DETAILED ACTION
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
Claim(s) 1 objected to because of the following informalities:
Claim 1 recites “by generating vectors from rows of the log source”. The examiner believes this is a typo. A suggested amendment to the claim is “by generating vectors from rows of the log sources”. For examination purposes, the claim will be interpreted as suggested.
Appropriate correction is required.
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.
Claim(s) 1-8, 10 rejected under 35 U.S.C. 101 because the claimed invention is directed to judicial exceptions without significantly more.
Claim(s) 1-8 recite(s) methods and claim(s) 10 recite(s) a system. Therefore, claim(s) 1-8, 10 fall(s) within a statutory category.
Claim 1 recites abstract ideas.
determining anomalies in one or more log sources of a system by generating vectors from rows of the log source and their time of arrival stamps, the elements of the vectors reproducing properties of the rows corresponds to data analysis steps recited at a high level of generality such that they could practically be performed using pen and paper, which are mental processes. The broadest reasonable interpretation of the limitation in light of the specification encompasses log analysis by parsing and grouping human-readable text to detect anomalies ([0010]-[0014], [0017]).
wherein: said determining anomalies is started in response to a memory consumption of the first application exceeding a predefined frame or a predefined increase rate; said determining anomalies includes analyzing the log sources and determining further applications based on a process tree…, said process tree comprising information on processes or applications which start other processes, said applications started by the first application, and identifying and analyzing log sources of the further applications; the anomalies include an application having ended within a predefined time period after its start, a memory consumption exceeding a predefined frame or a predefined increase rate, and/or an application starting more frequently than a predefined value within a predefined time period; determining…causes for each of the anomalies corresponds to evaluations, which are mental processes. The claim discloses log analysis from selected data sources to detect anomalies. The causes of the anomalies are determined by evaluating the result of a query. The broadest reasonable interpretation of the limitations in light of the specification encompasses evaluations ([0004]: Log sources are typically manually reviewed by a human to determine anomalies. [0021]: The cause of the anomaly from the query can be presented to a human for review).
Claim 1 does not recite additional limitations that integrate the judicial exceptions into practical application.
A computer-implemented method amounts to mere instructions to implement the abstract ideas on a computer, which is mere instructions to apply an exception. See MPEP 2106.05(f).
determining anomalies in one or more log sources of a system…by using the vectors as input for a machine learning model which classifies and/or correspondingly marks the vectors as normal or abnormal amounts to mere instructions to implement the abstract ideas on a computer, which is mere instructions to apply an exception. See MPEP 2106.05(f).
said log sources obtained by accessing one or more log files or log streams written by a first application amounts to mere data gathering, which is insignificant extra-solution activity. See MPEP 2106.05(g).
correcting the causes for each of the anomalies by…applying the configured solution actions to the system…and the solution actions include changing a variable, restarting a program, installing an application, and/or updating an installed application amounts to an attempt to cover any solution to any identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, which is mere instructions to apply an exception. See MPEP 2106.05(f).
querying a database that maps pre-known causes to respective solution actions amounts to mere data gathering, which is insignificant extra-solution activity. See MPEP 2106.05(g).
presenting the results of the query to a user on a display of the system amounts to mere data output, which is insignificant extra-solution activity. See MPEP 2106.05(g).
receiving a selected and configured solution action of the presented solution actions from the user amounts to mere data gathering and selecting a particular data source or type of data to be manipulated, which is insignificant extra-solution activity. See MPEP 2106.05(g).
storing the configured solution action in the database amounts to mere data gathering, which is insignificant extra-solution activity. See MPEP 2106.05(g).
said memory consumption determined by accessing system information of an operation system; process tree maintained by the operating system amounts to mere data gathering, which is insignificant extra-solution activity. See MPEP 2106.05(g).
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exceptions because the additional elements amount to mere instructions to apply an exception and insignificant extra-solution activity. See MPEP 2106.05(f) and MPEP 2106.05(g).
Claim 2 refines recited abstract ideas.
wherein determining anomalies comprises: converting texts stored in the log sources into structured data, wherein components of the texts are classified with respect to their underlying events and parameters of the components of text are determined, and wherein the structured data differentiates into constant components of the texts from variable components of the texts corresponds to data analysis steps recited at a high level of generality such that they could practically be performed using pen and paper, which are mental processes. The broadest reasonable interpretation of the limitation in light of the specification encompasses parsing and grouping human-readable text ([0010]-[0014]).
The claim does not contain additional limitations that integrate the judicial exceptions into practical application and does not contain additional limitations that are sufficient to amount to significantly more than the judicial exceptions.
Claim 3 refines recited abstract ideas.
wherein determining anomalies comprises: clustering rows of the log sources using common identifiers used in different rows; determining parameter values from the clusters corresponds to data analysis steps recited at a high level of generality such that they could practically be performed using pen and paper, which are mental processes. The broadest reasonable interpretation of the limitation in light of the specification encompasses parsing and grouping human-readable text ([0010]-[0014]).
converting the clusters into respective number vectors corresponds to mathematical relationships, which are mathematical concepts. The broadest reasonable interpretation of the limitation in light of the specification encompasses mathematical relationships ([0017]: the vector elements can be generated by means of a mapping function of text components, i.e. words or phrases or numbers, onto numerical values).
The claim does not contain additional limitations that integrate the judicial exceptions into practical application and does not contain additional limitations that are sufficient to amount to significantly more than the judicial exceptions.
Claim 4 refines recited abstract ideas.
wherein determining anomalies comprises: converting rows of the log sources and their time of arrival stamps into respective number vectors corresponds to mathematical relationships, which are mathematical concepts. The broadest reasonable interpretation of the limitation in light of the specification encompasses mathematical relationships ([0017]: the vector elements can be generated by means of a mapping function of text components, i.e. words or phrases or numbers, onto numerical values).
The claim does not contain additional limitations that integrate the judicial exceptions into practical application and does not contain additional limitations that are sufficient to amount to significantly more than the judicial exceptions.
Claim 5 refines recited abstract ideas.
wherein determining anomalies comprises: wherein a label designating the cluster as normal or abnormal is created for each cluster, respectively corresponds to evaluations, which are mental processes. The broadest reasonable interpretation of the limitation in light of the specification encompasses evaluations ([0017]: The decision as to whether a cluster or a row is designated as normal or not can be made, for example, using certain keywords).
Claim 5 does not recite additional limitations that integrate the judicial exceptions into practical application.
training a machine learning (ML) model using the number vectors amounts to mere instructions to implement the abstract ideas on a computer, which is mere instructions to apply an exception. See MPEP 2106.05(f).
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exceptions because the additional elements amount to mere instructions to apply an exception. See MPEP 2106.05(f).
Claim 6 recites abstract ideas.
clustering the anomalies according to a time of their occurrence and/or a logging granularity corresponds to data analysis steps recited at a high level of generality such that they could practically be performed using pen and paper, which are mental processes. The broadest reasonable interpretation of the limitation in light of the specification encompasses parsing and grouping human-readable text ([0010]-[0014]).
The claim does not contain additional limitations that integrate the judicial exceptions into practical application and does not contain additional limitations that are sufficient to amount to significantly more than the judicial exceptions.
Claim 7 recites abstract ideas.
for each of the clusters of the anomalies, generating a natural language query that describes the respective anomaly, wherein the generating comprises examining words in the clusters of the anomalies with respect to the frequency of the words within a cluster, the frequency of the words in all clusters of the log sources, the frequency of the words in all rows of the log sources, and the granularity of the words, and mapping the most frequent words thus determined to natural language sentences corresponds to data analysis steps recited at a high level of generality such that they could practically be performed using pen and paper, which are mental processes. The broadest reasonable interpretation of the limitation in light of the specification encompasses counting words and creating phrases ([0018]-[0019]).
The claim does not contain additional limitations that integrate the judicial exceptions into practical application and does not contain additional limitations that are sufficient to amount to significantly more than the judicial exceptions.
Claim 8 does not recite additional limitations that integrate the judicial exceptions into practical application.
wherein querying the database includes applying the natural language query to the database to obtain the solution actions, said solution actions for correcting the respective anomaly, wherein the database contains natural language questions regarding anomalies as well as corresponding solution actions, in particular wherein the solution actions comprise technical steps for resolving the respective anomalies amounts to mere data gathering, which is insignificant extra-solution activity. See MPEP 2106.05(g).
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exceptions because the additional elements amount to insignificant extra-solution activity. See MPEP 2106.05(g).
Claim 10 does not recite additional limitations that integrate the judicial exceptions into practical application.
A system comprising: a processor running an application configured to perform the method of claim 1 amounts to mere instructions to implement the abstract ideas on a computer, which is mere instructions to apply an exception. See MPEP 2106.05(f).
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exceptions because the additional elements amount to mere instructions to apply an exception. See MPEP 2106.05(f).
For at least the reasons provided above, claim(s) 1-8, 10 are not patent eligible.
Claim Rejections - 35 USC § 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.
Claim(s) 1-6, 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over US Patent Application Publication No. 20210042180 (“Sutton”) in view of US Patent Application Publication No. 20220179763 (“Chan”), US Patent Application Publication No. 20130047039 (“Manes”) and Non-Patent Literature Windows Task Manager: The Complete Guide (“Hoffman”).
Regarding claim 1, Sutton teaches
A computer-implemented method comprising:
determining anomalies in one or more log sources of a system, said log sources obtained by accessing one or more log files or log streams written by a first application; ([0021], [0027], [0050]: determine problems of a system by monitoring an application using logging agents)
determining and correcting causes for each of the anomalies by querying a database that maps pre-known causes to respective solution actions; ([0038], [0039], [0050], [0051]: determine remedial actions that map to problems in a repository)
presenting the results of the query to a user on a display of the system; (Fig. 2B, [0054], [0055]: send a notification of remedial actions for the problems to a user on a GUI)
receiving a selected and configured solution action of the presented solution actions from the user; ([0054], [0060]: a user can adjust how presented remedial actions are performed)
applying the configured solution actions to the system; and ([0054], [0057], [0060]: remedial actions are performed according to user adjustments)
storing the configured solution action in the database; ([0039], [0041], [0060]: user adjustments to remedial actions definitions and configurations are stored in the repository)
wherein:
said determining anomalies includes analyzing the log sources… ([0021], [0027], [0050]: determine problems of a system by monitoring an application using logging agents)
the solution actions include changing a variable, restarting a program, installing an application, and/or updating an installed application. ([0021], [0026]: remedial actions include resetting software)
Sutton does not teach the remaining limitations.
Chan teaches
determining anomalies in one or more log sources of a system by generating vectors from rows of the log source and their time of arrival stamps, the elements of the vectors reproducing properties of the rows ([0034], [0039], [0056]: generate feature vectors for the grouped log lines for a time window for problem diagnosis and anomaly detection. Logs contain timestamps), and by using the vectors as input for a machine learning model which classifies and/or correspondingly marks the vectors as normal or abnormal (Fig. 3, 6, [0042], [0043]: train a machine learning model using the feature vectors to determine cluster labels for feature vectors as anomalous or normal)
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine Chan’s problem diagnosis with Sutton in view of Manes and Hoffman problem analysis.
One of ordinary skill in the art prior to the effective filing date would have been motivated to make the combination to utilize spatial information from related sources during problem diagnosis (Chan, [0057]).
Sutton in view of Chan does not teach the remaining limitations.
Manes teaches
said determining anomalies is started in response to a memory consumption of the first application exceeding a predefined frame or a predefined increase rate…([0017], [0019], [0033]: Trigger analysis of collected information of a process in response to the process memory usage exceeding a threshold)
said determining anomalies includes…determining further applications based on a process tree…, said process tree comprising information on processes or applications which start other processes, said applications started by the first application ([0030]: determine sub-processes started by other processes in a process tree), and identifying and analyzing log sources of the further applications; ([0016], [0030]: drill-down analysis of collected information of sub-processes)
the anomalies include an application having ended within a predefined time period after its start, a memory consumption exceeding a predefined frame or a predefined increase rate, and/or an application starting more frequently than a predefined value within a predefined time period; ([0033]: process memory usage exceeding a threshold)
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine Manes’ problem analysis with Sutton in view of Chan’s problem analysis.
One of ordinary skill in the art prior to the effective filing date would have been motivated to make the combination to provide problem analysis that looks at a system as a whole, taking into consideration interactions between processes and resources (Manes, [0027]).
Sutton in view of Manes does not teach the remaining limitations.
Hoffman teaches
said memory consumption determined by accessing system information of an operation system; (Pg. 1, 9: Windows Task Manager provides process memory usage)
process tree maintained by the operating system (Pg. 1, 6, 19: Windows Task Manager provides process trees)
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine Hoffman’s monitoring with Sutton in view of Chan and Manes’ monitoring.
One of ordinary skill in the art prior to the effective filing date would have been motivated to make the combination because Windows Task Manager is a powerful tool for monitoring processes in Windows-based systems such as Sutton in view of Chan and Manes’ (Hoffman, Pg. 1; Manes, [0013])
Regarding claim 2, Sutton in view of Chan, Manes and Hoffman further teaches
wherein determining anomalies comprises: (Chan, [0056]: problem diagnosis and anomaly detection)
converting texts stored in the log sources into structured data (Chan, [0038]: determine log line representations for log lines), wherein components of the texts are classified with respect to their underlying events and the parameters of the components of text are determined (Chan, [0035], [0038]: group log lines based on the source type and source values), and wherein the structured data differentiates into constant components of the texts from variable components of the texts. (Chan, [0038]: log line representation differentiates between constant components such as source types and variable component such as the source values)
Regarding claim 3, Sutton in view of Chan, Manes and Hoffman further teaches
wherein determining anomalies comprises: (Chan, [0056]: problem diagnosis and anomaly detection)
clustering rows of the log sources using common identifiers used in different rows; (Chan, [0035], [0038]: grouping log lines by source type)
determining parameter values from the clusters; and (Chan, [0038]: extract features from the grouped logs)
converting the clusters into respective number vectors. (Chan, [0039]: generate numerical feature vectors for the grouped logs)
Regarding claim 4, Sutton in view of Chan, Manes and Hoffman further teaches
wherein determining anomalies comprises: (Chan, [0056]: problem diagnosis and anomaly detection)
converting rows of the log sources and their time of arrival stamps into respective number vectors. (Chan, [0034], [0039]: generate feature vectors for the grouped log lines for a time window. Logs contain timestamps)
Regarding claim 5, Sutton in view of Chan, Manes and Hoffman further teaches
wherein determining anomalies comprises: training a machine learning (ML) model using the number vectors, wherein a label designating the cluster as normal or abnormal is created for each cluster, respectively. (Chan, Fig. 3, 6, [0042], [0043]: train a machine learning model using the feature vectors to determine cluster labels for feature vectors as anomalous or normal)
Regarding claim 6, Sutton in view of Chan, Manes and Hoffman further teaches
clustering the anomalies according to a time of their occurrence and/or according to a logging granularity. (Chan, [0042], [0043]: clustering anomalies within a time window)
Regarding claim 10, Sutton in view of Chan, Manes and Hoffman further teaches
A system comprising:
a processor running an application configured to perform the method of claim 1. (Sutton, [0066]: one or more general purpose hardware processors programmed to perform the techniques pursuant to program instructions, inter alia)
Claim(s) 7 is/are rejected under 35 U.S.C. 103 as being unpatentable over US Patent Application Publication No. 20210042180 (“Sutton”) in view of US Patent Application Publication No. 20220179763 (“Chan”), US Patent Application Publication No. 20130047039 (“Manes”), Non-Patent Literature Windows Task Manager: The Complete Guide (“Hoffman”), and US Patent Application Publication No. 20220206886 (“Srivastava”).
Regarding claim 7, Sutton in view of Chan, Manes and Hoffman does not teach the limitations.
Srivastava teaches
for each of the clusters of the anomalies, generating a natural language query that describes the respective anomaly (Srivastava, [0023], [0046]: generate a label for an error log cluster by concatenating terms of the summary of the root cause, and use the label to retrieve a remedial action from a store), wherein the generating comprises examining words in the clusters of the anomalies with respect to the frequency of the words within a cluster, the frequency of the words in all clusters of the log sources (Srivastava, [0039], [0040]: a cluster characterization score is based on the frequency of terms in a cluster and the frequency of terms in all clusters), the frequency of the words in all rows of the log sources (Srivastava, Fig. 4, [0020], [0044]: preprocessing error logs using analysis of the frequency of terms among rows of error messages), and the granularity of the words (Srivastava, [0041]: terms that do not provide useful details on the failure are filtered), and mapping the most frequent words thus determined to natural language sentences. (Srivastava, [0039], [0040], [0046]: maximize the cluster characterization score to generate the summary of the root cause of the cluster of error logs by concatenating the most frequent terms).
In light of the specification, [0013], error messages correspond to rows of logs.
Filtering out terms that do not provide useful details involves considering the detail of the words and corresponds to the granularity of the words.
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine Srivastava’s anomaly clustering with Sutton in view of Manes and Hoffman’s problem diagnosis.
One of ordinary skill in the art prior to the effective filing date would have been motivated to make the combination to allow for root cause analysis of errors in complex systems (Srivastava, [0004], [0015]).
Claim(s) 8 is/are rejected under 35 U.S.C. 103 as being unpatentable US Patent Application Publication No. 20210042180 (“Sutton”) in view of US Patent Application Publication No. 20220179763 (“Chan”), US Patent Application Publication No. 20130047039 (“Manes”), Non-Patent Literature Windows Task Manager: The Complete Guide (“Hoffman”), US Patent Application Publication No. 20220206886 (“Srivastava”), and Non-Patent Literature How To Google Your Errors (“swyz”).
Regarding claim 8, Sutton in view of Chan, Manes, Hoffman, and Srivastava further teaches
wherein querying the database includes applying the natural language query to a database to obtain the solution actions, said solution actions for correcting the respective anomaly, wherein the database contains…anomalies as well as corresponding solution actions (Srivastava, [0023], [0046]: generate a label for an error log cluster by concatenating terms of the summary of the root cause, and use the label to retrieve a remedial action from a store), in particular wherein the solution actions comprise technical steps for resolving the respective anomalies (Srivastava, [0023]: instructions for remedial actions)
Sutton in view of Manes, Hoffman, and Srivastava does not further teach wherein the database contains natural language questions regarding anomalies.
swyz teaches
wherein the database contains natural language questions regarding anomalies (Pg. 4-5: finding Stackoverflow questions that have solutions to the error)
In light of the specification, [0020], the broadest reasonable interpretation of a database is a search engine on the Internet.
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to combine Sutton in view of Manes, Hoffman, and Srivastava’s error remediation and swyz’s error resolution.
One of ordinary skill in the art prior to the effective filing date would have been motivated to make the combination to help find answers to issues that other people have resolved (swyz, Pg. 4-5).
Response to Arguments
Applicant's arguments, see pg. 5-12, filed 03/03/2026, with respect to the 101 rejection(s) of claim(s) 1-8, 10 have been fully considered but they are not persuasive.
On pg. 6, Applicant argues:
“When all of the claim elements are considered as a whole, Applicant's invention of Claim 1 is not directed to an abstract idea. The USPTO has stated (such as in the Memorandum dated November 2, 2016 regarding "Recent Subject Matter Eligibility Decisions") the claims must be considered as a whole and not oversimplified, which is in contrast to how the Office Action considered the claims.
When Applicant's amended claims are considered as a whole, so as to include each and every feature of the claimed invention, it is clear that the only possible conclusion is that Applicant's claimed invention is not directed to merely an abstract idea.”
The Examiner respectfully disagrees. As a whole, the claims are directed to abstract ideas without significantly more. See above rejections.
On pg. 6-7, Applicant argues:
“Thus, even if Applicant's amended claims recite a judicial exception, the amended claims are not "directed to" the judicial exception because the judicial exception is integrated into the claimed practical application of:
determining anomalies in one or more log sources of a system by generating vectors from rows of the log source and their time of arrival stamps, the elements of the vectors reproducing properties of the rows, and by using the vectors as input for a machine learning model which classifies and/or correspondingly marks the vectors as normal or abnormal, said log sources obtained by accessing one or more log files or log
The Office objects against the claimed step of determining anomalies as corresponding to evaluations, "which are mental processes"; "The causes of the anomalies are determined by evaluating the result of a query". The Office refers to the "broadest reasonable interpretation of the limitations as [...]: Log sources are typically manually reviewed by a human to determine anomalies".
Applicant maintains that previously pending claim 1 fully complies with 35 USC 101. Nevertheless, and merely to advance prosecution, Applicant amended claim 1 to specify, inter alia, that determining anomalies is performed "by generating vectors from rows of the log source [...] and [...] using the vectors as input for a machine learning model which classifies [...] the vectors as normal or abnormal." Accordingly, the determining of anomalies is effectively carried out by a machine learning model and not by a human. The objection should be withdrawn.”
The Examiner respectfully disagrees. Generating vectors from data amounts to describing more detail on the mental processes. Reciting that a machine learning model performs the mental processes, amounts to performing mental processes using a computer and is still recitation of a mental process. See MPEP 2106.04(a)(2)(III)(C). Performing mental processes using a computer amounts to mere instructions to implement the abstract ideas on a computer, which is mere instructions to apply an exception. See MPEP 2106.05(f).
On pg. 7, Applicant argues:
“The Office further observes that "The cause of the anomaly from the query can be presented to a human for review." Applicant disagrees and submits that amended claim 1 specifies "determining and correcting causes for each of the anomalies by querying a database that maps preknown causes to respective solution actions," in addition to "presenting the results of the query to a user on a display of the system." Applicant notes that the mere presentation of results does not render the remainder of the claim as reciting "abstract ideas," as the Office appears to assert.”
The Examiner respectfully disagrees. Since a human can review the cause of the anomaly, that means that a human can determine the cause of the anomaly, which is a mental process. See MPEP 2106.04(a)(2)(III)(C). Querying a database is a mere data gathering step that gathers data for performing the mental process. The presentation of the results amounts to mere data output. See MPEP 2106.05(g).
On pg. 7, Applicant argues:
“The Office also asserts that "A computer-implemented method amounts to mere instructions to implement the abstract ideas on a computer." In response, Applicant notes that amended claim 1, in addition to reflecting a computer implemented method, teaches determining and resolving anomalies in a system and therefore cannot be regarded as merely representing abstract ideas.”
The Examiner respectfully disagrees. As noted above, determining anomalies amounts to mental processes. Computer implemented methods amounts to mere instructions to implement the abstract ideas on a computer, which is mere instructions to apply an exception. Resolving anomalies without tying a particular solution to a particular anomaly amounts to an attempt to cover any solution to any identified problem with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, which is mere instructions to apply an exception. See MPEP 2106.05(f).
On pg. 8, Applicant argues:
“The examiner further objects that "said log sources obtained by accessing one or more log files written by a first application amounts to mere data gathering, which is insignificant extra-solution activity". In response thereto, Applicant notes that the claimed features are not "extra-solution activity," but rather integral to the claimed solution. Specifically, the wording refers to logs being written by a "first application." This application is the same application that is analyzed, according to the claim, for "exceeding a predefined frame or a predefined increase rate" in memory consumption, and is also used as a basis for identifying, "based on a process tree [...] applications started by the first application" for detecting anomalies.
Amended claim 1 thus goes beyond "mere data gathering," as asserted in the Office Action. The objection should be withdrawn.”
The Examiner respectfully disagrees. “said log sources obtained by accessing one or more log files written by a first application” merely describes how data to be analyzed is obtained, and therefore amounts to mere data gathering. Specifying the source of data to be analyzed does not go beyond mere data gathering. See MPEP 2106.05(g).
On pg. 8, Applicant argues:
The Office also objects to the claimed "correcting the causes for each of the anomalies [amounting] to an attempt to cover any solution to any identified problem with no restriction on how the result is accomplished [...]".
In response, Applicant submits that amended claim 1 calls for solutions that are in fact restricted on how the result is accomplished. Specifically, claim 1 calls for "a memory consumption of the first application exceeding a predefined frame or a predefined increase rate, said memory consumption determined by accessing system information of an operation system." Furthermore, the solutions reflect solution actions that "include changing a variable, restarting a program, installing an application, and/or updating an installed application." Hence, both the causes and the solutions are restricted and do not "cover any solution to any identified problem," which is contrary to the assertions in the Office Action.
The Examiner respectfully disagrees. The claim lists multiple possible anomalies (“an application having ended within a predefined time period after its start, a memory consumption exceeding a predefined frame or a predefined increase rate, and/or an application starting more frequently than a predefined value within a predefined time period”) and multiple possible solutions (“the solution actions include changing a variable, restarting a program, installing an application, and/or updating an installed application”), but the solutions are not particularly tied to the problems listed. The claim attempts to cover solving any of the problems with any of the solutions, which amounts to mere instructions to apply an exception. See MPEP 2106.05(f).
On pg. 8-9, Applicant argues:
“The Office further objects alleging that "querying a database that maps pre-known causes to respective solution actions amounts to mere data gathering."
In response thereto, Applicant notes that the objected to claim language should not be regarded in isolation but in connection with the claimed use of the queried information. This use includes identifying the particular solution actions for an identified cause, and the subsequent "applying [of] the [...] solution actions to the system." The objected to claim language goes beyond mere data gathering.”
The Examiner respectfully disagrees. Querying a data source for information amounts to mere data gathering. See MPEP 2106.05(g).The fact that the information includes solution actions does not mean the querying goes beyond mere data gathering because the application of the solution actions attempts to cover solving any of the problems with any of the solutions, which amounts to mere instructions to apply an exception. See MPEP 2106.05(f).
On pg. 9, Applicant argues:
“The Office objects to "presenting the results of the query to a user on a display of the system [which] amounts to mere data output." In response, Applicant notes that the claim features should not be regarded in isolation, but in connection with the subsequent step of "receiving a selected and configured solution actions of the presented solution actions from the user." The claim language goes beyond mere data output in that it permits users to select and configure the presented solution actions.
Similar reasoning applies to the subsequent objection against "receiving a selected and configured solution action" which, when regarded in combination with the preceding features, does not amount to mere data gathering, but amounts to user interaction and improvement of proposed solution actions.
The Office objects to "storing the configured solution action in the database [which] amounts to mere data gathering." In response Applicant notes that "storing" is in contrast to "gathering" and hence cannot be regarded as mere data gathering.”
The Examiner respectfully disagrees. Storing and gathering data have the same meaning. The claim does not reflect how proposed solution actions are improved by "receiving a selected and configured solution action". See MPEP 2106.05(a).The user interaction to select and store presented data amounts to mere data gathering and output. See MPEP 2106.05(g).
On pg. 9-10, Applicant argues:
“The Office also objects as follows: "said memory consumption determined by accessing system information of an operation system; process tree maintained by the operating system [which] amounts to mere data gathering." In response, Applicant notes that the claim language does not relate to "memory consumption determined by accessing system information of an operation system" to "a process tree maintained by the operating system", as the Office appears to imply. Rather, determining memory consumption is part of "determining anomalies is started" (emphasis added) whereas the process is used in the course of "determining further applications" during "determining anomalies." Both aspects do not relate to mere data gathering, but rather to identifying causes for starting anomaly detection for a first application and to identifying further applications for anomaly detection, respectively.”
The Examiner respectfully disagrees. The claim amounts to gathering data that is evaluated using mental processes and using the mental processes to determine whether to start performing other mental processes. Therefore, “said memory consumption determined by accessing system information of an operation system; process tree maintained by the operating system” amount to mere data gathering. See MPEP 2106.05(g).
On pg. 10-12, Applicant argues:
“Even if claim 1 is directed to an abstract idea, which Applicant maintains that it is not, claim 1 satisfies § 101 because it includes numerous additional elements that amount to significantly more than the judicial exception. As explained in the USPTO's November 2, 2016 Memorandum:
""In step 2B of the USPTO's SME guidance, Examiners should consider the additional elements in combination, as well as individually, when determining whether a claim as a whole amounts to significantly more, as this may be found in the non-conventional and non-generic arrangement of known, conventional elements."
The Office asserts that claim is directed to an abstract idea and does not recite additional elements that amount to "significantly more" than the exception. Applicant respectfully submits that the rejection is improper because claim 1, and those claims dependent therefrom, recite specific, non-conventional elements that transform the alleged exception into a patent-eligible application.
Under the 2019 Revised Patent Subject Matter Eligibility Guidance, Step 2B asks whether the claim elements, individually or in ordered combination, amount to "significantly more" than a judicial exception by adding limitations that are not well- understood, routine, or conventional in the field.
Claim 1 does not merely invoke generic computer implementation of an abstract idea. Rather, the claim calls for the following (emphasis added):
The features of claim 1, and those claims dependent therefrom, go beyond simply "applying" an alleged abstract idea. Each recited element provides concrete structure and functionality that cannot be characterized as routine or conventional. When considered as an ordered combination, the claim elements provide a technical improvement in the field of "determining anomalies in one or more log sources of a system," etc., as set forth in claim 1.
Such features and improvements set forth in amended claim 1 constitute significantly more than a judicial exception, in line with cases such as DDR Holdings, LLC v. Hotels.com (solution to a technological problem), and BASCOM Global Internet v. AT&T Mobility (non-conventional combination of known elements).
Applicant submits that the claim elements of amended independent claim 1 are not well-understood, routine, or conventional. And the Office has not provided any evidence that the above-recited elements are well-understood, routine, or conventional. MPEP §2106.05(d) makes clear that mere conclusory statements (such as those set forth in the Office Action) are insufficient. Applicant submits that the claimed features, both individually and in combination, reflect specific technical solutions developed by Applicant and therefore cannot be dismissed as routine.
For the foregoing reasons, amended claim 1 recites additional elements that amount to significantly more than any alleged judicial exception, and thus satisfy the requirements of 35 U.S.C. §101. Applicant respectfully requests withdrawal of the §101 rejections.”
The Examiner respectfully disagrees. The claim as a whole does not include additional elements that are sufficient to amount to significantly more than the judicial exceptions because the additional elements amount to mere instructions to apply an exception and insignificant extra-solution activity. See MPEP 2106.05(f) and MPEP 2106.05(g). No additional elements have been indicated as well-understood, routine, or conventional under MPEP §2106.05(d), and therefore “mere conclusory statements” were never made.
Applicant’s arguments, see pg. 12-15, filed 03/03/2026, with respect to the 103 rejection(s) of claim(s) 1-8, 10 have been fully considered and are persuasive because the amendments changed the scope of the claims. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of previously cited prior art.
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.
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/A.L./Examiner, Art Unit 2113
/MARC DUNCAN/Primary Examiner, Art Unit 2113
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