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 .
Claim Objections
Claims 1,10,17 objected to because of the following informalities: typo between monitored and monitoring. Appropriate correction is required.
In claims 1,10 and 17, the goal/purpose of the method recited in the preamble is “for identifying anomalies in a monitored system”, but later in the claim, the term monitoring is used instead of monitored in limitation “receiving a second quantity indicative of an anomaly associated with the monitoring system;”. An anomaly associated with the monitoring system would mean an issue with the observation framework, not the system you are trying to monitor, as described by the beginning of the claim and the specification(par 14,16-17,19). For the purposes of examination the term “monitoring system” will be interpreted as “monitored system” in claims 1,10,17.
Examiner notes that although claim 13 also contains the term “monitoring system”, the goal of claim 13 is to report alert causal relationship results back to the alert generator(the monitoring system), so in that context, the term monitoring system does make sense, and is not a typo.
Claims 9 objected to because of the following informalities: typo between stats and status. Appropriate correction is required.
Claim 9 is about alert statuses and storing alert status. The word “stats” should be “status”. For the purposes of examination, “stats” will be interpreted as “status”.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. The claim(s) recite(s) mental processes – concepts performed in the human mind.
Subject Matter Eligibility Analysis
Step 1: Do the Claims Specify a Statutory Category?
Claims 1-9 recite a computer-implemented method, 10-16 recite a computing device, and claims 17-20 recite a non-transitory computer readable storage medium, therefore satisfying Step 1 of the analysis.
Step 2 Analysis
Regarding claim 1,
Step 2A – Prong 1: Is a Judicial Exception Recited?
For step 2A eligibility prong one(does the claim recite a judicial exception?), the claim(s) recite(s) “calculating an alert silencing score based upon the first quantity and the second quantity, wherein the alert silencing score is associated with a probability that the second quantity is causally related with the first quantity.”(This is a mental process of observation, evaluation, judgment, opinion [MPEP 2106.04(a)(2) III. “Mental processes”]. Under broadest reasonable interpretation, the calculating and probability calculations are also considered a mathematical calculation [MPEP 2106.04(a)(2) 1. “Mathematical concepts”]). As claimed, this process can practically be performed either in the human mind or using a computer as a tool.
Even if the limitations require a computer, it can still be a mental process [see MPEP 2106.04(a)(2) III. C. "A Claim That Requires a Computer May Still Recite a Mental Process"]. calculating an alert silencing score based upon the first quantity and the second quantity, wherein the alert silencing score is associated with a probability that the second quantity is causally related with the first quantity are directed to mental processes of observing the first and second quantities, evaluating what they mean, and making a judgement/opinion on if the two quantities are causally related. The steps are recited at a high level of generality and merely use computers as a tool to perform the processes.
Step 2A – Prong 2: Is the Judicial Exception Integrated into a Practical Application?
For step 2A eligibility prong two(does the claim recite additional elements that integrate the judicial exception into a practical application?), This judicial exception is not integrated into a practical application because the additional limitations of “receiving a first quantity indicative of an event associated with execution of the maintenance operation;” and “receiving a second quantity indicative of an anomaly associated with the monitoring system;” are insignificant extra-solution activities of data gathering, data sending, and presentation[see MPEP 2106.05(g) Whether the limitation amounts to necessary data gathering and outputting. This is considered in Step 2A Prong Two and Step 2B.]
The additional computer parts(“computer-implemented method”, “a monitored system”) are generic components recited at a high level of generality[see MPEP 2106.05(b) “If applicant amends a claim to add a generic computer or generic computer components and asserts that the claim recites significantly more because the generic computer is 'specially programmed' (as in Alappat, now considered superseded) or is a 'particular machine' (as in Bilski), the examiner should look at whether the added elements integrate the exception into a practical application or provide significantly more than the judicial exception. Merely adding a generic computer, generic computer components, or a programmed computer to perform generic computer functions does not automatically overcome an eligibility rejection. Alice Corp. Pty. Ltd. v. CLS Bank Int’l, 573 U.S. 208, 223-24, 110 USPQ2d 1976, 1983-84 (2014). See In re Alappat, 33 F.3d 1526, 1545, 31 USPQ2d 1545, 1558 (Fed. Cir. 1994); In re Bilski, 545 F.3d 943, 88 USPQ2d 1385 (Fed. Cir. 2008)”]. The generality of the “computer-implemented” method is described in the specification paragraph 30 “COMPUTER 301 may take the form of a desktop computer, laptop computer, tablet computer, smart phone, smart watch or other wearable computer, mainframe computer, quantum computer or any other form of computer or mobile device now known or to be developed in the future that is capable of running a program, accessing a network or querying a database, such as remote database 330.”. The generality of “a monitored system” is described in specification paragraph 26 “Various systems may be monitored, including on-premise systems, cloud systems, virtual machines, and the like.”. As a whole, the claims are directed to abstract mental processes implemented on a generic computer, but are not integrated into a practical application [see MPEP 2106.05(f) “implementing an abstract idea on a generic computer, does not integrate the abstract idea into a practical application in Step 2A Prong Two”].
The specification par 14-16 describes how automatically detecting and silencing maintenance-related alerts may reduce alert signals and alert fatigue and therefore provide a technological improvement. However, claim 1 does not require silencing an alert, changing an alert status, preventing an alert from being transmitted, modifying operation of a monitoring system, or otherwise applying the calculated alert silencing score to alter operation of a computer or other technology. Instead, claim 1 stops with the calculation of the probability-based score. Therefore, claim 1 does not reflect the disclosed steps that provide the asserted technological improvement and does not integrate the abstract idea into a practical application. [see MPEP 2106.04(d)(1) “Evaluating Improvements in the Functioning of a Computer, or an Improvement to Any Other Technology or Technical Field in Step 2A Prong Two”]
Step 2B: Do the Claims Provide an Inventive Concept?
For step 2B eligibility (Whether a Claim Amounts to Significantly More), The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because additional elements are either gathering/storing data(“receiving a first quantity indicative of an event associated with execution of the maintenance operation;” and “receiving a second quantity indicative of an anomaly associated with the monitoring system;”), or are additional computer parts that are well known components recited at a high level of generality(“computer-implemented method”, “a monitored system”). The generality of the “computer-implemented” method is described in the specification paragraph 30 “COMPUTER 301 may take the form of a desktop computer, laptop computer, tablet computer, smart phone, smart watch or other wearable computer, mainframe computer, quantum computer or any other form of computer or mobile device now known or to be developed in the future that is capable of running a program, accessing a network or querying a database, such as remote database 330.”. The generality of “a monitored system” is described in specification paragraph 26 “Various systems may be monitored, including on-premise systems, cloud systems, virtual machines, and the like.”.
The data gathering/storing/presenting limitations are insignificant extra-solution activity because these limitations amount to necessary data gathering and outputting, (i.e., all uses of the recited judicial exception require such data gathering or data output) [see MPEP 2106.05(g) “(1) Whether the extra-solution limitation is well known. “, “(2) Whether the limitation is significant (i.e. it imposes meaningful limits on the claim such that it is not nominally or tangentially related to the invention).”, “(3) Whether the limitation amounts to necessary data gathering and outputting, (i.e., all uses of the recited judicial exception require such data gathering or data output).”]
The claim’s (“computer-implemented method”, “a monitored system”) generally link the abstract idea to the field of maintainable systems. As described in the specification paragraph 30, the method could be implemented by (“a desktop computer, laptop computer, tablet computer, smart phone, smart watch or other wearable computer, mainframe computer, quantum computer or any other form of computer or mobile device now known or to be developed in the future that is capable of running a program, accessing a network or querying a database, such as remote database 330.” Spec par 30). Not only can the method be performed by any of those systems, it could be monitoring any of a variety of systems, as described in specification paragraph 26 “Various systems may be monitored, including on-premise systems, cloud systems, virtual machines, and the like.”. Therefore, the additional elements only merely indicate a field of use or technological environment in which to apply a judicial exception, and do not amount to more than the judicial exception. [See MPEP 2106.05(h) “Field of Use and Technological Environment”]
The additional limitations, considered individually and in combination, do not amount to significantly more than the abstract idea. Receiving data and using a generic computer to perform calculations are well-understood, routine, conventional computer functions recited at a high level of generality. See [MPEP 2106.05(d)]. The receiving steps also amount to insignificant data-gathering activity necessary to perform the mathematical calculation. The claim does not recite any non-conventional computer arrangement or any additional technological operation performed using the resulting score. Accordingly, the additional elements, individually and in combination, do not provide an inventive concept sufficient to transform the claimed abstract idea into patent-eligible subject matter.
Conclusion: In light of the above, the limitations in claim 1 recite and are directed to an abstract idea and recite no additional elements that would amount to significantly more than the identified abstract idea. Claim 1 is therefore not patent eligible.
Regarding claims 10 and 17, they are rejected for the same reasons as claim 1. The additional components (claim 10’s processor, memory, computer-usable medium embodying a computer program code),(claim 17’s “A non-transitory computer readable storage medium tangibly embodying a computer readable program code having computer readable instructions that, when executed, causes a computer device to carry out a method of …”), are generic and do not apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment.
As for the limitations recited in claims 2-9,11-16,18-20, when considering each of the claims as a whole these additional abstract ideas and additional elements do not integrate the exception into a practical application, using one or more of the considerations laid out by the Supreme Court and the Federal Circuit. The additional elements do not reflect an improvement in the functioning of a computer, or an improvement to other technology or technical field. The additional elements do not implement a judicial exception with, or use a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim. The additional elements do not apply or use the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception.
Claim Rejections - 35 USC § 103
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 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.
Claim(s) 1-2,5-11,14-18,20 is/are rejected under 35 U.S.C. 103 as being unpatentable over US 20200313953 A1 (Simeonov) in view of US 20180114376 A1 (Lu).
Regarding claim 1, Simeonov teaches,
A computer-implemented method for identifying anomalies in a monitored system caused by a maintenance operation,(par 3-4 – teaches monitoring configuration items, determining if the item is in a maintenance mode, and suppressing alerts related to the configuration item while the item is in the maintenance mode. Par 13 – teaches an automated monitoring system like a monitoring and event management(MEM) tool. ) comprising:
receiving a first quantity indicative of an event associated with execution of the maintenance operation;(fig 3:308; par 24 – teaches collecting maintenance information for every configuration item. Fig 3:312,314,316; par 25-26 – teaches logging actual maintenance actions and finding maintenance events.)
receiving a second quantity indicative of an anomaly associated with the monitoring system;(par 13 – teaches how alerts of anomalies related to the configuration item may be suppressed. Fig 3:322; par 29-30 – teaches how alerts from the monitoring and event management(MEM) tool are suppressed while the configuration item is in maintenance mode.)
However, although Simeonov teaches that the MEM tool silences related alerts, or consults with the suppression tool on alert-worthy behavior(Simeonov par 29), Simeonov does not specifically teach calculating an alert silencing score based upon the first quantity and the second quantity, wherein the alert silencing score is associated with a probability that the second quantity is causally related with the first quantity.
On the other hand, Lu teaches,
calculating an alert silencing score based upon the first quantity and the second quantity,(fig 5:510; par 53 – teaches collecting historical maintenance operations(which corresponds to applicant’s first quantity.). fig 5:515; par 54 – teaches collecting historical messages for analysis against the maintenance operations. fig 5:520; Par 55 – teaches calculating a correlation between the maintenance actions and the alert messages.)
wherein the alert silencing score is associated with a probability that the second quantity is causally related with the first quantity.(fig 5:520; Par 55 – teaches calculating a probability that there is a correlation between the maintenance action and the alert message.)
Therefore, it would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention to further modify Simeonov to incorporate Lu’s correlation calculation for determining whether an anomaly alert is associated with a maintenance operation. One of ordinary skill in the art would have been motivated to improve Simeonov's selective suppression of maintenance-related alerts by more accurately distinguishing alerts related to the maintenance operation from unrelated alerts, because Simeonov teaches selectively suppressing alerts related to a maintenance operation while allowing unrelated alerts to proceed normally (par 29-30), and Lu teaches filtering messages associated with a known maintenance operation to reduce message noise and improve analysis accuracy (par 22,59).
Regarding claim 2, Simeonov and Lu teach,
The computer-implemented method of claim 1,
Simeonov and Lu further teach,
further comprising continuously determining (Simeonov par 32 – teaches periodically monitoring for events to analyze and commence or cease maintenance mode for events. Repeatedly checking events to make sure alerts need to stay suppressed is continuously determining.), based upon the alert silencing score, whether the second quantity is causally related to the maintenance operation. (Lu par 36,62 – teaches receiving log message data continuously as they occur. Par 58,63 – teaches analyzing the received log message data and correlating them to maintenance operations.)
Regarding claim 5, Simeonov and Lu teach,
The computer-implemented method of claim 1,
Simeonov and Lu further teach,
further comprising indicating that the second quantity, previously determined as being causally related to the maintenance operation,( Simeonov par 32 – teaches periodically monitoring for events to analyze and commence or cease maintenance mode for events. Repeatedly checking events to make sure alerts need to stay suppressed is redetermining previously determined alert statuses. Par 40 – teaches re-evaluating maintenance status of configuration items when maintenance is completed, which allows the MEM tool to resume monitoring immediately instead of waiting for the maintenance scheduled time to pass.) is no longer causally related to the maintenance operation.(Lu par 36,62 – teaches receiving log message data continuously as they occur. Par 58,63 – teaches analyzing the received log message data and correlating them to maintenance operations. fig 5:520; par 55-56 – teaches calculating a correlation between the maintenance actions and the alert messages.)
Regarding claim 6, Simeonov and Lu teach,
The computer-implemented method of claim 1,
Simeonov further teaches,
wherein the first quantity includes a start time of the maintenance operation, an end time of the maintenance operation, and operation names for the maintenance operation.(par 25 – teaches relevant information systems like maintenance ticketing/scheduling/approval systems sending maintenance plans to the suppression tool, as well as tracking when maintenance personnel log into the configuration items, configuration item change logs that detail what maintenance has been performed, user notes on why the maintenance is being performance and what is being done during the maintenance. Par 26– teaches collecting date, time, duration information on maintenance scheduling and actions. Par 28 – teaches determining if configuration items are still in maintenance mode or not using the collected maintenance scheduling and maintenance action data, including scheduled times and extra time before and after the scheduled time window.)
Regarding claim 7, Simeonov and Lu teach,
The computer-implemented method of claim 1,
Simeonov further teaches,
wherein the second quantity is an alert received from an observability service.(par 13 – teaches an automated monitoring system like a monitoring and event management(MEM) tool. Par 19,29 – teaches how the suppression tool gets alert data from the MEM tool for analysis and decisions on if alerts should be suppressed or not.)
Regarding claim 8, Simeonov and Lu teach,
The computer-implemented method of claim 7,
Lu further teaches,
further comprising storing each alert in an alerts history database. (fig 2:220; par 37, 52 teaches a database that stores “thresholds, sensor data, warning data, and alert data.”, as well as correlations, message data, and trends(trends are explained in par 22))
Regarding claim 9, Simeonov and Lu teach,
The computer-implemented method of claim 8,
Simeonov and Lu further teach,
further comprising storing a status of each alert in an alerts status database (Lu fig 2:220; par 37, 52 teaches a database that stores “thresholds, sensor data, warning data, and alert data.”, as well as correlations, message data, and trends(trends are explained in par 22)), the stats including a SILENCED status and a NOT_SILENCED status. (Simeonov par 30 – teaches suppressing alerts when the alert is related to the specific maintenance actions and not suppressing alerts that are not related to the maintenance actions. Simeonov’s suppressed alert and not suppressed alert states correspond to applicant’s SILENCED and NOT_SILENCED states.)
Regarding claim 10, it is the computing device that implements the computer-implemented method of claim 1 and is rejected for similar reasons. The combination further discloses a memory, processors, and a computer-usable medium with instructions (see Simeonov fig 5; par 43-48).
Regarding claims 11,15,16 they are the computing device that implements the computer-implemented method of claims 2,8,9 and are rejected for the same reasons.
Regarding claim 14, Simeonov and Lu teach,
The computing device of claim 10,
Simeonov further teaches,
wherein: the first quantity includes a start time of the maintenance operation, an end time of the maintenance operation, and operation names for the maintenance operation; (par 25 – teaches relevant information systems like maintenance ticketing/scheduling/approval systems sending maintenance plans to the suppression tool, as well as tracking when maintenance personnel log into the configuration items, configuration item change logs that detail what maintenance has been performed, user notes on why the maintenance is being performance and what is being done during the maintenance. Par 26– teaches collecting date, time, duration information on maintenance scheduling and actions. Par 28 – teaches determining if configuration items are still in maintenance mode or not using the collected maintenance scheduling and maintenance action data, including scheduled times and extra time before and after the scheduled time window.)
and the second quantity is an alert received from an observability service. (par 13 – teaches an automated monitoring system like a monitoring and event management(MEM) tool. Par 19,29 – teaches how the suppression tool gets alert data from the MEM tool for analysis and decisions on if alerts should be suppressed or not.)
Regarding claim 17, it is the non-transitory computer readable storage medium tangibly embodying a computer readable program code having computer readable instructions that, when executed, causes a computer device to carry out the method of claim 1, and is rejected for the same reasons. The combination further discloses a non-transitory computer readable storage medium (see Simeonov par 51).
Regarding claims 18,20 they are the computer readable storage medium having computer readable instructions that, when executed, causes a computer device to carry out the method of claim 2,5 and are rejected for the same reasons.
Claim(s) 3-4,12-13,19 is/are rejected under 35 U.S.C. 103 as being unpatentable over US 20200313953 A1 (Simeonov) in view of US 20180114376 A1 (Lu) as applied to claim 1 above, and further in view of US 20220237069 A1 (Freeman).
Regarding claim 3, Simeonov and Lu teach,
The computer-implemented method of claim 1,
Lu further teaches,
further comprising outputting, to an alert database system, an indication of the second quantity,(fig 5:520; par 56 – teaches storing correlation results in the AMM(aircraft message monitor) server and database when the confidence exceeds a threshold. AMM server is further defined in fig 2:210; par 35 – which teaches that the monitoring system includes an aircraft message monitor (AMM), which receives a plurality of messages from aircraft for analysis, as well as a plurality of maintenance operations data to compare the aircraft messages to for correlation.) when it is determined that the second quantity is causally related to the maintenance operation.( par 36,62 – teaches receiving log message data continuously as they occur. Par 58,63 – teaches analyzing the received log message data and correlating them to maintenance operations.)
However, although Lu teaches storing the alert correlation, and Simeonov teaches consulting with a suppression tool on if an alert needs to be suppressed or not(Simeonov par 29), Lu and Simeonov do not specifically teach outputting an indication of the second quantity to an alert notification system.
On the other hand, Freeman further teaches,
further comprising outputting, to an alert notification system, an indication of the second quantity, (fig 4:426,428; par 48-49 – teaches anomaly alert events being sent to notification service 426 and UI service 428.)
It would have been obvious to one of ordinary skill in the art to further modify the combined system of Simeonov and Lu to output an indication of an anomaly determined to be associated with a maintenance operation to an alert notification system, as taught by Freeman. One of ordinary skill in the art would have been motivated to improve the handling and communication of detected anomaly information by providing the anomaly information to a notification service configured to apply notification rules and communicate appropriate notifications. Freeman teaches that when an anomaly alert is generated, the alert event is sent to a dedicated notification service over a well-defined API protocol and that notification service determines the appropriate notification messages to be sent through external messaging platforms (Freeman par 48-49).
Regarding claim 4, Simeonov, Lu, and Freeman teach,
The computer-implemented method of claim 3,
Simeonov and Lu further teach,
further comprising indicating that the second quantity, previously determined as being causally related to the maintenance operation,(Simeonov par 32 – teaches periodically monitoring for events to analyze and commence or cease maintenance mode for events. Repeatedly checking events to make sure alerts need to stay suppressed is redetermining previously determined alert statuses. Par 40 – teaches re-evaluating maintenance status of configuration items when maintenance is completed, which allows the MEM tool to resume monitoring immediately instead of waiting for the maintenance scheduled time to pass.) is no longer causally related to the maintenance operation. (Lu par 36,62 – teaches receiving log message data continuously as they occur. Par 58,63 – teaches analyzing the received log message data and correlating them to maintenance operations. fig 5:520; par 55-56 – teaches calculating a correlation between the maintenance actions and the alert messages.)
Regarding claims 12,13 it is the computing device that implements the computer-implemented method of claim 3,4 and is rejected for the same or similar reasons. Claim 13’s “indicate to the monitoring system” is taught by Freeman in (fig 4:426,428; par 48-49 – teaches anomaly alert events being sent to notification service 426 and UI service 428.)
Regarding claim 19 it is the computer readable storage medium having computer readable instructions that, when executed, causes a computer device to carry out the method of claim 3 and is rejected for the same reasons.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 20250028589 A1- Nagar - also IBM, published within 1 year. Claim 6 automatically decides whether to hide, dismiss, or maintain alerts associated with the detected anomaly time window.
US 20240134732 A1 - Iyer - Dell. Cause alert and clear alert correlation
US 20170213142 A1 - Kaluza - monitors an IT system, triggers alerts when monitored KPIs have abnormal values, establishes a causal correlation between those symptoms and changes to the system, and identifies the changes most likely to have caused the incident.
US 20110133945 A1 - Klein - calculates metrics for planned downtime
US 20020111755 A1 - Valadarsky - a network fault-management system that identifies alarms generated by maintenance activities, performs root-cause/correlation analysis, calculates confidence using probabilities and alarm ratios, suppresses maintenance-related alarms, stores results in a history database, and dynamically reevaluates the root cause as new alarms arrive. Calculates correlation between alerts and the root cause.
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/MICHAEL XU/Examiner, Art Unit 2113
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