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 .
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 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.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1, 2, and 6-10 are rejected under 35 U.S.C. 102(a)(1)/(a)(2) as being anticipated by Urabe (US 2024/0289717 A1, hereinafter referenced “Urabe”).
In regards to claim 1. Urabe discloses an information processing apparatus (Urabe, Abstract) comprising:
-a memory (Urabe, para [0064]; Reference discloses the storage unit 14 (i.e. memory) stores various types of information referred to when the control unit 15 operates and various types of information acquired when the control unit 15 operates);
-and a processor coupled to the memory (Urabe, Fig. 1; Reference illustrates control unit 15 (i.e. processor) coupled to storage unit 14) and the processor configured to: extract an actual measurement value of a resource used by a function included in a system from a log file acquired from the system (Urabe, para [0065] and [0067]; Reference at para [0065] discloses For example, the operation log storage unit 14 a stores “operation time,” “case ID,” “operation location (window information),” “operation location (GUI component, coordinates, etc.),” and “input value” as an operation log (i.e. extracted actual measurement value of resource for function regarding user’s operation). Para [0067] discloses the acquisition unit 15a acquires an operation log (i.e. acquired log file from system));
-calculate a score of the function on a basis of the actual measurement value of the resource used by the function and an upper limit value of the resource available by the function (Urabe, para [0068] and [0079]; Reference at para [0068] discloses the alignment unit 15b generates an operation sequence in units of operations arrayed in a time series order for each case on the basis of the operation log, and aligns the operation sequence in units of operations. Para [0079] discloses the alignment unit 15 b uses an operation sequence for each operation sequence type and performs sequence alignment of operation sequences using a progressive alignment method which is one of multiple sequence alignment methods. Specifically, first, the alignment unit 15 b applies a sequence alignment method (pairwise alignment) to two operation sequences, extracts a difference score between these operation sequences, and stores it in a distance matrix (procedure 1) (i.e. calculated score of function regarding operation based on data from operation log containing input value as difference score is assessed between two operation sequences thus being actual measurement value and a higher or upper limit value));
-generate information visualizing the score of the function (Urabe, para [0071]; Reference discloses the visualization unit 15 c specifies operation types that appear with a threshold or more at the same position in the operation sequence in units of operations for each case, as the operation type of the main flow, on the basis of the aligned operation sequence in units of operations, and arranges and visualizes nodes corresponding to the operation type of the main flow in a time series order on one axis (i.e. generating info for visualizing score of function));
-and display the information (Urabe, para [0072]; Reference discloses in addition, the visualization unit 15 c outputs the visualization result to the output unit 12).
In regards to claim 2. Urabe discloses the information processing apparatus according to claim 1.
Urabe further discloses
-wherein the processor is further configured to acquire a log file transmitted from the system at a constant cycle (Urabe, Fig. 15 and para [0105]; Reference discloses in a case where the user has neither stop the process nor dropped the PC terminal (step S201: No), the acquisition unit 15 a acquires an operation log (step S202). Next, the acquisition unit 15 a accumulates the operation log by storing the acquired operation log in the operation log storage unit 14 a (step S203), and proceeds to the process of step S201 (i.e. interpreted as constant cycle for log file acquisition unless user drops or stops process)).
In regards to claim 6. Urabe discloses the information processing apparatus according to claim 1.
Urabe further discloses
-wherein the processor is further configured to increase the score of the function as a difference between the actual measurement value of the resource used by the function and the upper limit value of the resource available by the function increases (Urabe, para [0068] and [0079]; Reference at para [0068] discloses the alignment unit 15b generates an operation sequence in units of operations arrayed in a time series order for each case on the basis of the operation log, and aligns the operation sequence in units of operations. Para [0079] discloses the alignment unit 15 b uses an operation sequence for each operation sequence type and performs sequence alignment of operation sequences using a progressive alignment method which is one of multiple sequence alignment methods. Specifically, first, the alignment unit 15 b applies a sequence alignment method (pairwise alignment) to two operation sequences, extracts a difference score between these operation sequences, and stores it in a distance matrix (procedure 1) (i.e. calculated score of function regarding operation based on data from operation log containing input value as difference score is assessed between two operation sequences thus being actual measurement value and a higher or upper limit value)).
In regards to claim 7. Urabe discloses the information processing apparatus according to claim 1.
Urabe further discloses
-wherein the processor is further configured to repeatedly execute processing of calculating the score of the function at a constant cycle, and generate a time-series score for the function (Urabe, para [0068], [0079], and [0105]; Reference at para [0068] discloses the alignment unit 15b generates an operation sequence in units of operations arrayed in a time series order for each case on the basis of the operation log, and aligns the operation sequence in units of operations. Para [0079] discloses the alignment unit 15 b uses an operation sequence for each operation sequence type and performs sequence alignment of operation sequences using a progressive alignment method which is one of multiple sequence alignment methods. Specifically, first, the alignment unit 15 b applies a sequence alignment method (pairwise alignment) to two operation sequences, extracts a difference score between these operation sequences, and stores it in a distance matrix (procedure 1)). Para [0105] discloses in a case where the user has neither stop the process nor dropped the PC terminal (step S201: No), the acquisition unit 15 a acquires an operation log (step S202). Next, the acquisition unit 15 a accumulates the operation log by storing the acquired operation log in the operation log storage unit 14 a (step S203), and proceeds to the process of step S201 (i.e. interpreted as constant cycling)).
In regards to claim 8. Urabe discloses the information processing apparatus according to claim 7.
Urabe further discloses
-wherein the processor is further configured to generate a graph indicating a relationship between time and the score for the function (Urabe, Fig. 8; Illustrates time order sequence data or scores for operations shown correlated in tree diagram).
In regards to claim 9. Urabe discloses a visualization method that causes a computer to execute a process (Urabe, Abstract) comprising:
-extracting an actual measurement value of a resource used by a function included in a system from a log file acquired from the system (Urabe, para [0065] and [0067]; Reference at para [0065] discloses For example, the operation log storage unit 14 a stores “operation time,” “case ID,” “operation location (window information),” “operation location (GUI component, coordinates, etc.),” and “input value” as an operation log (i.e. extracted actual measurement value of resource for function regarding user’s operation). Para [0067] discloses the acquisition unit 15a acquires an operation log (i.e. acquired log file from system));
-calculating a score of the function on a basis of the actual measurement value of the resource and an upper limit value of the resource available by the function (Urabe, para [0068] and [0079]; Reference at para [0068] discloses the alignment unit 15b generates an operation sequence in units of operations arrayed in a time series order for each case on the basis of the operation log, and aligns the operation sequence in units of operations. Para [0079] discloses the alignment unit 15 b uses an operation sequence for each operation sequence type and performs sequence alignment of operation sequences using a progressive alignment method which is one of multiple sequence alignment methods. Specifically, first, the alignment unit 15 b applies a sequence alignment method (pairwise alignment) to two operation sequences, extracts a difference score between these operation sequences, and stores it in a distance matrix (procedure 1) (i.e. calculated score of function regarding operation based on data from operation log containing input value as difference score is assessed between two operation sequences thus being actual measurement value and a higher or upper limit value));
-and generating and displaying information visualizing the score of the function (Urabe, para [0071] and [0072]; Reference at [0071] discloses the visualization unit 15 c specifies operation types that appear with a threshold or more at the same position in the operation sequence in units of operations for each case, as the operation type of the main flow, on the basis of the aligned operation sequence in units of operations, and arranges and visualizes nodes corresponding to the operation type of the main flow in a time series order on one axis (i.e. generating info for visualizing score of function). Para [0072] discloses in addition, the visualization unit 15 c outputs the visualization result to the output unit 12).
In regards to claim 10. Urabe discloses a non-transitory computer-readable recording medium having stored therein a visualization program that causes a computer to execute a process (Urabe, para [0175]) comprising:
-extracting an actual measurement value of a resource used by a function included in a system from a log file acquired from the system (Urabe, para [0065] and [0067]; Reference at para [0065] discloses For example, the operation log storage unit 14 a stores “operation time,” “case ID,” “operation location (window information),” “operation location (GUI component, coordinates, etc.),” and “input value” as an operation log (i.e. extracted actual measurement value of resource for function regarding user’s operation). Para [0067] discloses the acquisition unit 15a acquires an operation log (i.e. acquired log file from system));
-calculating a score of the function on a basis of the actual measurement value of the resource and an upper limit value of the resource available by the function (Urabe, para [0068] and [0079]; Reference at para [0068] discloses the alignment unit 15b generates an operation sequence in units of operations arrayed in a time series order for each case on the basis of the operation log, and aligns the operation sequence in units of operations. Para [0079] discloses the alignment unit 15 b uses an operation sequence for each operation sequence type and performs sequence alignment of operation sequences using a progressive alignment method which is one of multiple sequence alignment methods. Specifically, first, the alignment unit 15 b applies a sequence alignment method (pairwise alignment) to two operation sequences, extracts a difference score between these operation sequences, and stores it in a distance matrix (procedure 1) (i.e. calculated score of function regarding operation based on data from operation log containing input value as difference score is assessed between two operation sequences thus being actual measurement value and a higher or upper limit value));
-and generating and displaying information visualizing the score of the function (Urabe, para [0071] and [0072]; Reference at [0071] discloses the visualization unit 15 c specifies operation types that appear with a threshold or more at the same position in the operation sequence in units of operations for each case, as the operation type of the main flow, on the basis of the aligned operation sequence in units of operations, and arranges and visualizes nodes corresponding to the operation type of the main flow in a time series order on one axis (i.e. generating info for visualizing score of function). Para [0072] discloses in addition, the visualization unit 15 c outputs the visualization result to the output unit 12).
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 of this title, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 3-5 are rejected under 35 U.S.C. 103 as being unpatentable over Urabe (US 2024/0289717 A1) in view of Bingham (US 2019/0303365 A1, hereinafter referenced “Bingham”).
In regards to claim 3. Urabe discloses the information processing apparatus according to claim 1.
Urabe does not explicitly disclose but Bingham teaches
-wherein the processor is further configured to extract the actual measurement value of the resource from the log file on a basis of definition information defining a regular expression of the resource (Bingham, para [0009] and [0075]; Reference at para [0009] discloses time stamped events can also be stored for other types of information. Events can identify tasks (e.g., collecting, storing, retrieving, and/or processing of big-data) assigned to and/or performed by hypervisor components and/or data received and/or processed by a hypervisor component. For example, a stream of data (e.g., log files, big data, machine data, and/or unstructured data) can be received from one or more data sources. Para [0075] discloses task definer 215 can define one or more retrieval, field-extraction and/or processing tasks based on the query. For example, multiple retrieval tasks can be defined, each involving a different portion of the time period. Task definer 215 can also define a task to apply a schema so as to extract particular value of fields or a task to search for a keyword. Values extracted can be for fields identified in the query and/or for other fields (e.g., each field defined in the schema) (i.e. schema interpreted as definition info defining a regular expression of the resource)).
Urabe and Bingham are combinable because they are in the same field of endeavor regarding log data processing and visualization. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention for the visualization display device of Urabe to include the log data performance correlation features of Bingham in order to provide the user with a method for acquiring operation log data and generating operation sequences for providing subsequent visualization data showing nodes corresponding to operation types in time series order as taught by Urabe while incorporating the log data performance correlation features of Bingham to allow for acquiring and storing performance measurements relating to performance of a component within an IT environment and log data in association with time stamps where performance correlations can be determined from the data thus improving the ability for monitoring a systems performance, applicable to log data visualization systems such as those taught in Urabe.
In regards to claim 4. Urabe in view of Bingham teach the information processing apparatus according to claim 3.
Urabe does not explicitly disclose but Bingham teaches
-wherein the definition information further defines a regular expression of an event, and the processor is further configured to extract content and an occurrence frequency of the event from the log file on a basis of the regular expression of the event (Bingham, para [0009] and [0075]; Reference at para [0009] discloses time stamped events can also be stored for other types of information. Events can identify tasks (e.g., collecting, storing, retrieving, and/or processing of big-data) assigned to and/or performed by hypervisor components and/or data received and/or processed by a hypervisor component. For example, a stream of data (e.g., log files, big data, machine data, and/or unstructured data) can be received from one or more data sources. Para [0075] discloses the query can be received from a search engine via a search-engine interface 217. The query can identify events of interest. The query can be for one or more types of events, such as data events or performance events (e.g., searching for performance events with below-threshold performance values of a performance metric) (i.e. extracting content and occurrence frequency based on specified events below-threshold)… task definer 215 can define one or more retrieval, field-extraction and/or processing tasks based on the query. For example, multiple retrieval tasks can be defined, each involving a different portion of the time period. Task definer 215 can also define a task to apply a schema so as to extract particular value of fields or a task to search for a keyword. Values extracted can be for fields identified in the query and/or for other fields (e.g., each field defined in the schema) (i.e. schema interpreted as definition info defining a regular expression of the event)).
Urabe and Bingham are combinable because they are in the same field of endeavor regarding log data processing and visualization. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention for the visualization display device of Urabe to include the log data performance correlation features of Bingham in order to provide the user with a method for acquiring operation log data and generating operation sequences for providing subsequent visualization data showing nodes corresponding to operation types in time series order as taught by Urabe while incorporating the log data performance correlation features of Bingham to allow for acquiring and storing performance measurements relating to performance of a component within an IT environment and log data in association with time stamps where performance correlations can be determined from the data thus improving the ability for monitoring a systems performance, applicable to log data visualization systems such as those taught in Urabe.
In regards to claim 5. Urabe in view of Bingham teach the information processing apparatus according to claim 4.
Urabe does not explicitly disclose but Bingham teaches
-wherein the processor is further configured to calculate the score of the function by further using the content and the occurrence frequency of the event (Bingham, para [0092] and [0094]; Reference at [0092] discloses a statistics generator 340 can access the collection of performance metrics and generate one or more performance statistics based on the values of one or more performance metrics. A performance statistic can pertain to any of the various types of performance metrics, such as a CPU usage, a memory usage, assigned tasks, a task-completion duration, etc. Para [0094] discloses if a statistic is below the first threshold, then a first state (e.g., a “normal” state) is assigned; if a statistic is between the thresholds, then a second state (e.g., a “warning” state) is assigned; if a statistic is above the second threshold, then a third state (e.g., a “critical state”) is assigned. The state criteria can pertain to multiple statistics (e.g., having a function where a warning state is assigned if any of three statistics are below a respective threshold or if a score generated based on multiple statistics is below a threshold (i.e. calculated score based on content and then occurrence frequency of an event with respect to scoring across multiple statistics).
Urabe and Bingham are combinable because they are in the same field of endeavor regarding log data processing and visualization. It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention for the visualization display device of Urabe to include the log data performance correlation features of Bingham in order to provide the user with a method for acquiring operation log data and generating operation sequences for providing subsequent visualization data showing nodes corresponding to operation types in time series order as taught by Urabe while incorporating the log data performance correlation features of Bingham to allow for acquiring and storing performance measurements relating to performance of a component within an IT environment and log data in association with time stamps where performance correlations can be determined from the data thus improving the ability for monitoring a systems performance, applicable to log data visualization systems such as those taught in Urabe.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure: See the Notice of References Cited (PTO-892)
Any inquiry concerning this communication or earlier communications from the examiner should be directed to TERRELL M ROBINSON whose telephone number is (571)270-3526. The examiner can normally be reached 8am-5pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, KENT CHANG can be reached at 571-272-7667. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/TERRELL M ROBINSON/Primary Examiner, Art Unit 2614
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