Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Detailed Action
The following action is in response to the communication(s) received on 03/02/2026.
As of the claims filed 03/02/2026:
Claims 1, 5, 6, 10, 13, 15, and 19 have been amended.
Claim 21 has been added.
Claims 1, 4-6, 8-10, 12, 13, 15, 18, 19, and 21 are pending.
Claims 1, 10, and 15 are independent claims.
Response to Arguments
Applicant’s arguments filed 03/02/2026 have been fully considered, but are not fully persuasive.
With respect to the rejection under 35 USC § 101, Applicant asserts the amendments to claim 1 directs the invention towards patent-eligible subject matter. Examiner respectfully disagrees.
Step 2A Prong One:
Applicant asserts that the judicial exceptions recited cannot be performed by the human mind, as each of these judicial exceptions recite being performed “by the computing device” and thus “inextricably tied to a computer technology”. Examiner respectfully disagrees. In order for the claims to be tied inextricably to a specific technology, the instant claims must show the improvement to the technology. However, the hardware processor for training the OGEM and learning the history window is merely the technological application of the abstract ideas in the instant claims, as currently recited.
Thus, the claims remain reciting judicial exceptions.
Step 2A Prong Two:
Applicant asserts that the claims recite an improvement to the system based on the ordinal graphical event model (OGEM) by capturing the temporal order of causal event on the occurrence of subsequent events, thus improving efficiency of the algorithm. Examiner respectfully submits that the OGEM, as currently recited, is an improvement to a specific causal event model, which is an algorithm for causal events. Since the algorithm is an abstract idea and not a technology, the improvement is directed towards the abstract idea.
Thus, the claims remain directed to the judicial exceptions.
Claims 4-6, 8, 9, 12, 13, 18, 19, and 21 remain rejected by virtue of dependency to their respective parent claims.
With respect to the rejection under 35 USC § 103:
The amendments have overcome the prior art; thus, the art rejections have been withdrawn.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1, 4-6, 8-10, 12, 13, 15, 18, 19, and 21 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claim 1 recites method, thus a process, one of the four statutory categories of patentable subject matter (Step 1). However, Claim 1 further recites:
learning… parent-event types and one or more corresponding child-event types from the event occurrence data; generating… a timeline of the parent-event types and the one or more corresponding child-event types…from the event occurrence data; which is an evaluation or judgement that can be performed in the human mind;
learning, for each of the plurality of order instantiations, a respective conditional intensity parameter of conditional intensity parameters, which is an evaluation or judgement that can be performed in the human mind;
applying… a masking function to the event occurrence data, wherein the history window includes a plurality of labels, and the masking function is configured to return a masked sub-sequence where a label of the plurality of labels is not repeated, by excluding repeated labels of the plurality of labels and retaining only a first occurrence or a last occurrence of each label of the plurality of labels in the history window, which is an evaluation or judgement that can be performed in the human mind;
comprising asynchronous, irregularly spaced, time-stamped events of multiple types, which is a detail of an evaluation or judgement (learning…from the event occurrence data)
time-stamped asynchronous, irregularly spaced event occurrence data, which is a detail of an evaluation or judgement (learning…from the event occurrence data)
determining a plurality of order instantiations of the parent-event types, wherein each order instantiation of the plurality of order instantiations is determined for a respective occurrence of a plurality of occurrences of a given child-event type of the one or more corresponding child-event types, based on the masked sub-sequence, each order instantiation of the plurality of order instantiations corresponds to a respective permutation of the parent-event types in the masked sub-sequence, in the masked sub-sequence, the parent-event types are in a sequential order that corresponds to a temporal order of occurrences of the parent-event types, a first order instantiation of the plurality of order instantiations comprises an occurrence of a first parent-event type of the parent-event types prior to an occurrence of a second parent-event type of the parent-event types, a second order instantiation of the plurality of order instantiations comprises the occurrence of the second parent-event type prior to the occurrence of the first parent-event type, and the occurrence of the first parent-event type and the occurrence of the second parent-event type are within the history window, which is an evaluation or judgement that can be performed in the human mind; (Note: the amended limitations are merely details of the abstract idea of determining the order instantiations instead of a machine learning training methodology.)
…assigns conditional intensity parameters that vary based on the determined order instantiation of the parent-event types, which is an evaluation or judgement that can be performed in the human mind;
and predicting… agent interaction based on the conditional intensity parameters and the sequential order of the parent-event types in a predetermined history window, wherein the predicting of the agent interaction comprises: determining, within the timeline of the parent-event types, an occurrence of a current order instantiation of the parent-event types, wherein the current order instantiation corresponds to one of the plurality of order instantiations for which the OGEM is trained: and predicting an occurrence of the given child-event type based on the respective conditional intensity parameter associated with the current order instantiation, which is an evaluation or judgement that can be performed in the human mind;
Thus, the claim recites an abstract idea under Step 2A Prong 1.
Under Step 2A Prong 2, the claim does not include any additional elements which integrate the abstract idea into a practical application, since the additional elements consist of:
A computer-implemented method…; by a computing device…, as the performance of an abstract idea on a computer is not more than instructions to "apply it" on a computer, which by MPEP 2106.05(f) cannot integrate an abstract idea into a practical application;
receiving… event occurrence data, which is merely an insignificant extra-solution activity of data gathering, which by MPEP 2106.05(g) cannot integrate an abstract idea into a practical application;
using the OGEM, wherein the OGEM comprises a graph in which nodes represent event labels and edges represent parent-child event relationships…; using the OGEM, as the performance of an abstract idea on a computer is not more than instructions to "apply it" on a computer, which by MPEP 2106.05(f) cannot integrate an abstract idea into a practical application;
learning, by the computing device, a history window from the event occurrence data… the history window includes a plurality of labels , as the performance of an abstract idea on a computer is not more than instructions to "apply it" on a computer, which by MPEP 2106.05(f) cannot integrate an abstract idea into a practical application;
training, by the computing device, an ordinal graphic event model (OGEM) based on the event occurrence data, wherein the training of the OGEM comprises:…, as the performance of an abstract idea on a computer is not more than instructions to "apply it" on a computer, which by MPEP 2106.05(f) cannot integrate an abstract idea into a practical application;
Thus, the claim is directed towards an 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)) and the activity of data gathering (MPEP 2106.05(g)) cannot provide significantly more, as storing and retrieving information in memory is well understood, routine, and conventional (MPEP 2106.05(d)(II)(iv)) and the combination of additional elements does not provide an inventive concept. Thus, the claim is ineligible.
Claim 4, dependent upon Claim 1, further recites
the masking function is based on one of a first masking function based on a beginning of the history window, or a last masking function based on the last occurrence of each label of the plurality of labels in the event occurrence data, which is a detail of an evaluation or judgement (applying a masking function) that can be performed in the human mind.
Thus, the claim recites an abstract idea under Step 2A Prong 1.
Under Step 2A Prong 2 and 2B, the claim does not recite any new additional elements which could integrate the abstract idea into a practical application or provide significantly more than the abstract idea itself. Thus, the claim is ineligible.
Claim 5, dependent upon Claim 1, further recites
determining the plurality order instantiations at a given time over the history window by applying the masking function to each label of the plurality of labels from the event occurrence data occurring within the history window, which is an evaluation or judgement that can be performed in the human mind.
Thus, the claim recites an abstract idea under Step 2A Prong 1.
Under Step 2A Prong 2 and 2B, the claim does not recite any new additional elements which could integrate the abstract idea into a practical application or provide significantly more than the abstract idea itself. Thus, the claim is ineligible.
Claim 6, dependent upon Claim 5, further recites
the timeline is modeled as the graph, and wherein each node of the nodes of the graph is representative of each label of the plurality of labels from the event occurrence data, which is an evaluation or judgement that can be performed in the human mind.
Thus, the claim recites an abstract idea under Step 2A Prong 1.
Under Step 2A Prong 2 and 2B, the claim does not recite any new additional elements which could integrate the abstract idea into a practical application or provide significantly more than the abstract idea itself. Thus, the claim is ineligible.
Claim 8, dependent upon Claim 1, further recites
issuing a predictive alert or a feedback signal for an occurrence of an expected event type at an expected time, which is an evaluation or judgement that can be performed in the human mind.
Thus, the claim recites an abstract idea under Step 2A Prong 1.
Under Step 2A Prong 2 and 2B, the claim does not recite any new additional elements which could integrate the abstract idea into a practical application or provide significantly more than the abstract idea itself. Thus, the claim is ineligible.
Claim 9, dependent upon Claim 8, further recites
the predictive alert or the feedback signal is issued by tracking a history of occurrences of the expected event type in the event occurrence data in real- time, which is an evaluation or judgement that can be performed in the human mind.
Thus, the claim recites an abstract idea under Step 2A Prong 1.
Under Step 2A Prong 2 and 2B, the claim does not recite any new additional elements which could integrate the abstract idea into a practical application or provide significantly more than the abstract idea itself. Thus, the claim is ineligible.
Claim 10 recites method, thus a process, one of the four statutory categories of patentable subject matter (Step 1). However, Claim 10 further recites:
learning… an ordinal graphical event model (OGEM) from an event dataset, including: generating an OGEM graph where nodes represent events and edges represent connections between parent nodes to child nodes; and applying… the conditional intensity parameters to the OGEM graph, wherein the conditional intensity parameters are piece-wise constant over time, with rate changes occurring whenever there is a change in the plurality of order instantiations in the history window; which is an evaluation or judgement that can be performed in the human mind;
determining a plurality of order instantiations of the parent-event types, wherein each order instantiation of the plurality of order instantiations is determined for a respective occurrence of a plurality of occurrences of a given child-event type of the one or more corresponding child-event types, based on the masked sub-sequence, each order instantiation of the plurality of order instantiations corresponds to a respective permutation of the parent-event types in the masked sub-sequence, in the masked sub-sequence, the parent-event types are in a sequential order that corresponds to a temporal order of occurrences of the parent-event types, a first order instantiation of the plurality of order instantiations comprises an occurrence of a first parent-event type of the parent-event types prior to an occurrence of a second parent-event type of the parent-event types, a second order instantiation of the plurality of order instantiations comprises the occurrence of the second parent-event type prior to the occurrence of the first parent-event type, and the occurrence of the first parent-event type and the occurrence of the second parent-event type are within the history window, which is an evaluation or judgement that can be performed in the human mind; (Note: the amended limitations are merely details of the abstract idea of determining the order instantiations instead of a machine learning training methodology.)
and predicting… an occurrence of a particular event using summary statistics of counts and durations in the event dataset and the conditional intensity parameters, which is an evaluation or judgement that can be performed in the human mind;
wherein the event dataset includes event occurrence data as time-stamped asynchronous, irregularly spaced event occurrence data, which is a detail of an evaluation or judgement (learning…from an event dataset).
Thus, the claim recites an abstract idea under Step 2A Prong 1.
Under Step 2A Prong 2, the claim does not include any additional elements which integrate the abstract idea into a practical application, since the additional elements consist of:
A computer implemented method, as the performance of an abstract idea on a computer is not more than instructions to "apply it" on a computer, which by MPEP 2106.05(f) cannot integrate an abstract idea into a practical application;
training, by the computing device, an ordinal graphic event model (OGEM) based on the event occurrence data, wherein the training of the OGEM comprises:…, as the performance of an abstract idea on a computer is not more than instructions to "apply it" on a computer, which by MPEP 2106.05(f) cannot integrate an abstract idea into a practical application;
receiving… event occurrence data comprising asynchronous, irregularly spaced, time-stamped events of multiple types, which is merely an insignificant extra-solution activity of data gathering, which by MPEP 2106.05(g) cannot integrate an abstract idea into a practical application;
Thus, the claim is directed towards an abstract idea.
Further, under Step 2B, the additional element does not provide significantly more than the abstract idea itself, because implementation on a computer (MPEP 2106.05(f)) cannot provide significantly more. Thus, the claim is ineligible.
Claim 12, dependent upon Claim 10, further recites
applying a masking function that receives the event occurrence data as input and returns the masked sub-sequence where a label of a plurality of labels is not repeated, which is an evaluation or judgement that can be performed in the human mind.
Thus, the claim recites an abstract idea under Step 2A Prong 1.
Under Step 2A Prong 2 and 2B, the claim does not recite any new additional elements which could integrate the abstract idea into a practical application or provide significantly more than the abstract idea itself. Thus, the claim is ineligible.
Claim 13, dependent upon Claim 12, further recites
determining the order instantiation at a given time over the history window by applying the masking function to each label of the plurality of labels from the event occurrence data occurring within the history window, which is an evaluation or judgement that can be performed in the human mind.
Thus, the claim recites an abstract idea under Step 2A Prong 1.
Under Step 2A Prong 2 and 2B, the claim does not recite any new additional elements which could integrate the abstract idea into a practical application or provide significantly more than the abstract idea itself. Thus, the claim is ineligible.
Claims 15 and 18 recite A non-transitory computer readable storage medium, thus an article of manufacture, one of the four statutory categories of patentable subject matter. However, Claims 15 and 18 recite tangibly embodying a computer readable program code having computer readable instructions that, when executed, causes a computer device to carry out a method of modeling agent interactions, the method comprising precisely the abstract ideas and additional elements of Claims 1, and 4, respectively. Therefore, Step 2A Prong 1 analysis remains the same. As for Step 2A Prong 2 and Step 2B: performance on a computer cannot integrate an abstract idea into a practical application (Step 2A Prong 2) nor provide significantly more than the abstract idea itself (Step 2B) (MPEP 2106.05(f)), Claims 15, and 18are rejected as subject-matter ineligible for reasons set forth in the rejections of Claims 1, and 4, respectively.
Claim 19, dependent upon Claim 15, further recites
determining the order instantiation at a given time over the history window by applying the masking function to each label of the plurality of labels from the event occurrence data occurring within the history window, which is an evaluation or judgement that can be performed in the human mind.
Thus, the claim recites an abstract idea under Step 2A Prong 1.
Under Step 2A Prong 2 and 2B, the claim does not recite any new additional elements which could integrate the abstract idea into a practical application or provide significantly more than the abstract idea itself. Thus, the claim is ineligible.
Claim 21, dependent upon Claim 1, further recites
splitting the event occurrence data into at least a training set and a testing set, based on the time-stamped events of the multiple types, which is an evaluation or judgement that can be performed in the human mind;
and wherein each of the training set and the testing set retains one or more labels of the plurality of labels that are common between the training set and the testing set, which is an evaluation or judgement that can be performed in the human mind;
and determining the plurality of order instantiations of the parent-event types based on the splitting of the event occurrence data, which is an evaluation or judgement that can be performed in the human mind.
Thus, the claim recites an abstract idea under Step 2A Prong 1.
Under Step 2A Prong 2 and 2B, the claim does not recite any new additional elements which could integrate the abstract idea into a practical application or provide significantly more than the abstract idea itself. Thus, the claim is ineligible.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JOSEP HAN whose telephone number is (703)756-1346. The examiner can normally be reached Mon-Fri 9am-5pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Kakali Chaki can be reached on (571) 272-3719. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/J.H./Examiner, Art Unit 2122
/KAKALI CHAKI/Supervisory Patent Examiner, Art Unit 2122
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