a batch API and a real-time API that both serve the same data. In some instances, the embedded execution engine of Flux may be configured to accept a number of feature vectors as its inputs. In some instances, the machine learning raking system may be configured to contain feature transformation information, feature generation information, any other suitable feature information, or a combination thereof. In some instances, all data in elastic search indexes is populated by an indexer, such as an indexer comprised by the machine learning ranking system. In some instances, user data, deal data, and other data that is used by the Embedded Scoring is in the form of Feature Vectors. Col 5:3-21.
Markey et al. (US 2014/0046777) discloses systems and methods are disclosed for creating a digital consumer profile that may be dynamically and transiently generated, drawing upon attribute data that is available at time of the digital consumer profile creation. The digital consumer profile may further provide for dynamic and transient generations of a plurality of user profiles to fit definitions and use cases not anticipated at the outset of targeting or attribution efforts and attribute data collection. Regulatory conditions, privacy policies, enterprise rules and the like may determine, at least in part, the collection, analysis, and auditing of attribute data, and the merging of such data to form aliases that may be associated with consumers. The digital consumer service may comprise binding expression syntax to dynamically, and transiently, identify profiles to give flexibility and extensibility beyond having a flat match table. Abstract.
While the prior arts of record disclose trigger event, enriched event, algorithm logic, detecting trigger event and enriched event, event data describing the trigger event and enriched event, digital services of executable service platform in an online environment, offline, algorithm simulation operation, and storing the trigger data,
the prior arts of record, alone or in combination, neither anticipates, nor reasonable teaches, nor renders obvious, all of the following limitations of independent claims 1 and 11, when considered as a whole, of a method comprising: receiving trigger data defining a trigger event and logic to add an enriched event associated with the trigger event; detecting occurrence of the trigger event in execution of one or more digital services by an executable service platform in an online operational environment of a service provider system based on the trigger data; generating event data describing the execution of the trigger event and the enriched event responsive to the detecting based on the logic of the trigger data; storing the event data within an offline simulation environment; simulating operation of the executable service platform offline using the event data; and outputting a result of the simulating for display in a user interface. The prior arts of record, alone or in combination, neither anticipates, nor reasonable teaches, nor renders obvious, all of the following limitations of independent claim 19, when considered as a whole, of one or more computer-readable storage media storing instructions that, responsive to execution by a processing device, causes the processing device to perform operations including: receiving trigger data defining a trigger event and logic to add an enriched event associated with the trigger event; detecting occurrence of the trigger event in execution of one or more digital services by an executable service platform in an online operational environment of a service provider system based on the trigger data; generating event data describing the execution of the trigger event and the enriched event responsive to the detecting based on the logic of the trigger data; and executing a machine learning model, the executing simulating operation of the executable service platform offline using the event data.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. US-20160147754-A1, US-20230205775-A1, US-10140339-B, US-20220066905-A1, US-20240289261-A1.
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/BARBARA M LEVEL/ Examiner, Art Unit 2142
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