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and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114.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 April 20, 2026 has been entered.
This action is a Non-Final action on the merits in response to communications filed on 04/20/2026.
Claims 1, 8, 11 and 15 have been amended. Claims 1 – 20 are currently pending and have been examined in this application.
Response to Amendment
Applicant’s amendment has been considered.
Applicant’s amendment is sufficient to overcome the 35 U.S.C. 112(b) rejection set forth in the prior office action.
Response to Arguments
Applicant’s remarks have been considered.
Applicant argues, “The amendments toward segmenting a geographic area and normalizing the data gathered for the particular market segments provide technical improvements to order filling and accurate forecasting of resources, as these activities
are not human activities, and the claims therefore no longer cover Organizing Human Activity as noted in the Office Action.” (pg. 14)
Examiner respectively disagrees. The limitations directed to segmenting a geographic area and normalizing the data gathered for the particular market segments are related to the abstract concepts related to Certain Methods of Organizing Human Activity related to managing personal behaviors and relationships. The steps are still considered abstract and directed to facilitating managing personal behaviors even though they are performed using a generic computer. Additionally the steps do not provide for a technical improvement as there is no support in the claims or Specification for an improvement in a technology or a technical field.
Here, the limitation under its broadest reasonable interpretation covers Certain Methods of Organizing Human Activities related to managing personal behavior or relationships or interactions between people, but for the recitation of generic computer components (e.g. a processor). For example, receiving an indication of picker interest in being assigned a task, tracking a location of the user, identifying a market boundary, predicting task availability and a predicted gap in a geographic area of a picker to determine task availability is related to managing personal behavior. Accordingly, the claim recites an abstract idea of Certain Methods of Organizing Human Activity.
The judicial exception is not integrated into a practical application. Claims 1 and 8 recite the additional elements of a computer system comprising a processor, a computer-readable medium, a client device and a picker interface. Claim 15 recites the additional elements of a non-transitory computer readable storage medium storing instructions executed by a computer processor, a client device and a picker interface. These are generic computer components recited at a high level of generality as performing generic computer functions (see ¶0012).
For instance, the step of receiving a picker interest in being assigned a task involves data input and tracking a location of the user to update current location is data gathering functionality. The step of identifying a market boundary including market segments grouped into market data structures (analysis), normalizing the time and location values of the market data structures (analysis, generating a prediction of task availability includes steps such as a level of task availability, extracting an aggregate feature set comprising a first feature setoff level of picker availability, accessing logged data, computing aggregate gap measures, grouping the aggregate gap measures, identifying the geographic region of the picker, predicting a gap for the geographic region, a second feature set, inputting an aggregate feature set into a deep learning model (complex mathematics), receiving an estimate of time until availability of a first task to the picker from a retailer location involve collecting and analyzing data (data gathering activities). These steps are reflective of collecting and analyzing data. The step of causing the client device of the picker to display the prediction of task availability involves generic display functionality. The step of outputting for display to a picker a picker interface comprising the estimate of time until availability is outputting a result of analyzing data and the step of selecting an interactive element that renders the picker eligible is merely selecting an element on the screen which is generic display functionality.
Each of the additional limitations is no more than mere instructions to apply the exception using a generic computer components (e.g. a processor). 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). 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.
Claim Rejections - 35 USC § 101
The following is a quotation of the first paragraph of 35 U.S.C. 112(a):
(a) IN GENERAL.—The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor or joint inventor of carrying out the invention.
The following is a quotation of the first paragraph of pre-AIA 35 U.S.C. 112:
The specification shall contain a written description of the invention, and of the manner and process of making and using it, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which it pertains, or with which it is most nearly connected, to make and use the same, and shall set forth the best mode contemplated by the inventor of carrying out his invention.
Claims 1-20 rejected under 35 U.S.C. 112(a) or 35 U.S.C. 112 (pre-AIA ), first paragraph, as failing to comply with the written description requirement. The claim(s) contains subject matter which was not described in the specification in such a way as to reasonably convey to one skilled in the relevant art that the inventor or a joint inventor, or for applications subject to pre-AIA 35 U.S.C. 112, the inventor(s), at the time the application was filed, had possession of the claimed invention.
Claim 1 recites, “… market segments are grouped based on time and location values of market data structures,” at line 10. The Specification does not explicitly disclose ‘market data structures’. The Specification discloses ‘tuples’ (Spec ¶0059) which are a type of data structure but is not interpreted as the same.
Claims 8 and 15 are rejected based on the same rationale as Claim 1. Claims 2-7, 9-14 and 16-20 are rejected based on their dependency on Claims 1, 8 and 15 respectively.
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. Claim 1 recites:
receiving, from a client device of a picker, an indication of picker interest in being assigned a task, and a current location of the picker;
tracking a location of the user to update the current location;
identifying a market boundary according to the current location, wherein the market boundary corresponds to a geographic region around the current location, wherein the market boundary comprises market segments, wherein the market segments are grouped based on time and location values of market data structures;
normalizing the time and location values of the market data structures from the market segments to generate aggregate gap measures for the market boundary, wherein the aggregate gap measures represent an aggregate difference between numbers of customer requests for performance of a picker task and numbers of users requesting to be assigned a picker task to perform;
generating, based at least in part on the current location of the picker, a prediction of task availability; and causing the client device of the picker to display, in a picker interface thereof, a representation of the prediction of task availability;
wherein the prediction of task availability comprises: extracting an aggregate feature set comprising: a first feature set of a level of picker task availability relative to historical levels in a geographic region encompassing the current location of the picker, the level of task availability generated by:
accessing logged data comprising geographic location, time, and the aggregate gap measures computed from work sessions of pickers;
grouping the aggregate gap measures according to geographic location;
for each of the groups, performing percentile analysis of the aggregate gap measures to identify boundary values defining a set of ranges;
identifying the geographic region encompassing the current location of the picker;
predicting a gap for the geographic region at a predetermined future time; and
a second feature set comprising historical picker activities of the picker;
inputting the aggregate feature set into a deep learning model;
wherein the aggregate feature set comprises the first feature set and the second feature set;
receiving, as output from the deep learning model;
an estimate of time until availability of a first task to the picker from a retailer location within a given radius of the current location of the picker, and
The limitation under its broadest reasonable interpretation covers Certain Methods of Organizing Human Activities related to managing personal behavior or relationships or interactions between people, but for the recitation of generic computer components (e.g. a processor). For example, receiving an indication of picker interest in being assigned a task, tracking a location of the user, identifying a market boundary, predicting task availability and a predicted gap in a geographic area of a picker to determine task availability is related to managing personal behavior. Accordingly, the claim recites an abstract idea of Certain Methods of Organizing Human Activity.
Additionally, the limitations encompass Mathematical Concepts related to mathematical calculations based on using a deep learning model to predicting an estimating time of availability.
Independent Claims 8 and 15 substantially recite the subject matter of Claim 1 and also include the abstract idea identified above. The dependent claims encompass the same abstract idea. For instance, Claim 2 is directed to prediction of task availability comprises estimate of time until availability of a first task to a picker; Claim 3 is directed to predicted wait time until assignment; Claim 4 is directed to identifying features of a current work session; Claim 5 is directed to accessing logged values for features associated with geographic zone; Claim 6 is directed to features associated with a retail location and Claim 7 is directed to features associated with a picker. Claims 9-14 and 16-20 substantially recite the subject of Claims 2-7 and encompass the same abstract idea. Thus, the dependent claims further limit the abstract concepts found in the independent claims.
The judicial exception is not integrated into a practical application. Claims 1 and 8 recite the additional elements of a computer system comprising a processor, a computer-readable medium, a client device and a picker interface. Claim 15 recites the additional elements of a non-transitory computer readable storage medium storing instructions executed by a computer processor, a client device and a picker interface. These are generic computer components recited at a high level of generality as performing generic computer functions (see ¶0012).
For instance, the step of receiving a picker interest in being assigned a task involves data input and tracking a location of the user to update current location is data gathering functionality. The step of identifying a market boundary including market segments grouped into market data structures (analysis), normalizing the time and location values of the market data structures (analysis, generating a prediction of task availability includes steps such as a level of task availability, extracting an aggregate feature set comprising a first feature setoff level of picker availability, accessing logged data, computing aggregate gap measures, grouping the aggregate gap measures, identifying the geographic region of the picker, predicting a gap for the geographic region, a second feature set, inputting an aggregate feature set into a deep learning model (complex mathematics), receiving an estimate of time until availability of a first task to the picker from a retailer location involve collecting and analyzing data (data gathering activities). These steps are reflective of collecting and analyzing data. The step of causing the client device of the picker to display the prediction of task availability involves generic display functionality. The step of outputting for display to a picker a picker interface comprising the estimate of time until availability is outputting a result of analyzing data and the step of selecting an interactive element that renders the picker eligible is merely selecting an element on the screen which is generic display functionality.
Each of the additional limitations is no more than mere instructions to apply the exception using a generic computer components (e.g. a processor). 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). 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 picker device, 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 1-20 are not patent eligible.
Conclusion
The prior art made of record and not relied upon is considered relevant but not applied:
Verheijen (US 2020/0410867) discloses assigning trips to vehicles within a fleet of vehicles that traverse a navigable network in a geographic area, and, in particular, to methods and systems for generating information for a dispatcher to facilitate the assignment of a trip to a vehicle.
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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