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
Status of Claims
Request for Continued Examination under 37 CFR 1.1141
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on June 25, 2026 has been entered.
This action is a Non-Final action on the merits in response to the application filed on 06/25/2026.
Claims 1, 7, 9 and 15 have been amended. Claims 2, 6, 10 and 14 have been cancelled. Claims 1, 3-5, 7-9, 12-13 and 15 are currently pending and have been examined in this application.
Note, a new Examiner has been assigned to this application.
Response to Amendment
Applicant’s amendment has been considered
Response to Arguments
Applicant’s arguments have been considered.
Applicant argues, “ Viewed as a whole, amended claim 1 is not directed to organizing human activity in the abstract. “ (pg. 9)
Examiner respectfully disagrees. The claims encompass Certain Methods of Organizing Human Activity related to managing personal behavior, relationships or interactions. For example, receiving an allocation request for unallocated shifts; determining a label for requests; generating and training a classification model; detecting an unallocated shift record, generating an index for unallocated shift record; generating an impact indicator for the unallocated shift record and executing a selected control action involve scheduling shifts (managing people). Accordingly, the claim recites an abstract idea of Methods of Organizing Human Activity.
In addition, the claim could be seen as Mental Processes related to observation and evaluation of data.
Applicant argues, “ …the claims nevertheless integrate the idea into a practical application that reflects a specific technical improvement to computer-based scheduling systems.” (pgs. 9-10)
The judicial exceptions are not integrated into a practical application. Ther claims recite the additional elements of a computing device, a memory and a processor. These are generic computer components recited at a high level of generality as performing generic computer functions (Spec see ¶0026).
For instance, the steps of receiving allocation requests for unallocated shifts and detecting an unallocated shift record is data gathering activity. The steps of determining a label based on a number of allocation requests; generating and training a classification model; detecting an unallocated shift record; executing the trained classification model to generate a index; generating an impact indicator for the unallocated shift record and selecting a control action involve analyzing data and complex mathematics. The steps of controlling a display to present an unallocated shift record associated with the visual indicator and generating impact indicator includes retrieving a reference time period associated with the facility and determining an overlap involve display functionality and analyzing data.
Each of the additional limitations is no more than mere instructions to apply the exception using a generic computer components (e.g. a processor and memory). The combination of these additional elements is no more than mere instructions to apply the exception using a generic computer component (e.g. a processor and memory). The additional elements do not integrate the abstract ideas into a practical application because it does not impose meaningful limits on practicing the abstract idea. Therefore, the claims are directed to an abstract idea.
Applicant argue, “ …specific technical improvement to computer-based scheduling systems.” (pgs. 9-10)
Examiner respectfully disagrees. The problem cited, “…existing systems are unable to assess the impact of an open shift in a structured manner, and any such assessment is reliant on "subjective (and therefore error-prone and poorly scalable) judgements" of an administrator,” is a business process that is addressed by the instant claims. As such, the claims appear to be an improved business process. Further, there is no support in the claims or the Specification of an improvement in a technology (a computer) or a technical field.
Applicant argues, “ Like in Enfish, the present claims are directed to a specific technical solution-namely, the use of a machine-learned classification model trained on labels derived from historical allocation requests to forecast shift interest, combined with structured impact assessment incorporating temporal overlap analysis that improves the operation of a scheduling computing device itself.” (pgs. 10-11)
In Enfish the claims at issue focused on a specific improvement to a computer including a particular database technique in how computers could carry out the basic functions of storage and retrieval of data. In considering the claim, the court found that “the self-referential table recited in the claims is a specific type of data structure designed to improve the way a computer stores and retrieves data in memory.” As
such, the claims were found to be not an abstract idea.
Unlike Enfish, the instant claims are directed to generic computer components performing generic functionality including receiving allocation requests; determining a label; generating and training a classification model; detecting an unallocated shift record; executing a trained classification model to generate an index; generating an impact indicator etc.., which involves collecting and analyzing data. These limitations are reflective of abstract concepts. There is no support in the claims or the Specification of an improvement in the computing device, as the computing device is performing as it normally would.
Applicant argues, “ the additional elements of claim 1 (when considered both individually and as an ordered combination) amount to significantly more than the alleged abstract idea itself.” (pgs. 11)
Examiner respectfully disagrees. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As stated above, the additional elements of a processor, a memory, and a processing device. are considered generic computer components performing generic computer functions that amount to no more than instructions to implement the judicial exception. Mere, instructions to apply an exception using generic computer components cannot provide an inventive concept.
Applicant argues, “ The combination is therefore not merely the application of an abstract idea using generic computer components, but rather a particular technical implementation that produces meaningful improvements in the technical field of automated scheduling.” (pg. 12)
Automated scheduling is not considered a technical field. The claims appear to be an improved business process for automated scheduling and does not provide support in the claims or the Specification of an improvement in a technology (a computer) or a technical field.
The remainder of Applicant’s arguments are moot in view of new grounds of rejection as necessitated by amendment.
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, 3-5, 7-9, 12-13 and 15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Claim 1 recites:
receiving, at a computing device, allocation requests for a plurality of previous unallocated shifts;
determining, for each previous unallocated shift, a label based on a number of the allocation requests that correspond to the previous unallocated shift;
generating and training a classification model based on (i) the labels and (ii) the previous unallocated shifts;
detecting, at the computing device, an unallocated shift record corresponding to a facility, the unallocated shift record defining a time period and a task identifier;
executing, at the computing device, the trained classification model to generate an index corresponding to the unallocated shift record, the index being a value among a range of values indicative of a forecasted interest in the unallocated shift record;
generating, at the computing device, an impact indicator for the unallocated shift record based on the time period, the task identifier, and the index;
selecting a control action for the unallocated shift record according to the impact indicator; and executing the selected control action by controlling a display of the computing device to present the unallocated shift record in association with a selected visual indicator, wherein generating the impact indicator includes retrieving a reference time period associated with the facility, determining an overlap between the time period of the unallocated shift record and the reference time period, and generating a component of the impact indicator based on the determined overlap.
The limitation under its broadest reasonable interpretation covers Certain Methods of Organizing Human Activities related to managing personal behavior, relationships or interactions, but for the recitation of generic computer components (e.g. a processor and memory). For example, receiving an allocation request for unallocated shifts; determining a label for requests; generating and training a classification model; detecting an unallocated shift record, generating an index for unallocated shift record; generating an impact indicator for the unallocated shift record and executing a selected control action involve scheduling activities. Accordingly, the claim recites an abstract idea of Methods of Organizing Human Activity.
In addition, the claim could be seen as Mental Processes related to observation and evaluation of data.
Independent Claim 9 substantially recite the subject matter of Claim 1 and also include the abstract ideas identified above. The dependent claims encompass the same abstract ideas. For instance, Claim 3 is directed to generating a random forest classification model (analyzing using complex math); Claim 4 is directed retrieving task priority/task identifier and generating a component of impact indicator; Claim 5 is directed to unallocated shift record includes a portion of the time period corresponding to the task identifier (analysis); Claim 7 is directed to visual indicators and comparing thresholds (analyzing); Claim 8 is directed to determining and incentives (analysis). Claims 11-13, 15 and 16 substantially recites the subject matter of Claims 3-5, 7 and 8 and encompass same abstract ideas.
The judicial exceptions are not integrated into a practical application. Claim 1 recites the additional elements of a computing device. Claim 9 recites the additional elements of a memory, a processor and a computing device. These are generic computer components recited at a high level of generality as performing generic computer functions (Spec see ¶0026).
For instance, the steps of receiving allocation requests for unallocated shifts and detecting an unallocated shift record is data gathering activity. The steps of determining a label based on a number of allocation requests; generating and training a classification model; detecting an a unallocated shift record; executing the trained classification model to generate a index; generating an impact indicator for the unallocated shift record and selecting a control action involve analyzing data and complex mathematics. The steps of controlling a display to present an unallocated shift record associated with the visual indicator and generating impact indicator includes retrieving a reference time period associated with the facility and determining an overlap involve display functionality and analyzing data.
Each of the additional limitations is no more than mere instructions to apply the exception using a generic computer components (e.g. a processor and memory). The combination of these additional elements is no more than mere instructions to apply the exception using a generic computer component (e.g. a processor and memory). Therefore, the additional elements do not integrate the abstract ideas into a practical application because it does not impose meaningful limits on practicing the abstract idea. Therefore, the claims are directed to an abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As stated above, the additional elements of a processor, a memory, a crm, etc. are considered generic computer components performing generic computer functions that amount to no more than instructions to implement the judicial exception. Mere, instructions to apply an exception using generic computer components cannot provide an inventive concept.
The dependent claims when analyzed both individually and in combination are also held to be ineligible for the same reason above and the additional recited limitations fail to establish that the claims are not directed to an abstract. The additional limitations of the dependent claims when considered individually and as an ordered combination do not amount to significantly more than the abstract idea.
Looking at these limitations as an ordered combination and individually adds nothing additional that is sufficient to amount to significantly more than the recited abstract idea because they simply provide instructions to use generic computer components, to "apply" the recited abstract idea. Thus, the elements of the claims, considered both individually and as an ordered combination, are not sufficient to ensure that the claim as a whole amounts to significantly more than the abstract idea itself. Therefore, Claims 1, 3-5, 7-9, 12-13 and 15 are not patent eligible.
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.
The factual inquiries set forth in Graham v. John Deere Co., 383 U.S. 1, 148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103(a)(pre AIA )/103 (AIA ) are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1 and 9 are rejected under 35 U.S.C. 103 as being unpatentable over Guiffre et al. (IS 2022/0180266) further in view of Avats (US 2016/0275439).
Claim 1:
Guiffre discloses
A method, comprising: receiving, at a computing device, allocation requests for a plurality of previous unallocated shifts; (see at least ¶0062, detected number of requests for a shift; see also ¶0083, request and accept shifts)
determining, for each previous unallocated shift, a label based on a number of the allocation requests that correspond to the previous unallocated shift; (see at least ¶0062, detected number of requests for a shift, indication may be received based on data received from a demand forecasting model that indicates that there is a high demand (e.g., a demand exceeding a threshold) for shifts of certain types and/or at certain times within a next predefined period of time (e.g., within the next week, month, etc.). The demand forecasting model may be a machine learning model that may receive, as inputs, one or more of shift histories, shift owner attributes, past call-outs, shifter history, shift demand, shift likelihood of being filled, or the like. The forecasting model may output an indication to generate the shift at 206.; see also ¶0145, training data may include inputs and labels)
generating and training a classification model based on (i) the labels and (ii) the previous unallocated shifts; (see at least ¶0151, shift attractiveness machine learning model may be a classifier model)
detecting, at the computing device, an unallocated shift record corresponding to a facility, the unallocated shift record defining a time period and a task identifier; (see at least ¶0051, open shifts corresponding to a given period; see also ¶0070, shift data includes day, time, length, etc.)
executing, at the computing device, the trained classification model to generate an index corresponding to the unallocated shift record, the index being a value among a range of values indicative of a forecasted interest in the unallocated shift record; (see at least ¶0149-¶0150, a demand forecasting machine learning model may be trained and deployed to predict demand for upcoming shift, as discussed above with reference to Fig. 2B)
generating, at the computing device, an impact indicator for the unallocated shift record based on the time period, the task identifier, and the index; (see at least ¶0151-¶0152, a shift attractiveness machine learning model may be trained and deployed to predict a probability (index) of an upcoming shift being accepted)
selecting a control action for the unallocated shift record according to the impact indicator; and (see at least ¶0151-¶0152, predicting the probability that the upcoming shift will be accepted is used to further determine automatic adjustments to shift data or provision as suggestions to increase the probability prior to publishing of upcoming shift; see also Figure 5B and associated text; see also ¶0110, provide recommendations and suggestions to make shift more attractive)
executing the selected control action by controlling a display of the computing device to present the unallocated shift record in association with a selected visual indicator,… (see at least ¶0151-¶0152, predicting the probability that the upcoming shift will be accepted is used to further determine automatic adjustments to shift data or provision as suggestions to increase the probability prior to publishing of upcoming shift; see also Figure 5B and associated text; see also ¶0110)
While Guiffre discloses the above limitations, Guiffre does not explicitly disclose the following limitation; however, Avats does disclose:
wherein generating the impact indicator includes retrieving a reference time period associated with the facility, determining an overlap between the time period of the unallocated shift record and the reference time period, and generating a component of the impact indicator based on the determined overlap. (see at least ¶0009, to ensure proper staffing the system notifies employer of times that the employer must staff extra employees in order to properly manage peak times; see also ¶0066; see also ¶0014-¶0015)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, to combine the attribute-based generating and allocating of shift openings of Guiffre with the determining and notifying an employer of need to staff peak times of Avats to ensure the employer provides sufficient staffing for the time period (see ¶0009).
Claim 9 for a computing device substantially recites the subject matter of Claim 1 and is rejected based on the same rationale.
Claims 3 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Guiffre et al. (IS 2022/0180266) further in view of Avats (US 2016/0275439) further in view of Adeli-Nadjafi (US 2023/0103208).
Claim 3:
Guiffre and Avats disclose claim 1, and Guiffer further discloses a deep learning classifier model (see ¶0151) and providing labels (¶0062), neither explicitly disclose the following limitation; however, Adeli-Nadjafi does disclose:
wherein generating the classification model includes: generating a random forest classification model configured to output a label for an unallocated shift record. (see at least ¶0034, random forest classifier outputting labels)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, to combine the attribute-based generating and allocating of shift openings including a classifier model of Guiffre with the random forest classifier of Adeli-Nadjafi since each individual element and its function are shown in the prior art, albeit shown in separate references, the difference between the claimed subject matter and the prior art rests not on any individual element or function but in the very combination itself- that is in the substitution of random forest classifier model of the secondary reference for the deep learning model of Guiffre of the primary reference.
Thus, the simple substitution of one known element for another producing a predictable result renders the claim obvious.
Claim 11 for a computing device is substantially similar to Claim 3 and is rejected based on the same rationale.
Claims 4, 5, 12 and 13 are rejected under 35 U.S.C. 103 as being unpatentable over Guiffre et al. (IS 2022/0180266) further in view of Avats (US 2016/0275439) further in view of Che et al. (11610670).
Claim 4:
While Guiffre and Avats disclose claim 1, neither explicitly disclose the following limitations; however, Chen does disclose:
wherein generating the impact indicator includes: retrieving a task priority corresponding to the task identifier; and (see at least column 27, lines 64-67, prioritizing tasks and visual indicator of priority)
generating a component of the impact indicator based on the task priority. (see at least column 27, lines 64-67, prioritizing tasks and visual indicator of priority; see also column 32, lines 25-32, priority)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, to combine the attribute-based generating and allocating of shift openings of Guiffre with the determining and notifying an employer of need to staff peak times of Avats with the prioritization of tasks with indicators of Chen to assist workers in identifying prioritized tasks.
Claim 5:
While Guiffre, Avats and Chen disclose claim 4, neither explicitly disclose the following limitations; however, Chen does disclose:
wherein the unallocated shift record includes a portion of the time period corresponding to the task identifier; and (see at least column 19, lines 19-30, two hour increments and activities to be performed)
wherein generating the component of the impact indicator is further based on the portion of the time period. (see at least column 19, lines 19-30, two hour increments and activities to be performed; see also column 46, lines 22-32, alerts)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, to combine the attribute-based generating and allocating of shift openings of Guiffre with the determining and notifying an employer of need to staff peak times of Avats with the prioritization of tasks with indicators of Chen to assist workers in identifying prioritized tasks.
Claims 12 and 13 for a computing device substantially recites the subject matter of Claims 4 and 5 and are rejected based on the same rationale.
Claims 7, 8, 15 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Guiffre et al. (IS 2022/0180266) further in view of Avats (US 2016/0275439) further in view of Aslam (US 2022/0198353).
Claim 7:
While Guiffre and Avats disclose claim 1, neither explicitly disclose the following limitation; however, Aslam does disclose:
wherein selecting the control action includes:(i) maintaining, at the computing device, a plurality of visual indicators associated with respective thresholds; (see at least ¶0010, comparing reception level for a particular shift to a first threshold level; see also ¶0156)
(ii) selecting one of the visual indicators by comparing the impact indicator to the thresholds (see at least ¶0010, visual indicators)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, to combine the attribute-based generating and allocating of shift openings of Guiffre with the determining and notifying an employer of need to staff peak times of Avats with the threshold for comparing shifts bids of Aslam since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Claim 8:
While Guiffre and Avats disclose claim 1, neither explicitly disclose the following limitation; however, Aslam does disclose:
wherein selecting the control action includes: determining, at the computing device, an incentive value based on the impact indicator; and transmitting the unallocated shift record and the incentive value to a plurality of client devices. (see at least ¶0007-¶0008, displaying randomized incentive offers for each identified problem shift; see also ¶0227)
Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, to combine the attribute-based generating and allocating of shift openings of Guiffre with the determining and notifying an employer of need to staff peak times of Avats with the incentives of Aslam since the claimed invention is merely a combination of old elements, and in the combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable.
Claims 15 and 16 for a computing device substantially recites the subject matter of Claims 7 and 8 and are rejected based on the same rationale.
Conclusion
The prior art made of record and not relied upon is considered relevant but not applied:
Borza (US 2013/0090968) discloses an employee scheduling software system is taught that accesses multiple extrinsic databases hosting schedules relating to an employee allowing scheduling to avoid external conflicts for the employer and allowing employees to respond to schedules as well as trade/auction with other employee with confidence.
Yang (US 2023/0229993) discloses a system comprises a processor to determine whether labor demand has changed; in response to labor demand having been changed, generate an updated set of shift candidates; determine a new cost function and restart a solver using the updated set of shift candidates.
Any inquiry of a general nature or relating to the status of this application or concerning this communication or earlier communications from the Examiner should be directed to Renae Feacher whose telephone number is 571-270-5485. The Examiner can normally be reached Monday-Friday, 9:00 am - 5:00 pm. If attempts to reach the examiner by telephone are unsuccessful, the Examiner's supervisor, Beth Boswell can be reached at 571-272-6737.
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/Renae Feacher/
Primary Examiner, Art Unit 3625
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