DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claims 1-24 are presented for examination based on the application filed on May 8, 2023.
Claims 1-24 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to judicial exception, an abstract idea, and it has not been integrated into practical application. The claims further do not recite significantly more than the judicial exception.
Claims 1-2, 9-10, and 17-18 are rejected under 35 U.S.C. § 102(a)(1) as being anticipated by Cheng, Bin, Zizhen Wu, and Zhongkui Li. "Distributed edge-based event-triggered formation control." IEEE transactions on cybernetics 51, no. 3 (2019): 1241-1252 [herein “Cheng”].
Claims 3-8, 11-16, and 19-24 are rejected under 35 U.S.C. § 103 as being unpatentable over Cheng, as applied to claims 1, 9, and 17, and in further view of Hall, Eric C., and Rebecca M. Willett. "Tracking dynamic point processes on networks." IEEE Transactions on Information Theory 62, no. 7 (2016): 4327-4346 [herein “Hall”].
This action is made non-Final.
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 .
Information Disclosure Statement
The information disclosure statement (IDS) submitted on September 11, 2024 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
Drawings
The drawings are objected to because FIG. 2-18 and 21-25 are not easily discernable due to the lack of resolution. Corrected drawing sheets in compliance with 37 CFR 1.121(d) are required in reply to the Office action to avoid abandonment of the application. Any amended replacement drawing sheet should include all of the figures appearing on the immediate prior version of the sheet, even if only one figure is being amended. The figure or figure number of a n amended drawing should not be labeled as “amended.” If a drawing figure is to be canceled, the appropriate figure must be removed from the replacement sheet, and where necessary, the remaining figures must be renumbered and appropriate changes made to the brief description of the several views of the drawings for consistency. Additional replacement sheets may be necessary to show the renumbering of the remaining figures. Each drawing sheet submitted after the filing date of an application must be labeled in the top margin a s either “Replacement Sheet” or “New Sheet” pursuant to 37 CFR 1.121(d). If the changes are not accepted by the examiner, the applicant will be notified and informed of any required corrective action in the next Office action. The objection to the drawings will not be held in abeyance.
Specification
The disclosure is objected to because of the following informalities:
Para. 0005, which cites “mis specified”, should be “misspecified”.
Para. 0067 recites the acronym “API”. Acronyms should be spelled out the first time that they appear.
Para. 00204, which cites “AS400”, should be “AS/400”.
Para. 00204, which cites “A DEC VAX”, should be “a DEC VAX”.
Para. 00204, which cites “HP3000”, should be “HP 3000”.
The use of the terms “IBM”, “HP”, “Honeywell”, “Texas Instruments”, “raspberry pi”, “big.LITTLE”, “AMD”, “CompactFlash”, “InfiniBand”, “RapidIO”, “Thunderbolt”, “IEEE”, “DVD”, “Blu-ray”, “WiMax”, and “LTE”, which are trade names or marks used in commerce, has been noted in this application. The terms should be accompanied by the generic terminology; furthermore the terms should be capitalized wherever it appears or, where appropriate, include a proper symbol indicating use in commerce such as ™, SM , or ® following the term. Although the use of trade names and marks used in commerce (i.e., trademarks, service marks, certification marks, and collective marks) are permissible in patent applications, the proprietary nature of the marks should be respected and every effort made to prevent their use in any manner which might adversely affect their validity as commercial marks.
Appropriate correction is required.
Claim Objections
Claims 2-8, 13-14, and 20-21 are objected to because of the following informality: recitations of elements with no previous recitations. For example, claim 2, “the instructions” in Ln. 1, is improper because there has been no previous recitation of “the instructions”. For the purpose of examination, “the instructions” will be interpreted as “the machine-readable instructions”. Claims 3-4 and 7-8, having similar limitations of claim 2, are also objected. Similarly, the following are objected under similar rationale:
Claim 4, “an actor function” in Ln. 8 should be “the actor function”.
Claim 5, “the graph-based mathematical model” in Ln. 1 should be “the actor graph-based mathematical model”. Claim 6, having similar limitations of claim 5, is also objected.
Claim 5, “an actor” in Ln. 5 should be “the actor”. Claims 13 and 20, having similar limitations of claim 5, are also objected.
Claim 5, “a process” in Ln. 9 should be “the process”. Claims 13 and 20, having similar limitations of claim 5, are also objected.
Claim 6, “a future event jet” in Ln. 6 should be “the future event jet”. Claims 14 and 21, having similar limitations of claim 5, are also objected.
Claim 6, “a past event jet” in Ln. 7 should be “the past event jet”. Claims 14 and 21, having similar limitations of claim 5, are also objected.
All claims dependent on an objected base claim are objected based on their dependency.
Appropriate correction is required.
Claim Rejections - 35 U.S.C. § 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 1-24 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to judicial exception, an abstract idea, and it has not been integrated into practical application. The claims further do not recite significantly more than the judicial exception. Examiner has evaluated the claims under the framework provided in the 2019 Patent Eligibility Guidance published in the Federal Register 01/07/2019 and has provided such analysis below.
Step 1:
Claims 1-8 are directed to a system and fall within the statutory category of a machine; claims 9-16 are directed to a method and fall within the statutory category of a process; and claims 17-24 are directed to a non-transitory computer readable medium and fall within the statutory category of articles of manufacture. Therefore, “Are the claims to a process, machine, manufacture or composition of matter?” Yes.
In order to evaluate the Step 2A inquiry “Is the claim directed to a law of nature, a natural phenomenon or an abstract idea?” we must determine, at Step 2A Prong 1, whether the claim recites a law of nature, a natural phenomenon or an abstract idea and further whether the claim recites additional elements that integrate the judicial exception into a practical application.
Step 2A Prong 1:
Claims 1, 9, and 17: The limitations of:
“acquire object-related data of an object to be modeled”,
“generate a plurality of modeling parameters based on the object-related data”,
“convert the plurality of modeling parameters into an actor graph data structure simulating the object and generate a model of the object comprising a graph”,
“parse the simulation request to derive the at least one new modeling parameter”,
“input the at least one new modeling parameter into the model”, and
“receive at least one simulated output from the model comprising a new value of an endogenous parameter”, as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with pen and paper. For example, the limitations can be performed as the following:
a person can mentally identify or draw with a pen and paper attributes of a process such as the type of assets used to transfer a primary property between two individuals,
a person can mentally determine or draw with a pen and paper that the type of assets such as cash and deed of an existing property used to transfer the primary property as parameters of the process,
a person can mentally generate or draw with a pen and paper an actor node graph of the process of transferring the new property using the individuals as nodes/actors and the transfer of assets as the edges of the actor node graph,
a person can mentally identify or draw with a pen and paper based on new information on the process that the type of asset used to transfer the primary property such as a mortgage loan,
a person can mentally update or draw with a pen and paper the actor node graph of the process of transferring the new property by adding new individuals and entities based on the new information of the mortgage loan such as a bank and also update the respective edges, and
a person can mentally determine or draw with a pen and paper from the updated actor node graph that the time to transfer the new property will take 45 days to complete using cash and mortgage loan as the parameter.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with pen and paper but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea under Prong I step 2A.
Therefore, yes, claims 1, 9, and 17 recite judicial exceptions. The claims have been identified to recite judicial exceptions, Step 2A Prong 2 will evaluate whether the claims are directed to the judicial exception.
Step 2A Prong 2:
Claims 1, 9, and 17: The judicial exception is not integrated into a practical application. In particular, the claims recite the following additional elements: “A system, comprising: a processor of a graph processing node connected to at least one user node over a network; a memory on which are stored machine-readable instructions that when executed by the processor” and “A non-transitory computer readable medium comprising instructions, that when read by a processor”, which is merely a recitation of generic computing components and functions being used as a tool to implement the judicial exception (see MPEP § 2106.05(f)) with the broadest reasonable interpretation, which does not integrate a judicial exception into elements. Further, the following additional element of “receive a simulation request comprising at least one new modeling parameter comprising a graph status or a structure change from the at least one user node” which is merely a recitation of insignificant extra-solution data gathering activity (see MPEP § 2106.05(g)) which does not integrate a judicial exception into practical application. The insignificant extra-solution activities are further addressed below under step 2B as also being Well-Understood, Routine, and Conventional (WURC).
Therefore, “Do the claims recite additional elements that integrate the judicial exception into a practical application?” No, these additional elements do not integrate the abstract idea into a practical application and they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
After having evaluated the inquires set forth in Steps 2A Prong 1 and 2, it has been concluded that claims 1, 9, and 17 not only recite a judicial exception but that the claims are directed to the judicial exception as the judicial exception has not been integrated into practical application.
Step 2B:
Claims 1, 9, and 17: The claims do not include additional elements, alone or in combination, that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements amount to no more than generic computing components which do not amount to significantly more than the abstract idea. Further, the insignificant extra-solution data gathering, record update, and data transmission activities are also Well-Understood, Routine and Conventional (see MPEP § 2106.05(d)(II), “The courts have recognized the following computer functions as well understood, routine, and conventional functions when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity. i. Receiving or transmitting data over a network, ii. Performing repetitive calculations, iii. Electronic recordkeeping, iv. Storing and retrieving information in memory”).
Therefore, “Do the claims recite additional elements that amount to significantly more than the judicial exception?” No, these additional elements, alone or in combination, do not amount to significantly more than the judicial exception. Having concluded the analysis within the provided framework, claims 1, 9, and 17 do not recite patent eligible subject matter under 35 U.S.C. § 101.
Regarding claims 2, 10, and 18, they recite an additional limitation of “acquire object-related data directly from the object, wherein the object-related data comprises a plurality of exogenous variables”, as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with pen and paper. For example, a person can mentally identify or draw with a pen and paper attributes of a process such as the type of assets used to transfer a primary property between two individuals by looking first-hand at the process to find the provided assets.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with pen and paper but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea under Prong I step 2A.
Furthermore, regarding claims 2, 10, and 18, they recite an additional element recitation of “wherein the instructions further cause the processor to” and “further comprising instructions, that when read by the processor, cause the processor” which is merely a recitation of generic computing components and functions being used as a tool to implement the judicial exception (see MPEP § 2106.05(f)) which does not integrate a judicial exception into practical application. Further, these claims do not recite any further additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, these claims also fail both Step 2A prong 2, thus the claims are directed to the judicial exception as they have not been integrated into practical application, and fail Step 2B as not amounting to significantly more. Therefore, claims 2, 10, and 18 do not recite patent eligible subject matter under 35 U.S.C. § 101.
Regarding claims 3 and 11, they recite an additional limitation of “acquire stored object-related data from a database”, as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with pen and paper. For example, a person can mentally identify or draw with a pen and paper attributes of a process such as the type of assets used to transfer a primary property between two individuals by looking at the process archive to find the provided assets.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with pen and paper but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea under Prong I step 2A.
Furthermore, regarding claims 3 and 11, they recite an additional element recitation of “wherein the instructions further cause the processor to” which is merely a recitation of generic computing components and functions being used as a tool to implement the judicial exception (see MPEP § 2106.05(f)) which does not integrate a judicial exception into practical application. Further, these claims do not recite any further additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, these claims also fail both Step 2A prong 2, thus the claims are directed to the judicial exception as they have not been integrated into practical application, and fail Step 2B as not amounting to significantly more. Therefore, claims 3 and 11 do not recite patent eligible subject matter under 35 U.S.C. § 101.
Regarding claims 4, 12, and 19, they recite an additional limitation of “generate an actor graph-based mathematical model comprising: actor graph comprising graph nodes and edges; graph nodes comprising actors; graph edges comprising edge actors; an actor comprising actor function, external and internal events, a future event jet, a past event jet, trigger rings and an account tree; and an actor function comprising a process or another actor or another actor graph”, as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with pen and paper. For example, a person can mentally generate or draw with a pen and paper an actor node graph of the process of transferring the new property using the individuals as nodes/actors having actions for past and future steps in the process which have their own steps when triggered in a process tree and the transfer of assets as the edges of the actor node graph where assets are numerically summed and fees are subtracted to create a mathematical model of the process.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with pen and paper but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea under Prong I step 2A.
Furthermore, regarding claims 4, 12, and 19, they recite an additional limitations of “generate an actor graph-based mathematical model comprising: actor graph comprising graph nodes and edges; graph nodes comprising actors; graph edges comprising edge actors; an actor comprising actor function, external and internal events, a future event jet, a past event jet, trigger rings and an account tree; and an actor function comprising a process or another actor or another actor graph” as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation of mathematical evaluations. For example, calculating the time and cash to close to complete a process of a transfer of a new property can be accomplished by representing the process as a mathematical node graph using the individuals as nodes/actors having actions for past and future steps in the process which have their own steps when triggered in a process tree and the transfer of assets as the edges of the actor node graph where assets and days are numerically summed and fees are subtracted to create a mathematical model of the process (Para 0003, “A mathematical model differs from the more tangible physical model, in that "reality" is represented by an equation or series of equations. There are many kinds of models. For example, econometric models have their basis in economic theory, are derived using statistical techniques, and are used in studying relationships among economic variables. Two important elements of equations are variables and parameters. Variables represent the elements of the system being modeled (e.g., the number of cars or trucks in a certain state). In a mathematical model the values of some variables may be specified outside the model. These variables are called exogenous variables or parameters.” Further see Para. 0004-0006, 0052-0053, and 0061-0065).
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation of mathematic evaluations but for the recitation of generic computer components, then it falls within the “Mathematical Operation” grouping of abstract ideas. Accordingly, the claim recites an abstract idea under Prong I step 2A.
Furthermore, regarding claims 4, 12, and 19, they recite an additional element recitation of “wherein the instructions further cause the processor to” and “further comprising instructions, that when read by the processor, cause the processor” which is merely a recitation of generic computing components and functions being used as a tool to implement the judicial exception (see MPEP § 2106.05(f)) which does not integrate a judicial exception into practical application. Further, these claims do not recite any further additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, these claims also fail both Step 2A prong 2, thus the claims are directed to the judicial exception as they have not been integrated into practical application, and fail Step 2B as not amounting to significantly more. Therefore, claims 4, 12, and 19 do not recite patent eligible subject matter under 35 U.S.C. § 101.
Regarding claims 5, 13, and 20, they recite an additional limitation of “wherein the graph-based mathematical model comprises an event actor comprising: event accounts storing: time, posterior probability, prior probability, and location; an event structure specified by: an actor; a file; a form; a tag; a process; a parent event comprising child event; a trigger; and event end time and date”, as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with pen and paper. For example, a person can mentally generate or draw with a pen and paper an actor node graph of the process of transferring the new property using the individuals as nodes/actors having actions for past and future steps in the process which have their own steps when triggered in a process tree and the transfer of assets along with the time, place and probability of new steps occurring before and after the transfer as the edges of the actor node graph where assets are numerically summed and fees are subtracted to create a mathematical model of the process having information such as a file, form, and tag.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with pen and paper but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea under Prong I step 2A.
Furthermore, regarding claims 5, 13, and 20, they recite an additional limitations of “wherein the graph-based mathematical model comprises an event actor comprising: event accounts storing: time, posterior probability, prior probability, and location; an event structure specified by: an actor; a file; a form; a tag; a process; a parent event comprising child event; a trigger; and event end time and date” as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation of mathematical evaluations. For example, calculating the time and cash to close to complete a process of a transfer of a new property can be accomplished by representing the process as a mathematical node graph using the individuals as nodes/actors having actions for past and future steps in the process which have their own steps when triggered in a process tree and the transfer of assets along with the time, place and probability of new steps occurring before and after the transfer as the edges of the actor node graph where assets are numerically summed and fees are subtracted to create a mathematical model of the process having information such as a file, form, and tag (Para 0003, “A mathematical model differs from the more tangible physical model, in that "reality" is represented by an equation or series of equations. There are many kinds of models. For example, econometric models have their basis in economic theory, are derived using statistical techniques, and are used in studying relationships among economic variables. Two important elements of equations are variables and parameters. Variables represent the elements of the system being modeled (e.g., the number of cars or trucks in a certain state). In a mathematical model the values of some variables may be specified outside the model. These variables are called exogenous variables or parameters.” Further see Para. 0004-0006, 0052-0053, and 0061-0065).
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation of mathematic evaluations but for the recitation of generic computer components, then it falls within the “Mathematical Operation” grouping of abstract ideas. Accordingly, the claim recites an abstract idea under Prong I step 2A.
Furthermore, regarding claims 5, 13, and 20, they recite an additional element recitation of “further comprising instructions, that when read by the processor, cause the processor” which is merely a recitation of generic computing components and functions being used as a tool to implement the judicial exception (see MPEP § 2106.05(f)) which does not integrate a judicial exception into practical application. Further, these claims do not recite any further additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, these claims also fail both Step 2A prong 2, thus the claims are directed to the judicial exception as they have not been integrated into practical application, and fail Step 2B as not amounting to significantly more. Therefore, claims 5, 13, and 20 do not recite patent eligible subject matter under 35 U.S.C. § 101.
Regarding claims 6, 14, and 21, they recite an additional limitation of “wherein the graph-based mathematical model comprises a trigger actor comprising: a trigger; processes; accounts; a future event jet; a past event jet; events ring; events flow; and trigger events”, as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with pen and paper. For example, a person can mentally generate or draw with a pen and paper an actor node graph of the process of transferring the new property using the individuals as nodes/actors having actions for past and future steps in the process which have their own steps when triggered in an account tree and the transfer of assets as the edges of the actor node graph where assets are numerically summed and fees are subtracted to create a mathematical model of the process.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with pen and paper but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea under Prong I step 2A.
Furthermore, regarding claims 6, 14, and 21, they recite an additional limitations of “wherein the graph-based mathematical model comprises a trigger actor comprising: a trigger; processes; accounts; a future event jet; a past event jet; events ring; events flow; and trigger events” as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation of mathematical evaluations. For example, calculating the time and cash to close to complete a process of a transfer of a new property can be accomplished by representing the process as a mathematical node graph using the individuals as nodes/actors having actions for past and future steps in the process which have their own steps when triggered in an account tree and the transfer of assets as the edges of the actor node graph where assets and days are numerically summed and fees are subtracted to create a mathematical model of the process (Para 0003, “A mathematical model differs from the more tangible physical model, in that "reality" is represented by an equation or series of equations. There are many kinds of models. For example, econometric models have their basis in economic theory, are derived using statistical techniques, and are used in studying relationships among economic variables. Two important elements of equations are variables and parameters. Variables represent the elements of the system being modeled ( e.g., the number of cars or trucks in a certain state). In a mathematical model the values of some variables may be specified outside the model. These variables are called exogenous variables or parameters.” Further see Para. 0004-0006, 0052-0053, and 0061-0065).
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation of mathematic evaluations but for the recitation of generic computer components, then it falls within the “Mathematical Operation” grouping of abstract ideas. Accordingly, the claim recites an abstract idea under Prong I step 2A.
Furthermore, regarding claims 6, 14, and 21, they recite an additional element recitation of “further comprising instructions, that when read by the processor, cause the processor” which is merely a recitation of generic computing components and functions being used as a tool to implement the judicial exception (see MPEP § 2106.05(f)) which does not integrate a judicial exception into practical application. Further, these claims do not recite any further additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, these claims also fail both Step 2A prong 2, thus the claims are directed to the judicial exception as they have not been integrated into practical application, and fail Step 2B as not amounting to significantly more. Therefore, claims 6, 14, and 21 do not recite patent eligible subject matter under 35 U.S.C. § 101.
Regarding claims 7, 15, and 22, they recite an additional limitation of “generate an actor graph-based model comprising: an actor life cycle; an event life cycle; a trigger life cycle; and a null actor life cycle”, as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with pen and paper. For example, a person can mentally generate or draw with a pen and paper an actor node graph of the process of transferring the new property using the individuals as nodes/actors having actions for past and future steps in the process and the transfer of assets as the edges of the actor node graph where nodes and edges produced new nodes and edges when triggered in a process tree by certain criteria meet by existing nodes and edges are performed and no new nodes and edges are produced when the trigger criteria is not met.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with pen and paper but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea under Prong I step 2A.
Furthermore, regarding claims 7, 15, and 22, they recite an additional element recitation of “wherein the instructions further cause the processor to” and “further comprising instructions, that when read by the processor, cause the processor” which is merely a recitation of generic computing components and functions being used as a tool to implement the judicial exception (see MPEP § 2106.05(f)) which does not integrate a judicial exception into practical application. Further, these claims do not recite any further additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, these claims also fail both Step 2A prong 2, thus the claims are directed to the judicial exception as they have not been integrated into practical application, and fail Step 2B as not amounting to significantly more. Therefore, claims 7, 15, and 22 do not recite patent eligible subject matter under 35 U.S.C. § 101.
Regarding claims 8 and 24, they recite an additional limitation of “generate an actor graph-based model comprising a horizontal and vertical convection of events through trigger rings of trigger actors”, as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with pen and paper. For example, a person can mentally generate or draw with a pen and paper an actor node graph of the process of transferring the new property using the individuals as nodes/actors having actions for past and future steps in the process (vertical) and the transfer of assets as the edges of the actor node graph as well as new nodes and edges are produced when triggered in a process tree by certain criteria meet by existing nodes and edges are performed (horizontal).
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with pen and paper but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea under Prong I step 2A.
Furthermore, regarding claims 8 and 24, they recite an additional element recitation of “wherein the instructions further cause the processor to” and “further comprising instructions, that when read by the processor, cause the processor” which is merely a recitation of generic computing components and functions being used as a tool to implement the judicial exception (see MPEP § 2106.05(f)) which does not integrate a judicial exception into practical application. Further, these claims do not recite any further additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, these claims also fail both Step 2A prong 2, thus the claims are directed to the judicial exception as they have not been integrated into practical application, and fail Step 2B as not amounting to significantly more. Therefore, claims 8 and 24 do not recite patent eligible subject matter under 35 U.S.C. § 101.
Regarding claims 16 and 23, they recite an additional limitation of “generating an actor graph-based model based on a null graph and a plurality of graph layers”, as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with pen and paper. For example, a person can mentally generate or draw with a pen and paper an actor node graph of the process of transferring the new property using the individuals as nodes/actors having actions for past and future steps in the process (layers) and the transfer of assets as the edges of the actor node graph where nodes and edges produced new nodes and edges when triggered in a process tree by certain criteria meet by existing nodes and edges are performed and no new nodes and edges are produced when the trigger criteria is not met.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind or with pen and paper but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claim recites an abstract idea under Prong I step 2A.
Furthermore, regarding claims 16 and 23, they recite an additional element recitation of “further comprising instructions, that when read by the processor, cause the processor” which is merely a recitation of generic computing components and functions being used as a tool to implement the judicial exception (see MPEP § 2106.05(f)) which does not integrate a judicial exception into practical application. Further, these claims do not recite any further additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, these claims also fail both Step 2A prong 2, thus the claims are directed to the judicial exception as they have not been integrated into practical application, and fail Step 2B as not amounting to significantly more. Therefore, claims 16 and 23 do not recite patent eligible subject matter under 35 U.S.C. § 101.
Therefore, having concluded the analysis within the provided framework, claims 1-24 do not recite patent eligible subject matter and are rejected under 35 U.S.C. § 101 because the claimed invention is directed to judicial exception, an abstract idea, that has not been integrated into a practical application. The claims further do not recite significantly more than the judicial exception. Claims 2-8, 10-16, and 18-24 are also rejected for incorporating the deficiency of their dependent claims 1, 9, and 17, respectively.
Claim Rejections - 35 U.S.C. § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. § 102 and 103 (or as subject to pre-AIA 35 U.S.C. § 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. § 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-2, 9-10, and 17-18 are rejected under 35 U.S.C. § 102(a)(1) as being anticipated by Cheng, Bin, Zizhen Wu, and Zhongkui Li. "Distributed edge-based event-triggered formation control." IEEE transactions on cybernetics 51, no. 3 (2019): 1241-1252 [herein “Cheng”].
As per claim 1, Cheng teaches “A system, comprising: a processor of a graph processing node connected to at least one user node over a network; a memory on which are stored machine-readable instructions that when executed by the processor”. (Pg. 1249 Sect. V, “We do the simulation for time t from 0 to 30 s with a computing frequency of 200 Hz using the MATLAB software” [e.g., a system, comprising: a processor and a memory on which are stored machine-readable instructions that when executed by the processor]. Pg. 1242 Sect. II “The N agents are networked by an undirected graph G = (V, E), where V = {1, . . . ,N} denotes the node set and E ⊆V × V denotes the edge set” [i.e., graph processing node]. Pg. 1242 Sect. I, “It is shown that all the four kinds of edge-based event-triggered protocols are able to ensure the achievement of given formation structures and the exclusion of the Zeno behavior. We propose both the state-based and output-based event-driven algorithms in order to provide more choices for users” and Pg. 1249-1250 Sect. V, “In simulation, we also consider the case where there exist changes of the formation structures. For example, the formation structure is switched at 30 s… This result is very important since under the proposed protocols, multiagent systems can change their formation structures according to practical occasions” [e.g., graph processing node connected to at least one user node over a network]. Further see Sect. I-II & V. The examiner has interpreted that simulating using a computing frequency and MATLAB® software to create formations structure of agents as nodes with edges and change the formation structure according to a practical occasion using algorithms provided to users as a system, comprising: a processor of a graph processing node connected to at least one user node over a network; a memory on which are stored machine-readable instructions that when executed by the processor.)
Cheng teaches “acquire object-related data of an object to be modeled”. (Pg. 1242 Sect. I, “Motivated by the above discussions, we study the formation control of general linear models subject to event-triggered communications. Several edge-based event-triggered protocols are presented to solve this problem” [a formation of a network, i.e., an object to be modeled]. Pg. 1243, Sect. II, “This paper aims to design event-driven algorithms under which formation can be achieved in the sense of limt→∞ ||(xi(t) − hi) − (xj(t) – hj)|| = 0, where hi ∈ Rn is the formation variable of agent i” [variables of a formation of an agent network, i.e., acquire object-related data of an object to be modeled]. Furthermore, Pg. 1244 Sect. III, “Theorem 1 indicates that formation structures will be achieved as long as the constrains Ahi = 0, i = 1, . . . ,N, are satisfied”. Further see Sect. I-III. The examiner has interpreted that designing algorithms to achieve a formation that stratifies constraints of formation variables for the formation control of agents in a linear model as acquire object-related data of an object to be modeled.)
Cheng teaches “generate a plurality of modeling parameters based on the object-related data; convert the plurality of modeling parameters into an actor graph data structure simulating the object and generate a model of the object comprising a graph”. (Pg. 1249 Sect. V, “Let hi = [hri hsi], where hri ∈ R3 and hsi ∈ R3, respectively, represent the bias of positions and velocities. We select hsi = [0, 0, 0]T , i = 1, . . . , 8. Then, the formation variables are selected as: hr1 = [1, 0, 0]T , hr2 = [1 +
2
, 0, 0]T , hr3 = [0, 0, 1]T , hr4 = [2+
2
, 0, 1]T , hr5 = [0, 0, 1+
2
]T , hr6 = [2 + 2
2
, 0, 1 +
2
]T , hr7 = [1, 0, 2 +
2
]T , and hr8 = [1+
2
, 0, 2+
2
]T. Evidently, the assumption Ahi = 0, i = 1, . . . , 8, is satisfied” [generate a plurality of modeling parameters based on the object-related data]. “In fact, the expected formation is a regular octagon in 3-D space” [convert the plurality of modeling parameters into an actor graph data structure simulating the object]. Fig. 1 shows the communication graph of the network of agents in a node graph and Pg. 1249 Sect. V, “The topology associated with the eight agents is described by Fig. 1, which is obviously connected” [generate a model of the object comprising a graph]. Further see Sect. V. The examiner has interpreted that selecting formation variables to satisfy the constraints and where the expected formation is provided in 3-D space and described with a topology of the eight agents in a node graph as generate a plurality of modeling parameters based on the object-related data; convert the plurality of modeling parameters into an actor graph data structure simulating the object and generate a model of the object comprising a graph.)
Cheng teaches “receive a simulation request comprising at least one new modeling parameter comprising a graph status or a structure change from the at least one user node”. (Pg. 1242 Sect. I, “It is shown that all the four kinds of edge-based event-triggered protocols are able to ensure the achievement of given formation structures and the exclusion of the Zeno behavior. We propose both the state-based and output-based event-driven algorithms in order to provide more choices for users” and Pg. 1249-1250 Sect. V, “In simulation, we also consider the case where there exist changes of the formation structures. For example, the formation structure is switched at 30 s… This result is very important since under the proposed protocols, multiagent systems can change their formation structures according to practical occasions” [receive a simulation request comprising at least one new modeling parameter comprising a structure change from the at least one user node]. Furthermore, Pg. 1242 Sect. I, “It is to be pointed out that under the proposed protocols, formation structures can be switched according to practical occasions or emergency situations”. Further see Sect. I & V. The examiner has interpreted that switching formulation structure to cause changes according to practical occasions using algorithms provided to users as receive a simulation request comprising at least one new modeling parameter comprising a graph status or a structure change from the at least one user node.)
Cheng teaches “parse the simulation request to derive the at least one new modeling parameter; input the at least one new modeling parameter into the model; and receive at least one simulated output from the model comprising a new value of an endogenous parameter.” (Pg. 1249 Sect. V, “In simulation, we also consider the case where there exist changes of the formation structures. For example, the formation structure is switched at 30 s. New formation variables are listed as: h1 = [0, 0, 0, 0, 0, 0]T , h2 = [2, 0, 0, 0, 0, 0]T , h3 = [0, 0, 1, 0, 0, 0]T , h4 = [2, 0, 1, 0, 0, 0]T , h5 = [0, 0, 2, 0, 0, 0]T , h6 = [2, 0, 2, 0, 0, 0]T , h7 = [0, 0, 3, 0, 0, 0]T , and h8 = [2, 0, 3, 0, 0, 0]T” [parse the simulation request to derive the at least one new modeling parameter]. Agents’ positions ri for time from 30 to 50 s are represented in Fig. 7, which indicates the new formation structure can also be achieved” [input the at least one new modeling parameter into the model; and receive at least one simulated output from the model comprising a new value of an endogenous parameter]. Further see Sect. V. The examiner has interpreted that having a new formation variables when there exist a change to the formation structure and achieving the new formation structure having the positions of the agents as parse the simulation request to derive the at least one new modeling parameter, input the at least one new modeling parameter into the model, and receive at least one simulated output from the model comprising a new value of an endogenous parameter.)
As per claim 2, Cheng teaches “acquire object-related data directly from the object, wherein the object-related data comprises a plurality of exogenous variables”. (Pg. 1242 Sect. I, “Motivated by the above discussions, we study the formation control of general linear models subject to event-triggered communications. Several edge-based event-triggered protocols are presented to solve this problem” [a formation of a network, i.e., an object to be modeled]. Pg. 1243, Sect. II, “This paper aims to design event-driven algorithms under which formation can be achieved in the sense of limt→∞ ||(xi(t) − hi) − (xj(t) – hj)|| = 0, where hi ∈ Rn is the formation variable of agent i” [acquire object-related data directly from the object]. Furthermore, Pg. 1244 Sect. III, “Theorem 1 indicates that formation structures will be achieved as long as the constrains Ahi = 0, i = 1, . . . ,N, are satisfied” [i.e., wherein the object-related data comprises a plurality of exogenous variable]. Further see Sect. I-III. The examiner has interpreted that designing algorithms to achieve a formation that stratifies constraints of formation variables for the formation control of agents in a linear model as acquire object-related data directly from the object, wherein the object-related data comprises a plurality of exogenous variables.)
Re Claim 9, it is a method claim, having similar limitations of claim 1. Thus, claim 9 is also rejected under the similar rationale as cited in the rejection of claim 1.
Re Claim 10, it is a method claim, having similar limitations of claim 2. Thus, claim 10 is also rejected under the similar rationale as cited in the rejection of claim 2.
Re Claim 17, it is an articles of manufacture claim, having similar limitations of claim 1. Thus, claim 17 is also rejected under the similar rationale as cited in the rejection of claim 1.
Furthermore, regarding claim 17, “A non-transitory computer readable medium comprising instructions, that when read by a processor”. (Pg. 1249 Sect. V, “We do the simulation for time t from 0 to 30 s with a computing frequency of 200 Hz using the MATLAB software” [e.g., A non-transitory computer readable medium comprising instructions, that when read by a processor].)
Re Claim 18, it is an articles of manufacture claim, having similar limitations of claim 2. Thus, claim 18 is also rejected under the similar rationale as cited in the rejection of claim 2.
Claim Rejections - 35 U.S.C. § 103
The following is a quotation of 35 U.S.C. § 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. § 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. § 102(b)(2)(C) for any potential 35 U.S.C. § 102(a)(2) prior art against the later invention.
Claims 3-8, 11-16, and 19-24 are rejected under 35 U.S.C. § 103 as being unpatentable over Cheng, as applied to claims 1, 9, and 17, and in further view of Hall, Eric C., and Rebecca M. Willett. "Tracking dynamic point processes on networks." IEEE Transactions on Information Theory 62, no. 7 (2016): 4327-4346 [herein “Hall”].
As per claim 3, Cheng does not specifically teach “acquire stored object-related data from a database.”
However, in the same field of endeavor namely modeling interactions between actions and events using a graph, Hall teaches “acquire stored object-related data from a database.” (Pg. 4338 Sect. VII, “These 217 distinct websites made up our network of interest. We extracted the posts from these websites for a six month span from August 2008 through the end of January 2009, totaling over 3.5 million events. The only information considered was what websites were posting and at what times” [acquire stored object-related data from a database]. Further see Sect. VII. The examiner has interpreted that extracting information from websites which has posts and what times as acquire stored object-related data from a database.)
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add “acquire stored object-related data from a database” as conceptually seen from the teaching of Hall, into that of Cheng because this modification of database to acquire the information for the advantageous purpose of providing an online-based and improved event prediction algorithm using available information (Hall, Pg. 4329 Sect. III). Further motivation to combine be that Cheng and Hall are analogous art to the current claim as directed to modeling interactions between actions and events using a graph.
As per claim 4, Cheng teaches “generate an actor graph-based mathematical model comprising: actor graph comprising graph nodes and edges; graph nodes comprising actors; graph edges comprising edge actors”. (Pg. 1242-1243 Sect. II, “The N agents are networked by an undirected graph G =(V, E), where V = {1, . . . , N} denotes the node set and E ⊆V × V denotes the edge set. Under G, (i, j) ∈ E ⇔ (j, i) ∈ E, and we call agents i and j mutual neighbors, if (i, j) ∈ E. A path connected with nodes il and im is composed of a sequence of adjacent edges (il, il+1), l = 1, . . . , m − 1. If there exists a path between each pair of distinct nodes then the graph G is connected, otherwise is disconnected. A = [aij] is the adjacency matrix associated with the graph G, where aij = 1 if (j, i) ∈ E and aij = 0 otherwise” [i.e., generate an actor graph-based mathematical model comprising: actor graph comprising graph nodes and edges; graph nodes comprising actors; graph edges comprising edge actors]. Further see Sect. II. The examiner has interpreted that agents represented by the adjacency matrix in a graph networking agents in a node sets and a path connecting the nodes as edges as generate an actor graph-based mathematical model comprising: actor graph comprising graph nodes and edges; graph nodes comprising actors; graph edges comprising edge actors.)
Cheng teaches “an actor comprising actor function, [external and internal events, a future event jet, a past event jet,] trigger rings and an account tree; and an actor function comprising a process or another actor or another actor graph”. (Pg. 1243 Sect. III, “It is to be pointed out that existing triggering functions include node-based ones and edge-based ones … under edge-based event-triggered protocols, if an edge, like (i, j), is triggered, only agents i and j need to exchange their state information and update their control inputs” [i.e., an actor comprising actor function, and an actor function comprising a process]. Pg. 1243 Sect. III “the control inputs can be computed using (2) without requiring communications until the triggering function defined in (5) or (6) exceeds 0. In particular, when fij(t) ≥ 0 or fji(t) ≥ 0, the edge (i, j) is triggered, and agents i and j communicate state information between each other at once” [i.e., trigger rings and an account tree]. Further see Sect. III. The examiner has interpreted that using edge-based event-triggered protocols where adjacent agents communicate and share state information when a triggering function is trigged as an actor comprising actor function, trigger rings and an account tree, and an actor function comprising a process or another actor or another actor graph.)
Cheng does not specifically teach “an actor comprising external and internal events, a future event jet, a past event jet”.
However, Hall teaches “an actor comprising external and internal events, a future event jet, a past event jet”. (Pg. 4328 Sect. II, “We monitor p actors in a network, and record the identities of the actor and time of each event. An actor and event may represent a person “liking” a photo or article shared by another person in a social network, a neuron firing in the brain, or the incidence of disease. That is, we observe a time series of the form {kn, τn)}n, where kn ∈ {1, 2, . . . , p} is the actor involved in the nth event and τn ∈ R+ is the time at which it occurs. With each new event, we wish to accurately predict which future events are most likely in the immediate future and the underlying network of influence” [an actor comprising a future event jet and a past event jet]. Pg. 4340, Appendix B, “we make the distinction between two classes of events. The first set of events, An = {i |
τ
i
<
τ
n
,
τ
-
i
<
τ
-
n
}, are events that happen before the nth event and are not in the same time window. The second set, Bn = {i |
τ
i
<
τ
n
,
τ
-
i
=
τ
-
n
}, are events that happen before the nth event but in the same time window” [external and internal events]. Further see Sect. II and Appendix B. The examiner has interpreted that actors involved in a series of events located in same or different time windows and using new events to predict future events as an actor comprising external and internal events, a future event jet, a past event jet.)
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add “an actor comprising external and internal events, a future event jet, a past event jet” as conceptually seen from the teaching of Hall, into that of Cheng because this modification of including different, past, and future for the advantageous purpose of improving event predictions using available information (Hall, Pg. 4329 Sect. III). Further motivation to combine be that Cheng and Hall are analogous art to the current claim as directed to modeling interactions between actions and events using a graph.
As per claim 5, Cheng teaches “wherein the graph-based mathematical model comprises an event actor comprising: event accounts storing: [time, posterior probability, prior probability, and] location; an event structure specified by: [an actor; a file; a form; a tag;] a process; [a parent event comprising child event;] a trigger; [and event end time and date].” (Pg. 1242-1243 Sect. II, “The N agents are networked by an undirected graph G =(V, E), where V = {1, . . . , N} denotes the node set and E ⊆V × V denotes the edge set. Under G, (i, j) ∈ E ⇔ (j, i) ∈ E, and we call agents i and j mutual neighbors, if (i, j) ∈ E. A path connected with nodes il and im is composed of a sequence of adjacent edges (il, il+1), l = 1, . . . , m − 1. If there exists a path between each pair of distinct nodes then the graph G is connected, otherwise is disconnected. A = [aij] is the adjacency matrix associated with the graph G, where aij = 1 if (j, i) ∈ E and aij = 0 otherwise” [i.e., wherein the graph-based mathematical model comprises an event actor]. Pg. 1249 Sect. V, “We consider eight agents satisfying the dynamics (1), … where ri ∈ R3 and si ∈ R3, respectively, represent the positions and the velocities of agents” [comprising: event accounts storing location]. Pg. 1243 Sect. III, “It is to be pointed out that existing triggering functions include node-based ones and edge-based ones … under edge-based event-triggered protocols, if an edge, like (i, j), is triggered, only agents i and j need to exchange their state information and update their control inputs” [i.e., a process]. Pg. 1243 Sect. III “the control inputs can be computed using (2) without requiring communications until the triggering function defined in (5) or (6) exceeds 0. In particular, when fij(t) ≥ 0 or fji(t) ≥ 0, the edge (i, j) is triggered, and agents i and j communicate state information between each other at once” [i.e., trigger rings and an account tree]. Further see Sect. II-III & V. The examiner has interpreted that agents represented by the adjacency matrix in a graph networking agents in a node sets having positions and using edge-based event-triggered protocols where adjacent agents communicate and share state information when a triggering function is trigged as wherein the graph-based mathematical model comprises an event actor comprising: event accounts storing location; an event structure specified by: a processes; and a trigger.)
Cheng does not specifically teach “wherein the graph-based mathematical model comprises an event actor comprising: event accounts storing: time, posterior probability, prior probability; an event structure specified by: an actor; a file; a form; a tag; a parent event comprising child event; and event end time and date.”
However, Hall teaches “wherein the graph-based mathematical model comprises an event actor comprising: event accounts storing: time, posterior probability, prior probability; an event structure specified by: an actor; a file; a form; a tag; a process; a parent event comprising child event; and event end time and date.” (Pg. 4337, Sect. I, “We can model these interactions between nodes using a network or graph, where directed edge weights correspond to the degree to which one node’s activity stimulates activity in another node” [graph-based]. Pg. 4328 Sect. II, “We wish to track the time-varying likelihood of each of the p actors acting. To do so, we adopt a multivariate Hawkes process model [20]–[22] and track the parameters of this model over time” [the graph-based mathematical model]. Pg. 4328 Sect. II, “We monitor p actors in a network, and record the identities of the actor and time of each event. An actor and event may represent a person “liking” a photo or article shared by another person in a social network, a neuron firing in the brain, or the incidence of disease. That is, we observe a time series of the form {kn, τn)}n, where kn ∈ {1, 2, . . . , p} is the actor involved in the nth event and τn ∈ R+ is the time at which it occurs” [comprises an event actor comprising: event accounts storing: time and event structure specified by an actor; a process]. Pg. 4328 Sect. II, “Here
μ
-
k
is a baseline rate representing the nonzero likelihood of actor k acting even without having been influenced by any previous actions, with
μ
-
≜
μ
-
1
,
…
,
μ
-
p
T
” [prior probability]. “Furthermore, we have p2 functions of the form hk1,k2 (τ) which describe how events associated with actor k2 will impact the likelihood of events associated with actor k1” [posterior probability]. Pg. 4338 Sect. VII, “we used the raw phrases Memetracker [39] data set (http://www.memetracker.org/data.html) and extracted every post from websites analyzed by the authors as reporting a high percentage of important news (http://www.memetracker.org/lag.html)” [i.e., a file and form]. Pg. 4338 Sect. VII, “information considered was what websites were posting and at what times” [i.e., tag]. Pg. 4329 Sect. III, “Online learning techniques are generally based on the following paradigm: at every time point t we make a prediction, receive some data, and then do a few computationally inexpensive calculations to improve our previous prediction. In the setting of autoregressive event tracking, this means we would have an estimate about each actor’s likelihood of acting and then see who does act. Using the previous prediction, the current action, and information about the network itself, we update our belief of who is most likely to act next” [i.e., a parent event comprising child event]. Pg. 4330 Sect. III, “We introduce an approximation of the time varying rate function in the Hawkes process …To do this we define a new set of times
τ
-
n
n
, which are the ends of the discrete time intervals that the events occur” [event end time and date]. Further see Sect. I-III & VII. The examiner has interpreted that modeling interactions between nodes using a graph to adopt a multivariate Hawkes process model to track parameters of the model over time of actors in a network that like a photo involved in a series of events in a time series, where events are given a likelihood of occurring without and with previous actions and events, data used from through raw data sets extracted from html websites and specific websites were considered, likelihood is updated based on past predictions and actions, and events have discrete time intervals indicating when events end occurs as wherein the graph-based mathematical model comprises an event actor comprising: event accounts storing: time, posterior probability, prior probability; an event structure specified by: an actor; a file; a form; a tag; a process; a parent event comprising child event; and event end time and date.)
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add “wherein the graph-based mathematical model comprises an event actor comprising: event accounts storing: time, posterior probability, prior probability; an event structure specified by: an actor; a file; a form; a tag; a process; a parent event comprising child event; and event end time and date” as conceptually seen from the teaching of Hall, into that of Cheng because this modification of including various event data for the advantageous purpose of improving event predictions using available information (Hall, Pg. 4329 Sect. III). Further motivation to combine be that Cheng and Hall are analogous art to the current claim as directed to modeling interactions between actions and events using a graph.
Re Claim 6, it is a method claim, having similar limitations of claim 5. Thus, claim 6 is also rejected under the similar rationale as cited in the rejection of claim 5.
As per claim 7, Cheng teaches “generate an actor graph-based model comprising: an actor life cycle; [an event life cycle;] a trigger life cycle; and a null actor life cycle.” (Pg. 1242-1243 Sect. II, “The N agents are networked by an undirected graph G =(V, E), where V = {1, . . . , N} denotes the node set and E ⊆V × V denotes the edge set. Under G, (i, j) ∈ E ⇔ (j, i) ∈ E, and we call agents i and j mutual neighbors, if (i, j) ∈ E. A path connected with nodes il and im is composed of a sequence of adjacent edges (il, il+1), l = 1, . . . , m − 1. If there exists a path between each pair of distinct nodes then the graph G is connected, otherwise is disconnected. A = [aij] is the adjacency matrix associated with the graph G, where aij = 1 if (j, i) ∈ E and aij = 0 otherwise” [i.e., generate an actor graph-based model comprises an event]. Pg. 1243 Sect. III “the control inputs can be computed using (2) without requiring communications until the triggering function defined in (5) or (6) exceeds 0. In particular, when fij(t) ≥ 0 or fji(t) ≥ 0, the edge (i, j) is triggered, and agents i and j communicate state information between each other at once” [i.e., a trigger life cycle; and processes created by events, i.e. an actor life cycle and a null actor life cycle]. Further see Sect. II. The examiner has interpreted that agents represented by the adjacency matrix in a graph networking agents in a node sets using edge-based event-triggered protocols where adjacent agents communicate and share state information when a triggering function is trigged as generate an actor graph-based model comprising: an actor life cycle; a trigger life cycle; and a null actor life cycle.)
Cheng does not specifically teach “generate an actor graph-based model comprising an event life cycle”.
However, Hall teaches “generate an actor graph-based model comprising an event life cycle”. (Pg. 4337, Sect. I, “We can model these interactions between nodes using a network or graph, where directed edge weights correspond to the degree to which one node’s activity stimulates activity in another node” [graph-based]. Pg. 4328 Sect. II, “We wish to track the time-varying likelihood of each of the p actors acting. To do so, we adopt a multivariate Hawkes process model [20]–[22] and track the parameters of this model over time” [the graph-based mathematical model]. Pg. 4328 Sect. II, “We monitor p actors in a network, and record the identities of the actor and time of each event. An actor and event may represent a person “liking” a photo or article shared by another person in a social network, a neuron firing in the brain, or the incidence of disease. That is, we observe a time series of the form {kn, τn)}n, where kn ∈ {1, 2, . . . , p} is the actor involved in the nth event and τn ∈ R+ is the time at which it occurs” [generate an actor graph-based model]. Pg. 4328 Sect. II, “We monitor p actors in a network, and record the identities of the actor and time of each event. An actor and event may represent a person “liking” a photo or article shared by another person in a social network, a neuron firing in the brain, or the incidence of disease. That is, we observe a time series of the form {kn, τn)}n, where kn ∈ {1, 2, . . . , p} is the actor involved in the nth event and τn ∈ R+ is the time at which it occurs. With each new event, we wish to accurately predict which future events are most likely in the immediate future and the underlying network of influence” [an event life cycle]. Further see Sect. I-II. The examiner has interpreted that modeling interactions between nodes using a graph to adopt a multivariate Hawkes process model to track parameters of the model over time of actors in a network that like a photo involved in a series of events in a time series as generate an actor graph-based model comprising an event life cycle.)
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add “generate an actor graph-based model comprising an event life cycle” as conceptually seen from the teaching of Hall, into that of Cheng because this modification of including various event data for the advantageous purpose of improving event predictions using available information (Hall, Pg. 4329 Sect. III). Further motivation to combine be that Cheng and Hall are analogous art to the current claim as directed to modeling interactions between actions and events using a graph.
As per claim 8, Cheng does not specifically teach “generate an actor graph-based model comprising a horizontal and vertical convection of events through trigger rings of trigger actors.”
However, Hall teaches “generate an actor graph-based model comprising a horizontal and vertical convection of events through trigger rings of trigger actors.” (Pg. 4337, Sect. I, “We can model these interactions between nodes using a network or graph, where directed edge weights correspond to the degree to which one node’s activity stimulates activity in another node” [graph-based]. Pg. 4328 Sect. II, “We wish to track the time-varying likelihood of each of the p actors acting. To do so, we adopt a multivariate Hawkes process model [20]–[22] and track the parameters of this model over time” [the graph-based mathematical model]. Pg. 4328 Sect. II, “We monitor p actors in a network, and record the identities of the actor and time of each event. An actor and event may represent a person “liking” a photo or article shared by another person in a social network, a neuron firing in the brain, or the incidence of disease. That is, we observe a time series of the form {kn, τn)}n, where kn ∈ {1, 2, . . . , p} is the actor involved in the nth event and τn ∈ R+ is the time at which it occurs” [comprises an actor and external and internal events, i.e., a horizontal convection of events]. Pg. 4340, Appendix B, “we make the distinction between two classes of events. The first set of events, An = {i |
τ
i
<
τ
n
,
τ
-
i
<
τ
-
n
}, are events that happen before the nth event and are not in the same time window. The second set, Bn = {i |
τ
i
<
τ
n
,
τ
-
i
=
τ
-
n
}, are events that happen before the nth event but in the same time window” [external and internal events, e.g., vertical convection of events]. Pg. 4328 Sect. II, “Here
μ
-
k
is a baseline rate representing the nonzero likelihood of actor k acting even without having been influenced by any previous actions, with
μ
-
≜
μ
-
1
,
…
,
μ
-
p
T
. Furthermore, we have p2 functions of the form hk1,k2 (τ) which describe how events associated with actor k2 will impact the likelihood of events associated with actor k1” [through trigger rings of trigger actors]. Further see Sect. I-II and Appendix B. The examiner has interpreted that modeling interactions between nodes using a graph to adopt a multivariate Hawkes process model to track parameters of the model over time of actors in a network that like a photo involved in a series of events in a time series where events are given a likelihood of occurring without and with previous actions and events and are located in same or different time windows and using new events to predict future events as generate an actor graph-based model comprising a horizontal and vertical convection of events through trigger rings of trigger actors.)
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add “generate an actor graph-based model comprising a horizontal and vertical convection of events through trigger rings of trigger actors” as conceptually seen from the teaching of Hall, into that of Cheng because this modification of including various event data for the advantageous purpose of improving event predictions using available information (Hall, Pg. 4329 Sect. III). Further motivation to combine be that Cheng and Hall are analogous art to the current claim as directed to modeling interactions between actions and events using a graph.
Re Claim 11, it is a method claim, having similar limitations of claim 3. Thus, claim 11 is also rejected under the similar rationale as cited in the rejection of claim 3.
Re Claim 12, it is a method claim, having similar limitations of claim 4. Thus, claim 12 is also rejected under the similar rationale as cited in the rejection of claim 4.
Re Claim 13, it is a method claim, having similar limitations of claim 5. Thus, claim 13 is also rejected under the similar rationale as cited in the rejection of claim 5.
Re Claim 14, it is a method claim, having similar limitations of claim 6. Thus, claim 14 is also rejected under the similar rationale as cited in the rejection of claim 6.
Re Claim 15, it is a method claim, having similar limitations of claim 7. Thus, claim 15 is also rejected under the similar rationale as cited in the rejection of claim 7.
As per claim 16, Cheng does not specifically teach “generating an actor graph-based model based on a null graph and a plurality of graph layers.”
However, Hall teaches “generating an actor graph-based model based on a null graph and a plurality of graph layers”. (Pg. 4337, Sect. I, “We can model these interactions between nodes using a network or graph, where directed edge weights correspond to the degree to which one node’s activity stimulates activity in another node” [graph-based]. Pg. 4328 Sect. II, “We wish to track the time-varying likelihood of each of the p actors acting. To do so, we adopt a multivariate Hawkes process model [20]–[22] and track the parameters of this model over time” [the graph-based mathematical model]. Pg. 4328 Sect. II, “We monitor p actors in a network, and record the identities of the actor and time of each event. An actor and event may represent a person “liking” a photo or article shared by another person in a social network, a neuron firing in the brain, or the incidence of disease. That is, we observe a time series of the form {kn, τn)}n, where kn ∈ {1, 2, . . . , p} is the actor involved in the nth event and τn ∈ R+ is the time at which it occurs” [comprises an actor and external and internal events, i.e., a plurality of graph layers]. Pg. 4328 Sect. II, “These functions depend on the underlying network connectivity; if actors k1 and k2 are unconnected, the corresponding function hk1,k2 should be identically zero for all τ” [empty graph, i.e., a null graph]. Further see Sect. I-II. The examiner has interpreted that agents represented by the adjacency matrix in a graph networking agents in a node sets using edge-based event-triggered protocols where adjacent agents communicate and share state information when a triggering function is trigged and have a corresponding function of zero for all times in the time series when the nodes are unconnected as generating an actor graph-based model based on a null graph and a plurality of graph layers.)
Therefore, it would have been obvious to a person having ordinary skill in the art before the effective filing date of the claimed invention to add “generating an actor graph-based model based on a null graph and a plurality of graph layers” as conceptually seen from the teaching of Hall, into that of Cheng because this modification of including various event data for the advantageous purpose of improving event predictions using available information (Hall, Pg. 4329 Sect. III). Further motivation to combine be that Cheng and Hall are analogous art to the current claim as directed to modeling interactions between actions and events using a graph.
Re Claim 19, it is an articles of manufacture claim, having similar limitations of claim 4. Thus, claim 19 is also rejected under the similar rationale as cited in the rejection of claim 4.
Re Claim 20, it is an articles of manufacture claim, having similar limitations of claim 5. Thus, claim 20 is also rejected under the similar rationale as cited in the rejection of claim 5.
Re Claim 21, it is an articles of manufacture claim, having similar limitations of claim 6. Thus, claim 21 is also rejected under the similar rationale as cited in the rejection of claim 6.
Re Claim 22, it is an articles of manufacture claim, having similar limitations of claim 7. Thus, claim 22 is also rejected under the similar rationale as cited in the rejection of claim 7.
Re Claim 23, it is an articles of manufacture claim, having similar limitations of claim 16. Thus, claim 23 is also rejected under the similar rationale as cited in the rejection of claim 16.
Re Claim 24, it is an articles of manufacture claim, having similar limitations of claim 8. Thus, claim 24 is also rejected under the similar rationale as cited in the rejection of claim 8.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Stadtfeld, Christoph, and Per Block. "Interactions, actors, and time: Dynamic network actor models for relational events." Sociological Science 4 (2017): 318-352 teaches a Dynamic Network Actor Models of interpersonal interactions over time using exogenous updates to provide endogenous changes in the process state model.
Ou, Yangjun, Li Mi, and Zhenzhong Chen. "Object-relation reasoning graph for action recognition." In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 20133-20142. 2022 teaches modeling an actor-centric object-level graph to show relationships and dependencies between subjects in the model over various changes.
Examiner’s Note: The examiner has cited particular columns and line numbers in the reference that applied to the claims above for the convenience of the applicant. Although the specified citations are representative of the art and are applied to specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested from the applicant, to fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner. In the case of amending the claimed invention, the applicant is respectfully requested to indicate the portion(s) of the specification which dictate(s) the structure relied on for the proper interpretation and also to verify and ascertain the metes and bound of the claimed invention.
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/SIMEON P DRAPEAU/Examiner, Art Unit 2188
/RYAN F PITARO/Supervisory Patent Examiner, Art Unit 2188
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