Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
DETAILED ACTION
Applicant has amended claims 1-3, 5, 7-9, 11, 13-15, 17 in the filed amendment on 1/26/2026.
Claims 1-20 are pending in this office action.
Response to Arguments
Applicant’s arguments with respect to claim(s) 1-20 have been considered but are moot in new ground of rejection.
For 101 rejection:
Applicant argued that claims 1, 7, and 13 have been amended to overcome 101 rejection. Independent claims 1, 7, and 13 as amended, recite specific improvement in time-series data processing, rather than a mental process or mathematical concept. The claimed method requires specialized computer components including a user interface, a time-series database, and processor-executed analysis operators, and implements a concrete technical workflow in which the computing device retrieves digital time- series data, processes the data using a trained analysis operator, computes updated model parameters based on the processed data, generates an updated operator, and reapplies the updated operator to later-arriving data. These steps cannot be performed mentally and provide a technological solution to a technological problem, namely the inefficiency and computational cost of repeatedly retraining models for sequential data analysis. Accordingly, the claims recite significantly more than any alleged abstract idea and are patent-eligible under §101.
Examiner respectfully disagrees.
Claims 1, 7, 13 similarly recite abstract ideas of
(analyzing, in response to the first analysis mode, the first time series data using a first time series analysis operator comprising a first model parameter;
updating the first time series analysis operator based on the first time series data and the first model parameter;
determining a second model parameter based on the first time series data and the first model parameter;
determining an updated first time series analysis operator based on the second model parameter;
analyzing the second time series data using the updated first time series analysis operator) because the human mind can perform step of analyzing, updating, determining, determining and analyzing. Accordingly, the claims recite an abstract idea.
The additional elements of one or more processor (in claims 1, 7, 13); a memory configured to store instructions; and one or more processors coupled to the memory, wherein when executed by the one or more processors, the instructions cause the apparatus to (in claim 7); and computer-executable instructions that are stored on a non-transitory computer-readable storage medium and that, when executed by one or more processors, cause an apparatus to (claim 13) that are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using a generic computer component for obtaining that are well understood routine and conventional activities.
The additional limitation of (receiving a first analysis mode selected through a user interface; retrieve, from a time-series database, first time-series data, retrieving, from the time-series database, second time-series data occurring after the first time-series data) that just indicates ordering of first data and second data and that would be insignificant post-solution data outputting, and are insignificant extra solution activities which are well understood routine and conventional activities, see (Presenting offers and gathering statistics, OIP Techs and Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec) and See (MPEP 2106.05(g) or 2106.05(d) for Receiving or transmitting data over a network, e.g. see Intellectual Ventures v. Symantec; Storing and retrieving information in memory: Versata; Analyzing data: Genetic Techs; Determining: OIP Techs; Electronic recordkeeping: Alice Corp).
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea and these additional elements do not amount to significantly more than the judicial exception. The claims are directed to an abstract idea.
In addition,
step 2A Prong One
Claims 1, 7, 13 recite abstract idea of
(analyzing, in response to the first analysis mode, the first time series data using a first time series analysis operator comprising a first model parameter;
updating the first time series analysis operator based on the first time series data and the first model parameter;
determining a second model parameter based on the first time series data and the first model parameter;
determining an updated first time series analysis operator based on the second model parameter;
analyzing the second time series data using the updated first time series analysis operator) as drafted, is a process or system or medium that, under its broadest reasonable interpretation, covers performance of the limitations in the mind but for the recitation of generic computer components. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. The human mind can perform step of analyzing, updating, determining, determining and analyzing. Accordingly, the claims recite an abstract idea.
step 2A Prong Two
Claims do not recite any additional elements that integrate the judicial exception into a practical application because additional elements of one or more processor (in claims 1, 7, 13); a memory configured to store instructions; and one or more processors coupled to the memory, wherein when executed by the one or more processors, the instructions cause the apparatus to (in claim 7); and computer-executable instructions that are stored on a non-transitory computer-readable storage medium and that, when executed by one or more processors, cause an apparatus to (claim 13) that are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using a generic computer component for obtaining that are well understood routine and conventional activities.
The additional limitation of (receiving a first analysis mode selected through a user interface; retrieve, from a time-series database, first time-series data, retrieving, from the time-series database, second time-series data occurring after the first time-series data) that just indicates ordering of first data and second data and that would be insignificant post-solution data outputting, and are insignificant extra solution activities which are well understood routine and conventional activities, see (Presenting offers and gathering statistics, OIP Techs and Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec) and See (MPEP 2106.05(g) or 2106.05(d) for Receiving or transmitting data over a network, e.g. see Intellectual Ventures v. Symantec; Storing and retrieving information in memory: Versata; Analyzing data: Genetic Techs; Determining: OIP Techs; Electronic recordkeeping: Alice Corp).
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea.
Step 2B:
Claims do not recite any additional elements that amount to significantly more than the judicial exception because additional elements of one or more processor (in claims 1, 7, 13); a memory configured to store instructions; and one or more processors coupled to the memory, wherein when executed by the one or more processors, the instructions cause the apparatus to (in claim 7); and computer-executable instructions that are stored on a non-transitory computer-readable storage medium and that, when executed by one or more processors, cause an apparatus to (claim 13) that are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using a generic computer component for obtaining that are well understood routine and conventional activities.
The additional limitation of (receiving a first analysis mode selected through a user interface; retrieve, from a time-series database, first time-series data, retrieving, from the time-series database, second time-series data occurring after the first time-series data) that just indicates ordering of first data and second data and that would be insignificant post-solution data outputting, and are insignificant extra solution activities which are well understood routine and conventional activities, see (Presenting offers and gathering statistics, OIP Techs and Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec) and See (MPEP 2106.05(g) or 2106.05(d) for Receiving or transmitting data over a network, e.g. see Intellectual Ventures v. Symantec; Storing and retrieving information in memory: Versata; Analyzing data: Genetic Techs; Determining: OIP Techs; Electronic recordkeeping: Alice Corp).
Accordingly, these additional elements do not amount to significantly more than the judicial exception. The claims are not patent eligible.
For 103 rejection:
Applicant argued that amended claims overcome 103 rejection.
In response to Applicant’s argument claims are rejected under new ground.
In addition:
Hsiao teaches limitations
“receiving a first analysis mode selected through a user interface” as in response to the selection of either user-interface element 1766 or user-interface element 1768, the GUI may further group event stream information shown in the table (figs. 17A-17B, paragraph 254) that indicates the GUI receives the user-interface element 1766 or 1768 as a first analysis mode selected via a user interface (figs. 17A-17B, paragraph 254).
In particularly: Selection of one user-interface element 1766-1768 may result in the automatic deselection of the other user-interface element. In response to the selection of either user-interface element 1766 or user-interface element 1768, the GUI may further group event stream information shown in the table by the event stream lifecycle represented by the selected user-interface element. For example, the GUI may show only permanent event streams that match the “HTTP” protocol classification in the table of FIG. 17A because user-interface element 1766 and “HTTP” are selected (paragraph 254);
“……first time-series data” as displaying on interface a first time series event data as first time series data e.g., first row in table using a first table that includes columns 1750, 1734-1750 is represented as a first time series analysis operator (fig. 17C, paragraphs 273-274, 281);
“analyzing, in response to the first analysis mode, the first time series data using a first time series analysis operator comprising……” as grouping as analyzing, in response to the user-interface element 1766 or 1768 as the first analysis model, first time series event data as first time series data e.g., first row using a first table as a first time series analysis operator comprising first column 1750 (figs. 17A-17C, paragraphs 254-255, 273-274, 281);
“updating the first time series analysis operator based on the first time series data and ……by:” as including or adding as updating a first table as a first time series analysis operator based on the first time series event data in the first row as first time series data (fig. 17C) and the first column 1750 by: (figs. 17C-17D, paragraphs 287-288):
For example, the user may select the user-interface element in the first row of column 1750 to view event stream information for 120 ephemeral event streams belonging to the group named “Group_A,” as discussed in further detail below with respect to FIG. 17D (paragraph 273).
FIG. 17D shows an exemplary screenshot in accordance with the disclosed embodiments. More specifically, FIG. 17D shows the GUI of FIG. 17C after the user-interface element in the first row of column 1750 has been selected. In response to the selected user-interface element, the table includes additional event stream information for ephemeral event streams in the group represented by the first row in the table. As shown in FIG. 17D, the additional event stream information includes an additional grouping of ephemeral event streams in the “Group_A” group by protocol (paragraph 287);
“determining ……based on the first time series data and……” as selecting as determining user-interface element e.g., Group_A in the first row of column 1750 as based on the first row that includes start time and end time as the first time series data and the column 1750 (paragraphs 273-274, fig. 17C).
For example, selection of the group _A value in column 1734 may cause the GUI to navigate to a screen showing events and the corresponding timestamps of the ephemeral event streams of group _A, graphs of metrics related to the events, and/or other information associated with the events (paragraph 274);
“determining an updated first time series analysis operator based on……” as representing a table that includes addition event streams e.g., HTTP-80, HTTP-20, is represented as updated first time series analysis operator (fig. 17D, paragraph 287).
FIG. 17D shows an exemplary screenshot in accordance with the disclosed embodiments. More specifically, FIG. 17D shows the GUI of FIG. 17C after the user-interface element in the first row of column 1750 has been selected. In response to the selected user-interface element, the table includes additional event stream information for ephemeral event streams in the group represented by the first row in the table. As shown in FIG. 17D, the additional event stream information includes an additional grouping of ephemeral event streams in the “Group_A” group by protocol (paragraph 287);
“……the updated first time series analysis operator” as representing a table that includes addition event streams e.g., HTTP-80, HTTP-20, is represented as updated first time series analysis operator (fig. 17D, paragraph 287).
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.
Per Step 1, claim 1 is directed to a method, 7 is directed to an apparatus, and 13 is directed to a computer program product, which are statutory categories of invention per Step 1. However, the claims are rejected under 35 U.S.C. 101 because they are directed to an abstract idea, a judicial exception, without reciting additional elements that integrate the judicial exception into a practical application or are significantly more.
Step 2:
a) In analyzing under step 2A Prong One, Does the claim recite an abstract idea law of nature or natural phenomenon? Yes.
Claims 1, 7, 13 recite abstract idea of
(analyzing or analyze, in response to the first analysis mode, the first time series data using a first time series analysis operator comprising a first model parameter;
updating or update the first time series analysis operator based on the first time series data and the first model parameter by:
determining a second model parameter based on the first time series data and the first model parameter;
determining an updated first time series analysis operator based on the second model parameter;
analyzing or analyze the second time series data using the updated first time series analysis operator) as drafted, is a process or system or medium that, under its broadest reasonable interpretation, covers performance of the limitations in the mind but for the recitation of generic computer components. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. The human mind can perform step of analyzing, updating, determining, determining and analyzing. Accordingly, the claims recite an abstract idea.
b) In analyzing under step 2A Prong Two, Does the claim recite additional elements that integrate the judicial exception into a practical application? NO.
Claims do not recite any additional elements that integrate the judicial exception into a practical application because additional elements of one or more processor (in claims 1, 7, 13); a memory configured to store instructions; and one or more processors coupled to the memory, wherein when executed by the one or more processors, the instructions cause the apparatus to (in claim 7); and computer-executable instructions that are stored on a non-transitory computer-readable storage medium and that, when executed by one or more processors, cause an apparatus to (claim 13) that are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using a generic computer component for obtaining that are well understood routine and conventional activities.
The additional limitation of (receiving or receive a first analysis mode selected through a user interface; retrieving or retrieve, from a time-series database, first time-series data; retrieving or retrieve, from the time-series database, second time-series data occurring after the first time-series data) that just indicates ordering of first data and second data and that would be insignificant post-solution data outputting, and are insignificant extra solution activities which are well understood routine and conventional activities, see (Presenting offers and gathering statistics, OIP Techs and Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec) and See (MPEP 2106.05(g) or 2106.05(d) for Receiving or transmitting data over a network, e.g. see Intellectual Ventures v. Symantec; Storing and retrieving information in memory: Versata; Analyzing data: Genetic Techs; Determining: OIP Techs; Electronic recordkeeping: Alice Corp).
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea.
c) In analyzing under step 2B, does the claim recite additional elements that amount to significantly more than the judicial exception? NO
Claims do not recite any additional elements that amount to significantly more than the judicial exception because additional elements of one or more processor (in claims 1, 7, 13); a memory configured to store instructions; and one or more processors coupled to the memory, wherein when executed by the one or more processors, the instructions cause the apparatus to (in claim 7); and computer-executable instructions that are stored on a non-transitory computer-readable storage medium and that, when executed by one or more processors, cause an apparatus to (claim 13) that are recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using a generic computer component for obtaining that are well understood routine and conventional activities.
The additional limitation of (receiving or receive a first analysis mode selected through a user interface; retrieving or retrieve, from a time-series database, first time-series data, retrieving or retrieve, from the time-series database, second time-series data occurring after the first time-series data) that just indicates ordering of first data and second data and that would be insignificant post-solution data outputting, and are insignificant extra solution activities which are well understood routine and conventional activities, see (Presenting offers and gathering statistics, OIP Techs and Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec) and See (MPEP 2106.05(g) or 2106.05(d) for Receiving or transmitting data over a network, e.g. see Intellectual Ventures v. Symantec; Storing and retrieving information in memory: Versata; Analyzing data: Genetic Techs; Determining: OIP Techs; Electronic recordkeeping: Alice Corp).
Accordingly, these additional elements do not amount to significantly more than the judicial exception. The claims are not patent eligible.
Dependent claims 2-6, 8-12, 14-20 include all the limitations of claims 1, 7, 13. Therefore, claims 2-6, 8-12, 14-20 recite the same abstract idea of processing and generating practically being performed in the mind, and the analysis must therefore proceed to Step 2A Prong Two.
In particularly:
Claims 2, 8, 14, recite limitation of (determining the first model parameter using an exponential moving average algorithm; or determine the first model parameter using a stochastic gradient decent (SGD) algorithm) as drafted, is a process or system or medium that, under its broadest reasonable interpretation, covers performance of the limitations in the mind but for the recitation of generic computer components. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. The human mind can perform step of updating, determining and determining. Accordingly, the claims recite an abstract idea.
Claims 3, 9, 15, recite abstract idea of (storing or store the second model parameter) that would be insignificant post-solution data outputting, and are insignificant extra solution activities which are well understood routine and conventional activities, see (Presenting offers and gathering statistics, OIP Techs and Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec) and See (MPEP 2106.05(g) or 2106.05(d) for Receiving or transmitting data over a network, e.g. see Intellectual Ventures v. Symantec; Storing and retrieving information in memory: Versata; Analyzing data: Genetic Techs; Determining: OIP Techs; Electronic recordkeeping: Alice Corp).
Claims 4, 10, 16 recite abstract idea of (training the first time series analysis operator based on third time series data) as drafted, is a process or system or medium that, under its broadest reasonable interpretation, covers performance of the limitations in the mind but for the recitation of generic computer components. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. The human mind can perform step of training. Accordingly, the claims recite an abstract idea.
The additional limitation of (wherein the third time series data is before the first time series data) that just indicate third data is before first data.
Claims 5, 11, 17 recite abstract limitation of (obtaining or obtain the third time series data from the time series database) that would be insignificant post-solution data outputting, and are insignificant extra solution activities which are well understood routine and conventional activities, see (Presenting offers and gathering statistics, OIP Techs and Receiving or transmitting data over a network, e.g., using the Internet to gather data, Symantec) and See (MPEP 2106.05(g) or 2106.05(d) for Receiving or transmitting data over a network, e.g. see Intellectual Ventures v. Symantec; Storing and retrieving information in memory: Versata; Analyzing data: Genetic Techs; Determining: OIP Techs; Electronic recordkeeping: Alice Corp).
Claims 6, 12, 18 recite limitations (training a second time series analysis operator based on the first time series data; and analyzing, in response to a second analysis mode input, the first time series data using the second time series analysis operator) as drafted, is a process or system or medium that, under its broadest reasonable interpretation, covers performance of the limitations in the mind but for the recitation of generic computer components. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. The human mind can perform step of training and analyzing. Accordingly, the claims recite an abstract idea.
Claims do not recite any additional elements that amount to significantly more than the judicial exception because additional element of user that is recited at a high-level of generality such that it amounts no more than mere instructions to apply the exception using a generic computer component for obtaining that are well understood routine and conventional activities.
Claim 19 recites limitation (determine the first model parameter using a moving average algorithm) as drafted, is a process or system or medium that, under its broadest reasonable interpretation, covers performance of the limitations in the mind but for the recitation of generic computer components. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. The human mind can perform step of determining. Accordingly, the claims recite an abstract idea.
Claim 20 recites limitation (determine the first model parameter using an exponential moving average algorithm) as drafted, is a process or system or medium that, under its broadest reasonable interpretation, covers performance of the limitations in the mind but for the recitation of generic computer components. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. The human mind can perform step of training. Accordingly, the claims recite an abstract idea.
Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea.
Accordingly, these additional elements do not amount to significantly more than the judicial exception. The claims 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.
Claims 1, 3, 7, 9, 13 and 15 are rejected under 35 U.S.C. 103 as being unpatentable over Hsiao (US 20220124183) in view of Esman (US 20210191909) and Togawa (or hereinafter “To”) (US 20220121191).
As to claim 1, Hsiao teaches a method implemented by one or more processors (paragraph 323), the method comprising:
“receiving a first analysis mode selected through a user interface” as in response to the selection of either user-interface element 1766 or user-interface element 1768, the GUI may further group event stream information shown in the table (figs. 17A-17B, paragraph 254) that indicates the user-interface element 1766 or 1768 as a first analysis mode received and selected via a user interface (figs. 17A-17B, paragraph 254).
In particularly: Selection of one user-interface element 1766-1768 may result in the automatic deselection of the other user-interface element. In response to the selection of either user-interface element 1766 or user-interface element 1768, the GUI may further group event stream information shown in the table by the event stream lifecycle represented by the selected user-interface element. For example, the GUI may show only permanent event streams that match the “HTTP” protocol classification in the table of FIG. 17A because user-interface element 1766 and “HTTP” are selected (paragraph 254);
“……first time-series data” as displaying on interface a first time series event data as first time series data e.g., first row in table using a first table that includes columns 1750, 1734-1750 is represented as a first time series analysis operator (fig. 17C, paragraphs 273-274, 281);
“analyzing, in response to the first analysis mode, the first time series data using a first time series analysis operator comprising……” as grouping as analyzing, in response to the user-interface element 1766 or 1768 as the first analysis model, first time series event data as first time series data e.g., first row using a first table as a first time series analysis operator comprising first column 1750 (figs. 17A-17C, paragraphs 254-255, 273-274, 281);
“updating the first time series analysis operator based on the first time series data and ……by:” as including or adding addition event streams e.g., HTTP-80, HTTP-20 in a first result table, which includes fields and rows for selection by a user, is represented as a first time series analysis operator based on first time series event data as the first time series data in the first row of first column 1750 and the first column 1750 by: (figs. 17C-17D, paragraphs 287-288):
For example, the user may select the user-interface element in the first row of column 1750 to view event stream information for 120 ephemeral event streams belonging to the group named “Group_A,” as discussed in further detail below with respect to FIG. 17D (paragraph 273).
FIG. 17D shows an exemplary screenshot in accordance with the disclosed embodiments. More specifically, FIG. 17D shows the GUI of FIG. 17C after the user-interface element in the first row of column 1750 has been selected. In response to the selected user-interface element, the table includes additional event stream information for ephemeral event streams in the group represented by the first row in the table. As shown in FIG. 17D, the additional event stream information includes an additional grouping of ephemeral event streams in the “Group_A” group by protocol (paragraph 287)
“determining ……based on the first time series data and……” as selecting as determining user-interface element e.g., Group_A in the first row of column 1750 as based on the first row that includes start time and end time as the first time series data and the column 1750 (paragraphs 273-274, fig. 17C).
For example, selection of the Group A value in column 1734 may cause the GUI to navigate to a screen showing events and the corresponding timestamps of the ephemeral event streams of Group A graphs of metrics related to the events, and/or other information associated with the events (paragraph 274);
“determining an updated first time series analysis operator based on……” as representing a table that includes addition event streams e.g., HTTP-80, HTTP-20, is represented as updated first time series analysis operator and the GUI (fig. 17D, paragraph 287).
FIG. 17D shows an exemplary screenshot in accordance with the disclosed embodiments. More specifically, FIG. 17D shows the GUI of FIG. 17C after the user-interface element in the first row of column 1750 has been selected. In response to the selected user-interface element, the table includes additional event stream information for ephemeral event streams in the group represented by the first row in the table. As shown in FIG. 17D, the additional event stream information includes an additional grouping of ephemeral event streams in the “Group_A” group by protocol (paragraph 287);
“……the updated first time series analysis operator” as a table that includes addition event streams e.g., HTTP-80, HTTP-20, is represented as updated first time series analysis operator and the GUI (fig. 17D, paragraph 287).
Hsiao does not explicitly teach limitation
a first model parameter; the first model parameter; the first model parameter;
a second model parameter; the second model parameter;
retrieve, from a time-series database,
retrieving, from the time-series database, second time-series data occurring after the first time-series data;
analyzing the second time series data using.
Esman teaches limitations
a first model parameter; the first model parameter; the first model parameter (as fields e.g., 702-704 of data model that includes a first field 702 of data model as a first model parameter: fig. 7A, paragraph 134);
a second model parameter; the second model parameter (second field 703 of data model is represented as a second model parameter: fig. 7A, paragraph 134);
“retrieve, from a time-series database……” as retrieve, from data store that stores timestamped events, timestamped events that includes a first timestamped event as first time-series data (paragraphs 66, 119-120, fig. 6A);
“retrieving, from the time-series database, second time-series data occurring after the first time-series data” as retrieve, from data store that stores timestamped events, timestamped events that includes second timestamped event having time 4/28/14: 6:22PM occurring after first timestamped event having time 4/28/14: 6:20PM (paragraphs 66, 119-120, fig. 6A).
Esman further teaches limitations
“retrieve, from a time-series database, first time-series data” as retrieve, from data store that stores timestamped events, timestamped events that includes a first timestamped event as first time-series data (paragraphs 66, 119-120, fig. 6A).
Hsiao and Esman disclose a method of analyzing time-series data and updating an operator based on analyzed time-series data. These references are same field with application’s field. Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply Esman’s teaching to Hsiao’s system in order to perform searches of different types of data, to improve time-based searching, to allow for events with recent timestamps, which may have a higher likelihood of being accessed, to be stored in a faster memory to facilitate faster retrieval, to produce a reduced set of search results, and further to speed up queries that are performed on a periodic basis.
To teaches limitation
“analyzing the second time series data using……” as analyzing the second time-series data using the updated reference data (paragraphs 99, 104) e.g., correlation model as the updated first time series analysis operator (paragraphs 48-49).
To further teaches limitation
“updating the first time series analysis operator based on the first time series data and ……by: determining ……based on the first time series data and……” as updating the reference data as the first time series analysis operator based on the first time series data and an analysis unit 121 (fig. 2) by setting as determining a section of the first time-series data based on the first time series data and analysis unit (paragraphs 48-49, 123).
In particularly:
[0123] the analysis unit analyzes the first time-series data with use of reference data set in advance, sets the section of the first time-series data on a basis of an analysis result, updates the reference data on a basis of the first time-series data included in the set section, and analyzes the second time-series data with use of the reference data updated; and
“determining an updated first time series analysis operator based on……” as generating as determining an updated reference data as the updated first time series analysis operator based on the section of the first time-series data (paragraph 123);
“analyzing the second time series data using the updated first time series analysis operator” as analyzing the second time-series data using the updated reference data (paragraphs 99, 104) e.g., correlation model as the updated first time series analysis operator (paragraphs 48-49).
Hsiao and To disclose a method of analyzing time-series data and updating an operator based on analyzed time-series data. These references are same field with application’s field. Thus, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply To’s teaching to Hsiao’s system in order to enable prevention of output of unnecessary abnormality detection with respect to time-series data, to enable improvements in monitoring accuracy with respect to a monitoring object by a user and further to represent the abnormal state of the second time-series data.
As to claims 3, 9, 15, Hsiao, Esman and To each limitation
“wherein when executed by the one or more processors, the instructions further cause the apparatus to store or storing the second model parameter” as instructions are executed by the one or more processors, the instructions cause computer system to (Hsiao: fig. 27, paragraph 323-324, col. Left, page 29) save a data model object (Esman: paragraph 131) that includes a second field 703 of data model is represented as a second model parameter: (Esman: fig. 7A, paragraph 134)
.Claim 7 has the same limitations as discussed in claim 1; thus claim 7 is rejected under the same reason as discussed in claim 1. In addition, Hsiao teaches an apparatus, comprising “a memory configured to store instructions; and one or more processors coupled to the memory, wherein when executed by the one or more processors, the instructions cause the apparatus to:” as a memory configured to store instructions; and a processor coupled to the memory, wherein when executed by the one or more processors, the instructions cause computer system to (fig. 27, paragraph 323-324, col. Left, page 29).
Claim 13 has the same limitations as discussed in claim 1; thus claim 13 is rejected under the same reason as discussed in claim 1. In addition, Hsiao teaches computer program product comprising computer-executable instructions that are stored on a non-transitory computer-readable storage medium and that, when executed by one or more processors, cause an apparatus to: (fig. 27, paragraph 323-324, col. Left, page 29).
Claims 2, 20 are rejected under 35 U.S.C. 103 as being unpatentable over Hsiao in view of Esman and To and further in view of MONTGOMERY et al (or hereinafter “Mo”) (US 20220215432)
As to claim 2, Hsiao, Esman and To teach limitations
“determining the first model parameter using……” as selecting a field 702 of data model as the first model parameter using user interface (Esman: fig. 7A, paragraph 134: Hsiao: paragraph 217).
Hsiao, Esman and To do not explicitly teach limitation
an exponential moving average algorithm
Mo teaches limitation
“an exponential moving average algorithm” as an exponential moving average algorithm (paragraph 35).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply Mo’s teaching to Hsiao’s system in order to adjust present value for a webpage or link that is displayed for one period of time correctly, to determine a cost for observation or viewing data on a webpage efficiently, and further to allow users may submit search queries to search engines for searching data from storage device.
As to claim 20, Hsiao, Esman and To teach limitation
“ wherein the computer-executable instructions, when executed by the one or more processors, further cause the apparatus to determine the first model parameter using……” as wherein the computer-executable instructions, when executed by the one or more processors, further cause the computer system to (Hsiao: fig. 27, paragraph 323-324, col. Left, page 29) selecting a field 702 of data model as the first model parameter using user interface (Esman: fig. 7A, paragraph 134: Hsiao: paragraph 217).
Hsiao, Esman and To do not explicitly teach limitation
an exponential moving average algorithm
Mo teaches limitation
“an exponential moving average algorithm” as an exponential moving average algorithm (paragraph 35).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply Mo’s teaching to Hsiao’s system in order to adjust present value for a webpage or link that is displayed for one period of time correctly, to determine a cost for observation or viewing data on a webpage efficiently, and further to allow users may submit search queries to search engines for searching data from storage device.
Claims 4-6, 10-12, 16-18 are rejected under 35 U.S.C. 103 as being unpatentable over Hsiao in view of Esman and To and further in view of Martin (US 20220092112)
As to claims 4, 10, 16, Hsiao, Esman and To teach limitation
“wherein when executed by the one or more processors, the instructions further cause the apparatus to” as instructions are executed by the one or more processors, the instructions cause computer system to (Hsiao: fig. 27, paragraph 323-324, col. Left, page 29),
“……the first time series analysis operator based on third time series data” as updating, based on time series data, the table (Hsiao: fig. 17C) that includes time series data is represented as a second time series analysis operator (Hsiao: fig. 17C, paragraphs 273, 286-287);
“wherein the third time series data is before the first time series data” as third event 6:20:55pm is before event 6:22:16pm as the first time series data (Esman: fig. 6A, paragraphs 66, 119-120).
Hsiao, Esman and To do not explicitly teach limitation
train or training.
Martin teaches limitations
“train or training the first time series analysis operator based on third time series data” as training a model based on time series data set (Martin: paragraphs 3, 82)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply Martin’s teaching to Hsiao’s system in order to allow a user, through the user interface, to quickly and easily select for display in one or more plots aligned time series sensor data, and further to allows faster analysis of time series data and model generation by allowing quick and accurate access to selected portions of time series sensor data.
As to claims 5, 11,17, Hsiao, Esman and To teach limitation
“ obtaining the third time series data from the time series database” as retrieving time stamped data events that includes a third time stamped data event as the third time series data from a time series data store as a time series database (Esmam: paragraphs 66, 119-120, fig. 6A; Hsiao: fig.4) or
“wherein when executed by the one or more processors, the instructions further cause the apparatus to obtain the third time series data from the time series database” as instructions are executed by the one or more processors, the instructions cause computer system to (Hsiao: fig. 27, paragraph 323-324, col. Left, page 29) retrieve time stamped data events that includes a third time stamped data event as the third time series data from a time series data store as a time series database (Esman: paragraphs 66, 119-120, fig. 6A; Hsiao: fig. 4).
As to claim 6, 12, 18, Hsiao, Esman and To teach limitations
“wherein when executed by the one or more processors, the instructions further cause the apparatus to:” as instructions are executed by the one or more processors, the instructions cause computer system to (Hsiao: fig. 27, paragraph 323-324, col. Left, page 29) and/or
“……a second time series analysis operator based on the first time series data” as updating, based on time series data, the table (Hsiao: fig. 17C) that includes time series data is represented as a second time series analysis operator (Hsiao: fig. 17C, paragraphs 273, 286-287);
“analyze or analyzing, in response to a second analysis mode input by the user, the first time series data using the second time series analysis operator” as navigating and showing or viewing as analyzing, in response to selection of the Group A value in column 1734 as a first analysis mode input by a user, first time series event data e.g., a row in table as first time series data using a second table that includes a different set of columns 1734-1750 is represented as a first time series analysis operator (Hsiao: fig. 17C, paragraphs 273-274, 281; Esman: fig. 6A).
Hsiao, Esman and To do not explicitly teach limitation
train or training.
Martin teaches limitation
“train or training a second time series analysis operator based on the first time series data” as training a model based on time series data set (Martin: paragraphs 3, 82)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply Martin’s teaching to Hsiao’s system in order to allow a user, through the user interface, to quickly and easily select for display in one or more plots aligned time series sensor data, and further to allows faster analysis of time series data and model generation by allowing quick and accurate access to selected portions of time series sensor data.
Claims 8, 14 are rejected under 35 U.S.C. 103 as being unpatentable over Hsiao in view of Esman and To and further in view of Stewart et al (US 20230297629)
As to claims 8, 14, Hsiao, Esman and To teach limitation
“wherein when executed by the one or more processors, the instructions further cause the apparatus to:” as instructions are executed by the one or more processors, the instructions cause computer system to (Hsiao: fig. 27, paragraph 323-324, col. Left, page 29):
“determine the first model parameter using……” as selecting a field 702 of data model as the first model parameter using user interface (Esman: fig. 7A, paragraph 134: Hsiao: paragraph 217).
Hsiao, Esman and To do not explicitly teach limitation
a stochastic gradient descent (SGD) algorithm
Stewart teaches limitation
“a stochastic gradient descent (SGD) algorithm” as a stochastic gradient descent (SGD) algorithm (paragraph 90).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply Stewart’s teaching to Hsiao’s system in order to provide a skill evaluation improvement recommendation to user and further to providing a best predicted output/actual output fit corresponding to user’s request.
Claim 19 is rejected under 35 U.S.C. 103 as being unpatentable over Hsiao in view of Esman and To and further in view of Xue et al (US 20220207434).
As to claim 19, Hsiao, Esman and To teach limitation
“ wherein the computer-executable instructions, when executed by the one or more processors, further cause the apparatus to determine the first model parameter using……” as wherein the computer-executable instructions, when executed by the one or more processors, further cause the computer system to (Hsiao: fig. 27, paragraph 323-324, col. Left, page 29) as selecting a field 702 of data model as the first model parameter using user interface (Esman: fig. 7A, paragraph 134: Hsiao: paragraph 217).
Hsiao, Esman and To do not explicitly teach limitation
a moving average algorithm.
Xue teaches limitation “a moving average algorithm” as Autoregressive integrated moving average model as a moving average algorithm (paragraph 103)
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply Xue’s teaching to Hsiao’s system in order to reduce complexity of network analysis systems, to save storage space, further to reduce an overall training cost of the first analysis device and to improve prediction efficiency.
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.
Contact Information
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CAM-Y T TRUONG whose telephone number is (571)272-4042. The examiner can normally be reached (571) 272 4042.
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/CAM Y T TRUONG/Primary Examiner, Art Unit 2169
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