DETAILED ACTION
Status of Claims
This is a final action in reply to the response filed on February 3, 2026.
Claims 1, 10 and 16 have been amended.
Claim 2 has been cancelled.
Claims 1, 3-7 and 9-20 are currently pending and have been examined.
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 .
Response to Amendments
Applicant’s amendment necessitated the new ground(s) of rejection presented in this Office action.
The rejection of claims 1-7 and 9-20 under 35 USC § 112(a) and 35 USC § 112(b) is withdrawn in light of Applicant’s argument and amendments.
The rejection of claims 1, 3-7 and 9-20 under 35 USC § 101 is maintained. Please see the Response to Arguments.
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, 3-7 and 9-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more. Per MPEP 2106.03 Eligibility Step 1: The Four Categories of Statutory Subject Matter [R-07.2022]. Step 1 is directed to determining whether or not the claims fall within a statutory class. Herein, claims 1, 3-7 and 9 falls within statutory class of a process, claims 10-15 falls within statutory class of an article of manufacturing and claims 16-20 falls within statutory class of a machine. Hence, the claims qualify as potentially eligible subject matter under 35 U.S.C §101. With Step 1 being directed to a statutory category, MPEP 2106.04 Eligibility Step 2A: Whether a Claim is Directed to a Judicial Exception [R-07.2022].. Step 2 is the two-part analysis from Alice Corp. (also called the Mayo test). The 2019 PEG makes two changes in Step 2A: It sets forth new procedure for Step 2A (called “revised Step 2A”) under which a claim is not “directed to” a judicial exception unless the claim satisfies a two-prong inquiry. The two-prong inquiry is as follows: Prong One: evaluate whether the claim recites a judicial exception. If claim recites an exception, then Prong Two: evaluate whether the claim recites additional elements that integrate the exception into a practical application of the exception. The claim(s) recite(s) the following abstract idea indicated by non-boldface font and additional limitations indicated by boldface font:
Claims 1, 10 and 16:
[one or more processors; and
one or more computer-readable memories coupled to the one or more processors and having instructions stored thereon that are executable by the one or more processors to perform operations comprising:]
obtaining, as an obtained time series, a time series comprising data observations, each data observation associated with a respective date, wherein the data observations are associated with executions of a process for resource scheduling for a cloud system;
determining model variables derived based on evaluating combinations of hierarchy levels of a time hierarchy of a planning calendar when processing the time series, wherein a combination of the combinations is defined as a set of periods or sub-periods of the time hierarchy, wherein the model variables map a time period of the time series associated with a set of data observations to a combination of hierarchy levels of time hierarchy of the planning calendar , wherein the time hierarchy comprising hierarchy levels defining periods of sub-periods, wherein each period of a given hierarchy level is defined to comprise a number of sub-periods of a lower hierarchy level, wherein the time hierarchy is defined based on a week-based pattern of the planning calendar, and wherein a period or a sub-period comprises a number of consecutive days of a year, the number being a multiple of the days of a week defined for the week-based pattern;
generating a predictive model for a predicted variable identified at the data observations based on the model variables, wherein the predictive model identifies recurring data patterns at the time series for the predicted variable within the periods of the time hierarchy; and
executing the predictive model to predict, as predicted values, values for the predicted variable over a time horizon requested for scheduling the process; and
using the predicted values to instruct executing the process for resource scheduling at the cloud system so that resources are provided to be consumed over the time horizon, wherein the cloud system is scheduled to provide the resources that match the predicted values for the predicted variable over the time horizon.
Per Prong One of Step 2A, the identified recitation of an abstract idea falls within at least one of the Abstract Idea Groupings consisting of: Mathematical Concepts, Mental Processes, or Certain Methods of Organizing Human Activity. Particularly, the identified recitation falls within Mental Processes, concepts performed in the human mind including observations, evaluation, judgement and opinion and Certain Methods of Organizing Human Activity such as commercial or legal interactions including advertising, marketing or sales activities or behaviors, business relations. Per Prong Two of Step 2A, this judicial exception is not integrated into a practical application because the claim as a whole does not integrate the identified abstract idea into a practical application. The one or more processors, computer-readable memories and cloud system is recited at a high level of generality, i.e., as a generic computing and processing system. This one or more processors and computer-readable memories is no more than mere instructions to apply the exception using a generic computing devices each comprising at least a processor and memory. Further, processor configured to cause receiving/determining/transmitting data is mere instruction to apply an exception using a generic computer component which cannot integrate a judicial exception into a practical application. Accordingly, this/these additional element(s) does/do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. Thus, since the claims are directed to the determined judicial exception in view of the two prongs of Step 2A, MPEP 2106.05 Eligibility Step 2B: Whether a Claim Amounts to Significantly More [R-07.2022] is directed to Step 2B. Therein, the additional elements and combinations therewith are examined in the claims to determine whether the claims as a whole amounts to significantly more than the judicial exception. It is noted here that the additional elements are to be considered both individually and as an ordered combination. In this case, the claims each at most comprise additional elements of one or more processors, computer-readable memories and cloud system. Taken individually, the additional limitations each are generically recited and thus does not add significantly more to the respective limitations. Further, executing all the steps/functions by a user/service subsystem is mere instruction to apply an exception using a generic computer component which cannot provide an inventive concept in Step 2B (or, looking back to Step 2A, cannot integrate a judicial exception into a practical application). For further support, the Applicant’s specification supports the claims being directed to use of a generic one or more processors, computer-readable memories and cloud system type structure at paragraphs 0089: “ The computer system 600 includes a processor 610, a memory 620, a storage device 630, and an input/output device 640.” See also figures 1and 6 and paragraph 0039: “The cloud environment 106 may include one or more server devices and databases (for example, processors, memory). In the depicted example, a user 114 interacts with the client device 102, and a user 116 interacts with the client device 104.”
Taken as an ordered combination, the claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the limitations are directed to limitations referenced in Alice Corp. that are not enough to qualify as significantly more when recited in a claim with an abstract idea include, as a non-limiting or non-exclusive examples: i. Adding the words "apply it" (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, e.g., a limitation indicating that a particular function such as creating and maintaining electronic records is performed by a computer, as discussed in Alice Corp., 134 S. Ct. at 2360, 110 USPQ2d at 1984 (see MPEP § 2106.05(f)); ii. Simply appending well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception, e.g., a claim to an abstract idea requiring no more than a generic computer to perform generic computer functions that are well-understood, routine and conventional activities previously known to the industry, as discussed in Alice Corp., 134 S. Ct. at 2359-60, 110 USPQ2d at 1984 (see MPEP § 2106.05(d)); iii. Adding insignificant extra-solution activity to the judicial exception, e.g., mere data gathering in conjunction with a law of nature or abstract idea such as a step of obtaining information about credit card transactions so that the information can be analyzed by an abstract mental process, as discussed in CyberSource v. Retail Decisions, Inc., 654 F.3d 1366, 1375, 99 USPQ2d 1690, 1694 (Fed. Cir. 2011) (see MPEP § 2106.05(g)); or v. Generally linking the use of the judicial exception to a particular technological environment or field of use, e.g., a claim describing how the abstract idea of hedging could be used in the commodities and energy markets, as discussed in Bilski v. Kappos, 561 U.S. 593, 595, 95 USPQ2d 1001, 1010 (2010) or a claim limiting the use of a mathematical formula to the petrochemical and oil-refining fields, as discussed in Parker v. Flook. The courts have recognized the following computer functions inter alia to be well-understood, routine, and conventional functions when they are claimed in a merely generic manner: performing repetitive calculations; receiving, processing, and storing data (e.g., the present claims); electronically scanning or extracting data; electronic recordkeeping; automating mental tasks (e.g., process/machine for performing the present claims); and receiving or transmitting data (e.g., the present claims). The dependent claims 3-7, 9-0, 11-15 and 17-20 do not cure the above stated deficiencies, and in particular, the dependent claims further narrow the abstract idea without reciting additional elements that integrate the exception into a practical application of the exception or providing significantly more than the abstract idea. Claims 11 and 17 further limit the abstract idea that the model variables are determined for each combination of hierarchy levels of the planning calendar, the hierarchy levels comprising a year, an aggregation period, a period, a sub-period, and a day (a more detailed abstract idea remains an abstract idea). Claims 3, 12 and 18 further limit the abstract idea that the planning calendar is a calendar defined to comprise a same number of days in a hierarchy level of the time hierarchy, and wherein each sub-period within a period of the time hierarchy is defined to start on a same weekday of the Gregorian calendar (a more detailed abstract idea remains an abstract idea). Claims 4, 13 and 19 further limit the abstract idea that a first period of sub- periods is a period of weeks within the time hierarchy of the planning calendar, wherein the first period comprises a different number of weeks compared to a second period of weeks as sub- periods and a third period of weeks as sub-periods, the second period of weeks and the third period of weeks being defined within the time hierarchy of the planning calendar (a more detailed abstract idea remains an abstract idea). Claims 5, 14 and 20 further limit the abstract idea that the planning calendar comprising a 4-4-5 week-based pattern as the pattern of the planning calendar, wherein the 4-4-5 week-based pattern defines a repetitive sequence of number of weeks for each consecutive period in the time hierarchy of the planning calendar (a more detailed abstract idea remains an abstract idea). Claims 6 and 15 further limit the abstract idea that each period of sub-periods comprises a same number of sub-periods as the week-based pattern of the planning calendar (a more detailed abstract idea remains an abstract idea). Claim 7 further limit the abstract idea that the obtained time series comprise data identifying a position of a respective date of a data observation within a hierarchy of a Gregorian calendar, wherein the Gregorian calendar is defined to comprise hierarchy levels comprising calendar year, calendar quarter, calendar month as a period comprising a respective number of days (a more detailed abstract idea remains an abstract idea). And claim 9 further limit the abstract idea that the predictive model is generated based on a plurality of predictor values comprising the model variables as variables for prediction and one or more additional variables as one or more respective predictors to support prediction of values for the predicted variable (a more detailed abstract idea remains an abstract idea). The identified recitation of the dependents claims falls within the Mental Processes, concepts performed in the human mind including observations, evaluation, judgement and opinion and Certain Methods of Organizing Human Activity such as commercial or legal interactions including advertising, marketing or sales activities or behaviors, business relations. Since there are no elements or ordered combination of elements that amount to significantly more than the judicial exception, the claims are not eligible subject matter under 35 USC §101. Thus, viewed as a whole, these additional claim element(s) do not provide meaningful limitation(s) to transform the abstract idea into a patent eligible application of the abstract idea such that the claim(s) amounts to significantly more than the abstract idea itself. Therefore, the claim(s) are rejected under 35 U.S.C. 101 as being directed to non-statutory subject matter.
Response to Arguments
Applicant's arguments filed on 2/3/2026 have been fully considered but they are not persuasive.
With regard to the 35 U,S.C. 101 rejection, Applicant argues that (1) “claims 1, 8 and 15 are not directed to an abstract idea under Step 2A, Prong 1 of the subject matter eligibility analysis,” and (2) “the claim limitations impose meaningful limits on any such abstract idea and integrate the abstract idea into a practical application” (Remarks, pages 9-13).
With regard to the 35 U.S.C. 103 rejection, Applicant argues specifically that the prior art (3) “that the cited references, whether alone or in combination, does not teach or suggest each and every element of amended claim 1. ” (Remarks, pages 13-16).
In response to Applicant’s argument (1). Examiner respectfully disagrees. claim 1 recites a computer-implemented method for generating a predictive model to predict values for the predicted variable over a time horizon in order to provide resources for scheduling for a cloud system to be consumed over the time horizon. Time series are obtained which comprises observations associated with a process for resource scheduling for a cloud system, model variables are determined based on evaluating combinations of hierarchy levels of a time hierarchy of a planning calendar as described in the Applicant's disclosure in paragraph 0028 "identifying data patterns within periods of a time hierarchy of a planning calendar, where the data patterns are identified based on data observations collected as time series. The identification of data patterns in data observations can be during the execution of predictive services based on forecasting models for predicting future expected data observations. The result from such predictive services can be used for automating process executions, planning and forecasting executions, performing system maintenance based on predicted resource demand and/or supply, adjustments to sensors and devices in physical spaces, or defining device work schedules, among other example of utilization” and paragraph 0029: “ time series analysis can be used in the context of various forecasting tasks and processes defined in organizations, for example, forecasting production units, sales, and estimating prices, among other example organizational processes. Further, forecasting can be used in the context of automating process execution based on accurate prediction of process execution results, scheduling of operations of devices, systems and environments, or other performance prediction executions.” Therefore, claim 1 recites an abstract idea falling within the Guidance's subject-matter grouping to the group of Mental Processes, concepts performed in the human mind including observations(time series), evaluation(model variables based on combinations of hierarchy levels of a time hierarchy of a planning calendar), judgement (predictive model) and opinion (resources to be consumed over the time horizon) and Certain Methods of Organizing Human Activity such as commercial or legal interactions including advertising, marketing or sales activities or behaviors, business relations such as scheduling resources for consumption over a time period. The same rationale applies to claims 10 and 16.
In response to Applicant’s argument (2). Examiner respectfully disagrees. Per Prong Two of Step 2A, this judicial exception is not integrated into a practical application because the claim as a whole does not integrate the identified abstract idea into a practical application. The one or more processors, computer-readable memories and cloud system is recited at a high level of generality, i.e., as a generic processor performing a generic computer function of receiving/determining/transmitting data. This generic processor limitation is no more than mere instructions to apply the exception using a generic computer component. Considering the claims as a whole, these additional limitations merely add generic computer activities i.e., receiving/determining/transmitting to receive inputs (time series: data observation) to determine (model variables, predictive model for resource scheduling) and to transmit (resource consumption over time based on the predictive model). The one or more processors, computer-readable memories and cloud system, merely links the abstract idea to a computer environment. The predictive model and the cloud system merely links the abstract idea to a computer environment. In this way, the one or more processors, computer-readable memories and cloud system involvement is merely a field of use which only contributes nominally and insignificantly to the recited method, which indicates absence of integration. Claim 1 uses the one or more processors, computer-readable memories, cloud system and the predictive model as a tool, in its ordinary capacity, to carry out the abstract idea. As to this level of computer involvement, mere automation of manual processes using generic computers does not necessarily indicate a patent-eligible improvement in computer technology. Considered as a whole, the claimed method does not improve the functioning of the computer itself or any other technology or technical field i.e., processing of time series data,. Further, a processor configured to cause receiving/determining/transmitting data to a device is mere instruction to apply an exception using a generic computer component which cannot integrate a judicial exception into a practical application. Accordingly, this/these additional element(s) does/do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The same rationale applies to claims 10 and 16. With regard that the claims are similar to Ex parte Desjardins, Examiner respectfully disagrees. Examiner has carefully reviewed the specifications and the claims and is unable to find some technical way that there is an improvement or technical solution to cloud system technical field. Accordingly, at this time, all we have is a “bare assertion” of an improvement – with no details on how the execution of the predictive model provides technical benefits over existing systems. Accordingly, at this time, this is viewed as MPEP 2106.04(d)(1) “Conversely, if the specification explicitly sets forth an improvement only in a conclusory manner (i.e., a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art), the examiner should not determine that the claim improves technology or a technical field.” The rejection is maintained.
In response to Applicant’s argument (3) with respect to the rejection(s) of claim(s) 1-7 and 9-20 under 35 U.S.C. 103 have been fully considered and are persuasive. Therefore, the rejection has been withdrawn. However, upon further consideration, a new ground(s) of rejection is made in view of new found prior art references of Achin in view of Tableau and Kaushik. Please see below as necessitated by amendments.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1, 3-7 and 9-20 are rejected under 35 U.S.C. 103 as being unpatentable over Achin et al., (US 10,496,927 B2) hereinafter “Achin” in both view of help.tableau.com https://web.archive.org/web/20210728103437/https://help.tableau.com/current/pro/desktop/en-us/dates_calendar.htm “hereinafter “Tableau” and Kaushik et al., (US 10,949,116 B2) hereinafter “Kaushik”.
Claim 1:
Achin as shown discloses a computer-implemented method, the method:
obtaining, as an obtained time series, a time series comprising data observations, each data observation associated with a respective date, (col. 3, lines 53-57: “(a) obtaining time-series data including one or more data sets, wherein each data set includes a plurality of observations, wherein each observation includes (1) an indication of a time associated with the observation (2) respective values of one or more variables;” and col. 25, lines 28-34: “Characteristics of a dataset may include, without limitation,[…] the data types of the data set's variables (e.g., numerical, ordinal, categorical, or interpreted (e.g., date, time, text, etc.)”);
wherein the data observations are associated with executions of a process [for resource scheduling for a cloud system] (col. 1, lines 40-49: Many organizations and individuals use electronic data to improve their operations or aid their decision-making. For example, many business enterprises use data management technologies to enhance the efficiency of various business processes, such as executing transactions, tracking inputs and outputs, or marketing products. As another example, many businesses use operational data to evaluate performance of business processes, to measure the effectiveness of efforts to improve processes, or to decide how to adjust processes.” As shown in col. 54, lines 36-40: “In many fields, organizations face uncertainty in the outcome of a production process and want to predict how a given set of conditions will affect the final properties of the output.”);
determining model variables derived based on evaluating combinations of hierarchy levels of a time hierarchy of a planning calendar when processing the time series, wherein a combination of the combinations is defined as a set of periods or sub-periods of the time hierarchy, (Figure 9, describe in reference character 930 “Identify one or more variables of the time-series data as targets, and identify zero or more other variables as features”, col. 2, lines 2-6, describe at least two variables “The variable(s) to be predicted may be referred to as “target(s)”, “response(s)”, or “dependent variable(s)”. The remaining variable(s), which can be used to make the predictions, may be referred to as “feature(s)”, “predictor(s)”, or “independent variable(s)” see also col. 6, lines 20-29: “the forecast range is determined based, at least in part, on (1) a time interval of the time-series data, (2) a number of observations included in the time-series data, (3) a time period corresponding to the time-series data, and/or (4) a natural time period selected from the group consisting of microseconds, milliseconds, seconds, minutes, hours, days, weeks, months, quarters, seasons, years, decades, centuries, and millennia. In some embodiments, the forecast range is an integer multiple of the time interval of the time-series data Col. 65 lines 55-59: “The time step is a time period (e.g., the smallest time period, the most typical time period, a user specified time period, etc.) between successive observations (e.g., daily, weekly, or annual data).” And col. 67 lines 8-18: “the engine 110 may suggest a forecast range based on the frequency of the data and/or the total number of periods in the data. For example, with daily data and a relatively small number of time periods, the engine 110 may suggest a 7-day forecast, while with a relatively large number of time periods, it may suggest a 30-day forecast. With monthly data, the engine 110 may suggest 3-, 6-, or 12-month forecasts depending on the number of time periods. With quarterly data, the engine 110 may suggest a 4-, 8-, or 12-quarter forecast. For annual data, the engine 110 may suggest a 5-, 10-, or 20-year forecast.”);
wherein the model variables map a time period of the time series associated with a set of data observations to a combination of hierarchy levels of time hierarchy of the planning calendar (col. 39, lines 41-54: “to assessing the importance of features contained in the original dataset, the evaluation performed at step 408 of method 400 includes feature generation. Feature generation techniques may include generating additional features by interpreting the logical type of the dataset's variable and applying various transformations to the variable. […] For interpreted variables (e.g., date, time, currency, measurement units, percentages, and location coordinates), examples of transformations include, without limitation, parsing a date string into a continuous time variable, day of week, month, and season to test each aspect of the date for predictive power.” See also col. 71, lines 1-3: “The “time” associated with an observation may include a date and/or time of day, or any other suitable temporal data.” And col. 65 lines 55-59: “The time step is a time period (e.g., the smallest time period, the most typical time period, a user specified time period, etc.) between successive observations (e.g., daily, weekly, or annual data).”);
Achin is silent with regard to the following limitations. However Tableau in an analogous art of date analysis for the purpose of providing the following limitations as shown does:
combination of hierarchy levels of a time hierarchy of a planning calendar, wherein a combination of the combinations is defined as a set of periods or sub-periods of the time hierarchy, a time hierarchy of a planning calendar, wherein the time hierarchy comprising hierarchy levels defining periods of sub-periods , wherein each period of a given hierarchy level is defined to comprise a number of sub-periods of a lower hierarchy level, wherein the time hierarchy is defined based on a week-based pattern of the planning calendar, and wherein a period or a sub-period comprises a number of consecutive days of a year, the number being a multiple of the days of a week defined for the week-based pattern (pages 1 and 3-4: “The ISO-8601 Week-Based Calendar is an international standard for date-related data. The purpose of the ISO-8601 calendar is to provide a consistent and clear method to represent and calculate dates. ISO-8601 calendars divide dates into Years, Quarters, Weeks, and Week Days. Unlike the Gregorian calendar, ISO-8601 calendars have a consistent number of weeks in each quarter and a consistent number of days each week, making the ISO-8601 calendar popular when calculating retail and financial dates.” The tables from pages 3-4 describes the hierarchy levels, the set of periods or sub-periods of the time hierarchy i.e., year, quarter, week. For a quarter “The first three quarters in theISO-8601 always have 13 weeks in them, with the last Quarter having either 13 or 14 weeks in it, depending upon the start of the next ISO-8601 year” and “Many retail and financial systems divide ISO-8601 Quarters into three segments of 4-4-5 weeks, though other segment systems also exist” and “All weeks in the ISO-8601Week-Based calendar have exactly 7 days, start on a Monday, and each week belongs to single year” );
Both Achin and Tableau teach date analysis. Achin teaches in col. 39, lines 52-54 “parsing a date string into a continuous time variable, day of week, month, and season to test each aspect of the date for predictive power.” Tableau teaches in page 1 “The ISO-8601 Week-Based Calendar is an international standard for date-related data.” Thus, they are deemed to be analogous references as they are reasonably pertinent to each other and are directed towards solving similar problems within the same environment. One of ordinary skill in the art would have recognized that applying the known technique of Tableau would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Tableau to the teaching of Achin would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such as a combination of hierarchy levels of a time hierarchy of a planning calendar, wherein a combination of the combinations is defined as a set of periods or sub-periods of the time hierarchy, time hierarchy of a planning calendar, wherein the time hierarchy comprising hierarchy levels defining es periods of sub-periods as a hierarchy level, wherein each period of a given hierarchy level is defined to comprise a number of sub-periods of a lower hierarchy level, wherein the time hierarchy is defined based on a week-based pattern of the planning calendar, and wherein a period or a sub-period comprises a number of consecutive days of a year, the number being a multiple of the days of a week defined for the week-based pattern into similar systems. Further, as noted by Tableau “The ISO-8601 Week-Based Calendar is an international standard for date-related data. […] Unlike the Gregorian calendar, ISO-8601 calendars have a consistent number of weeks in each quarter and a consistent number of days each week, making the ISO-8601 calendar popular when calculating retail and financial dates.” (Tableau, page 1).
In addition, Achin teaches:
generating a predictive model for a predicted variable identified at the data observations based on the model variables, (col. 74, lines 43-46: “selecting a predictive model for a prediction problem may be used to select a time-series predictive model for a time-series prediction problem.”);
Achin teaches a predictive model that solve a prediction problem as explained above. Achin in view of Tableau is silent with regard to the following limitations. However Kaushik in an analogous art of time series modeling for the purpose of providing the following limitations as shown does:
for resource scheduling for a cloud system (col. 11, lines 35-47: “The ensemble storage resource capacity prediction may be for a particular user, for a particular storage system, or combinations thereof. […] The ensemble storage resource capacity prediction may alternatively be for a particular storage system. This may be useful for the operator of IT infrastructure (e.g., a cloud service provider) to determine when storage resources of a particular storage system will run out and thus when capacity needs to be upgraded.” And col. 4, lines 17-21: “The capacity modeling module 122 is configured to generate a plurality of model-specific storage resource capacity predictions utilizing the historical storage resource utilization data and respective ones of a plurality of time series capacity prediction forecasting models”);
wherein the predictive model identifies recurring data patterns at the time series for the predicted variable within the periods of the time hierarchy; (col. 4, lines 17-32: “The capacity modeling module 122 is configured to generate a plurality of model-specific storage resource capacity predictions utilizing the historical storage resource utilization data and respective ones of a plurality of time series capacity prediction forecasting models. The plurality of time series capacity prediction forecasting models may include at least a first time series capacity prediction forecasting model that takes into account a first type of seasonality and trend factors and at least a second time series capacity prediction forecasting model that takes into account a second type of seasonality and trend factors. The first and second types may correspond to different “frequencies” of seasonality and trends. For example, the first type of seasonality and trend factors may correspond to weekly patterns, while the second type of seasonality and trend factors may correspond to daily patterns.”);
executing the predictive model to predict, as predicted values, values for the predicted variable over a time horizon requested for scheduling the process (col. 8, lines 57-58: “Various types of models may be used to provide storage resource capacity forecasts or predictions.” Col. 4, lines 44-48: “The capacity prediction module 124 is also configured to determine an overall storage resource capacity prediction based at least in part on a combination of the selected subset of the model-specific storage resource capacity predictions.” And col. 12, lines 21-25: “The ensemble storage resource capacity prediction may also or alternatively include a forecast of storage resource capacity utilization over a designated time period. The designated time period may be from a current time until the time at which capacity is expected to run out.”);
using the predictive values to instruct executing the process for resource scheduling at the cloud system so that resources are provided to be consumed over the time horizon, wherein the cloud system is scheduled to provide the resources that match the predicted values for the predicted variable over the time horizon (col. 13, lines 5-9: “FIG. 6 shows an example processing platform comprising cloud infrastructure 600. The cloud infrastructure 600 comprises a combination of physical and virtual processing resources that may be utilized to implement at least a portion of the information processing system 100.” And col. 4, lines 49-57: “The storage resource provisioning module 126 is configured to modify a provisioning of storage resources of the storage systems 106 based at least in part on the overall storage resource capacity prediction. Modifying storage resource provisioning may include adding storage resources to one or more of the storage systems 106 (e.g., increasing capacity by adding additional storage devices or capacity to the storage systems), adding or removing storage resources allocated to particular users of the storage systems 106, etc.”);
Both Achin and Kaushik teach time series modeling. Achin teaches in the Abstract “predictive modeling method may include determining a time interval of time-series data.” Veasey teaches in the Abstract “obtaining historical storage resource utilization data for a given set of storage resources of one or more storage systems, and generating a plurality of model-specific storage resource capacity predictions utilizing the historical storage resource utilization data and respective ones of a plurality of time series capacity prediction forecasting models.” Thus, they are deemed to be analogous references as they are reasonably pertinent to each other and are directed towards solving similar problems within the same environment. One of ordinary skill in the art would have recognized that applying the known technique of Kaushik would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Kaushik to the teaching of Achin in view of Tableau and would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such as for resource scheduling for a cloud system, wherein the predictive model identifies recurring data patterns at the time series for the predicted variable within the periods of the time hierarchy; executing the predictive model to predict, as predicted values, values for the predicted variable over a time horizon requested for scheduling the process and using the predictive values to instruct executing the process for resource scheduling at the cloud system so that resources are provided to be consumed over the time horizon, wherein the cloud system is scheduled to provide the resources that match the predicted values for the predicted variable over the time horizon into similar systems. Further, as noted by Kaushik “To ensure that available storage resources in the storage pools do not run out, it may be desired to provide storage capacity predictions to the users.” (Kaushik, col. 1, lines 17-20).
Claims 10 and 16:
The limitations of claims 10 (col. 92, lines 39-41) and 16 encompass substantially the same scope as claim 1. Accordingly, those similar limitations are rejected in substantially the same manner as claim 1, as described above. The following limitations differs from claim 1:
Claim 16:
Achin as shown discloses a system, the system:
one or more processors; and one or more computer-readable memories coupled to the one or more processors and having instructions stored thereon that are executable by the one or more processors to perform operations comprising: (claim 20, lines 21-22: “one processor configured to execute the machine-executable module”);
Claims 11 and 17:
Achin teaches in col. 39, lines 41-54: “to assessing the importance of features contained in the original dataset, the evaluation performed at step 408 of method 400 includes feature generation. Feature generation techniques may include generating additional features by interpreting the logical type of the dataset's variable and applying various transformations to the variable. […] For interpreted variables (e.g., date, time, currency, measurement units, percentages, and location coordinates), examples of transformations include, without limitation, parsing a date string into a continuous time variable, day of week, month, and season to test each aspect of the date for predictive power.” See also col. 71, lines 1-3: “The “time” associated with an observation may include a date and/or time of day, or any other suitable temporal data.” See also col. 72, lines 59-67 to col. 73 line 1: “The forecast range may indicate a duration of a time period for which values of the targets are to be predicted. The forecast range may be determined based on (1) the time interval of the time-series data, (2) the number of observations included in the time-series data, (3) the time period covered by the observations in the time-series data, (4) a natural time period selected from the group consisting of microseconds, milliseconds, seconds, minutes, hours, days, weeks, months, quarters, seasons, years, decades, centuries, and millennia, (5) user input, etc.” Achin is silent with regard to the following limitations. However Tableau in an analogous art of date analysis for the purpose of providing the following limitations as shown does:
wherein the model variables are determined for each combination of hierarchy levels of the planning calendar, the hierarchy levels comprising a year, an aggregation period, a period, a sub-period, and a day (pages 1 and 3-4: “ISO-8601 calendars divide dates into Years, Quarters, Weeks, and Week Days. Unlike the Gregorian calendar, ISO-8601 calendars have a consistent number of weeks in each quarter and a consistent number of days each week,” The tables from pages 3-4 describes the hierarchy levels. Such as for a quarter “The first three quarters in theISO-8601 always have 13 weeks in them, with the last Quarter having either 13 or 14 weeks in it, depending upon the start of the next ISO-8601 year” and “Many retail and financial systems divide ISO-8601 Quarters into three segments of 4-4-5 weeks, though other segment systems also exist” and “All weeks in the ISO-8601Week-Based calendar have exactly 7 days, start on a Monday, and each week belongs to single year”);
Both Achin and Tableau teach date analysis. Achin teaches in col. 39, lines 52-54 “parsing a date string into a continuous time variable, day of week, month, and season to test each aspect of the date for predictive power.” Tableau teaches in page 1 “The ISO-8601 Week-Based Calendar is an international standard for date-related data.” Thus, they are deemed to be analogous references as they are reasonably pertinent to each other and are directed towards solving similar problems within the same environment. One of ordinary skill in the art would have recognized that applying the known technique of Tableau would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Tableau to the teaching of Achin would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such as wherein the model variables are determined for each combination of hierarchy levels [of the planning calendar], the hierarchy levels comprising a year, an aggregation period, a period, a sub-period, and a day into similar systems. Further, as noted by Tableau “The ISO-8601 Week-Based Calendar is an international standard for date-related data. […] Unlike the Gregorian calendar, ISO-8601 calendars have a consistent number of weeks in each quarter and a consistent number of days each week, making the ISO-8601 calendar popular when calculating retail and financial dates.” (Tableau, page 1).
Claims 3, 12 and 18:
Achin is silent with regard to the following limitations. However Tableau in an analogous art of date analysis for the purpose of providing the following limitations as shown does:
wherein the planning calendar is a calendar defined to comprise a same number of days in a hierarchy level of the time hierarchy, and wherein each sub-period within a period of the time hierarchy is defined to start on a same weekday of a Gregorian calendar (pages 3-4, “All weeks in the ISO-8601 Week-Based calendar have exactly 7 days, start on a Monday, and each week belongs to single year.” See also “Many retail and financial systems divide ISO-8601Quarters into three segments of 4-4-5 weeks, though other segment systems also exist.”);
Both Achin and Tableau teach date analysis. Achin teaches in col. 39, lines 52-54 “parsing a date string into a continuous time variable, day of week, month, and season to test each aspect of the date for predictive power.” Tableau teaches in page 1 “The ISO-8601 Week-Based Calendar is an international standard for date-related data.” Thus, they are deemed to be analogous references as they are reasonably pertinent to each other and are directed towards solving similar problems within the same environment. One of ordinary skill in the art would have recognized that applying the known technique of Tableau would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Tableau to the teaching of Achin would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such as wherein the planning calendar is a calendar defined to comprise a same number of days in a hierarchy level of the time hierarchy, and wherein each sub-period within a period of the time hierarchy is defined to start on a same weekday of a Gregorian calendar into similar systems. Further, as noted by Tableau “The ISO-8601 Week-Based Calendar is an international standard for date-related data. […] Unlike the Gregorian calendar, ISO-8601 calendars have a consistent number of weeks in each quarter and a consistent number of days each week, making the ISO-8601 calendar popular when calculating retail and financial dates.” (Tableau, page 1).
Claims 4, 13 and 19:
Achin is silent with regard to the following limitations. However Tableau in an analogous art of date analysis for the purpose of providing the following limitations as shown does:
wherein a first period of sub-periods is a period of weeks within the time hierarchy of the planning calendar, wherein the first period comprises a different number of weeks compared to a second period of weeks as sub- periods and a third period of weeks as sub-periods, the second period of weeks and the third period of weeks being defined within the time hierarchy of the planning calendar (pages 3-4 “Many retail and financial systems divide ISO-8601Quarters into three segments of 4-4-5 weeks, though other segment systems also exist.”);
Both Achin and Tableau teach date analysis. Achin teaches in col. 39, lines 52-54 “parsing a date string into a continuous time variable, day of week, month, and season to test each aspect of the date for predictive power.” Tableau teaches in page 1 “The ISO-8601 Week-Based Calendar is an international standard for date-related data.” Thus, they are deemed to be analogous references as they are reasonably pertinent to each other and are directed towards solving similar problems within the same environment. One of ordinary skill in the art would have recognized that applying the known technique of Tableau would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Tableau to the teaching of Achin would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such as •wherein a first period of sub-periods is a period of weeks within the time hierarchy of the planning calendar, wherein the first period comprises a different number of weeks compared to a second period of weeks as sub- periods and a third period of weeks as sub-periods, the second period of weeks and the third period of weeks being defined within the time hierarchy of the planning calendar into similar systems. Further, as noted by Tableau “The ISO-8601 Week-Based Calendar is an international standard for date-related data. […] Unlike the Gregorian calendar, ISO-8601 calendars have a consistent number of weeks in each quarter and a consistent number of days each week, making the ISO-8601 calendar popular when calculating retail and financial dates.” (Tableau, page 1).
Claims 5, 14 and 20:
Achin is silent with regard to the following limitations. However Tableau in an analogous art of date analysis for the purpose of providing the following limitations as shown does:
wherein the planning calendar comprising a 4-4-5 week-based pattern as the pattern of the planning calendar, wherein the 4-4-5 week-based pattern defines a repetitive sequence of number of weeks for each consecutive period in the time hierarchy of the planning calendar (pages 3-4 “Many retail and financial systems divide ISO-8601Quarters into three segments of 4-4-5 weeks, though other segment systems also exist.”);
Both Achin and Tableau teach date analysis. Achin teaches in col. 39, lines 52-54 “parsing a date string into a continuous time variable, day of week, month, and season to test each aspect of the date for predictive power.” Tableau teaches in page 1 “The ISO-8601 Week-Based Calendar is an international standard for date-related data.” Thus, they are deemed to be analogous references as they are reasonably pertinent to each other and are directed towards solving similar problems within the same environment. One of ordinary skill in the art would have recognized that applying the known technique of Tableau would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Tableau to the teaching of Achin would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such as wherein the planning calendar comprising a 4-4-5 week-based pattern as the pattern of the planning calendar, wherein the 4-4-5 week-based pattern defines a repetitive sequence of number of weeks for each consecutive period in the time hierarchy of the planning calendar into similar systems. Further, as noted by Tableau “The ISO-8601 Week-Based Calendar is an international standard for date-related data. […] Unlike the Gregorian calendar, ISO-8601 calendars have a consistent number of weeks in each quarter and a consistent number of days each week, making the ISO-8601 calendar popular when calculating retail and financial dates.” (Tableau, page 1)
Claims 6 and 15:
Achin is silent with regard to the following limitations. However Tableau in an analogous art of date analysis for the purpose of providing the following limitations as shown does:
wherein each period of sub-periods comprises a same number of sub-periods as the week-based pattern of the planning calendar (pages 3-4 “Many retail and financial systems divide ISO-8601Quarters into three segments of 4-4-5 weeks, though other segment systems also exist.”);
Both Achin and Tableau teach date analysis. Achin teaches in col. 39, lines 52-54 “parsing a date string into a continuous time variable, day of week, month, and season to test each aspect of the date for predictive power.” Tableau teaches in page 1 “The ISO-8601 Week-Based Calendar is an international standard for date-related data.” Thus, they are deemed to be analogous references as they are reasonably pertinent to each other and are directed towards solving similar problems within the same environment. One of ordinary skill in the art would have recognized that applying the known technique of Tableau would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Tableau to the teaching of Achin would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such as wherein each period of sub-periods comprises a same number of sub-periods as the week-based pattern of the planning calendar into similar systems. Further, as noted by Tableau “The ISO-8601 Week-Based Calendar is an international standard for date-related data. […] Unlike the Gregorian calendar, ISO-8601 calendars have a consistent number of weeks in each quarter and a consistent number of days each week, making the ISO-8601 calendar popular when calculating retail and financial dates.” (Tableau, page 1).
Claim 7:
Achin as shown discloses the following limitations:
wherein the obtained time series comprise data identifying a position of a respective date of a data observation (col. 39, lines 41-54: “to assessing the importance of features contained in the original dataset, the evaluation performed at step 408 of method 400 includes feature generation. Feature generation techniques may include generating additional features by interpreting the logical type of the dataset's variable and applying various transformations to the variable. […] For interpreted variables (e.g., date, time, currency, measurement units, percentages, and location coordinates), examples of transformations include, without limitation, parsing a date string into a continuous time variable, day of week, month, and season to test each aspect of the date for predictive power.” See also col. 71, lines 1-3: “The “time” associated with an observation may include a date and/or time of day, or any other suitable temporal data.”)
Achin is silent with regard to the following limitations. However Tableau in an analogous art of date analysis for the purpose of providing the following limitations as shown does:
within a hierarchy of a Gregorian calendar, wherein the Gregorian calendar is defined to comprise hierarchy levels comprising calendar year, calendar quarter, calendar month as a period comprising a respective number of days (pages 3-4, describes the Gregorian calendar and the hierarchy levels);
Both Achin and Tableau teach date analysis. Achin teaches in col. 39, lines 52-54 “parsing a date string into a continuous time variable, day of week, month, and season to test each aspect of the date for predictive power.” Tableau teaches in page 1 “The ISO-8601 Week-Based Calendar is an international standard for date-related data.” Thus, they are deemed to be analogous references as they are reasonably pertinent to each other and are directed towards solving similar problems within the same environment. One of ordinary skill in the art would have recognized that applying the known technique of Tableau would have yielded predictable results and resulted in an improved system. It would have been recognized that applying the technique of Tableau to the teaching of Achin would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such as within a hierarchy of a Gregorian calendar, wherein the Gregorian calendar is defined to comprise hierarchy levels comprising calendar year, calendar quarter, calendar month as a period comprising a respective number of days into similar systems. Further, as noted by Tableau “The ISO-8601 Week-Based Calendar is an international standard for date-related data. […] Unlike the Gregorian calendar, ISO-8601 calendars have a consistent number of weeks in each quarter and a consistent number of days each week, making the ISO-8601 calendar popular when calculating retail and financial dates.” (Tableau, page 1).
Claim 9:
Achin as shown discloses the following limitations:
wherein the predictive model is generated based on a plurality of predictor values comprising the model variables as variables for prediction and one or more additional variables as one or more respective predictors to support prediction of values for the predicted variable (Figure 9, describe in reference character 930 “Identify one or more variables of the time-series data as targets, and identify zero or more other variables as features”, col. 2, lines 2-6, describe at least two variables “The variable(s) to be predicted may be referred to as “target(s)”, “response(s)”, or “dependent variable(s)”. The remaining variable(s), which can be used to make the predictions, may be referred to as “feature(s)”, “predictor(s)”, or “independent variable(s)”);
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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/NADJA N CHONG CRUZ/
Primary Examiner, Art Unit 3623