DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Drawings
The drawings as submitted by Applicant on 04/04/2024 have been accepted by the examiner.
Disposition of Claims
Claims 1-20 are pending in the instant application. Claims 1, 7, and 11 have been amended. Claims 3 and 13 have been cancelled. No claims have been added. Claims 1,2, 4-12, and 14-20 are rejected herein. The rejection of the aforementioned claims is hereby made final.
Response to Remarks
The examiner has considered Applicant’s arguments pertaining to the rejection of the pending claims under 35 USC 101 but does not find said arguments to be persuasive. The examiner submits that the pending claims recited at least a method and non-transitory computer readable medium for displaying task management for order fulfillment, which both fall into one of the four statutory categories. The claims must then qualify as patent eligible subject matter. i.e., the claim must not be directed to a judicial exception unless the claim as a whole includes additional limitations amounting to significantly more than the exception. The judicial exceptions (also called "judicially recognized exceptions" or simply "exceptions") are subject matter that the courts have found to be outside of, or exceptions to, the four statutory categories of invention, and are limited to abstract ideas, laws of nature and natural phenomena (including products of nature). Alice Corp. Pty. Ltd. v. CLS Bank Int'l, 573 U.S. 208, 216, 110 USPQ2d 1976, 1980 (2014) (citing Ass'n for Molecular Pathology v. Myriad Genetics, Inc., 569 U.S. 576, 589, 106 USPQ2d 1972, 1979 (2013). See MPEP § 2106.04 for detailed information on the judicial exceptions. Because abstract ideas, laws of nature, and natural phenomenon "are the basic tools of scientific and technological work", the Supreme Court has expressed concern that monopolizing these tools by granting patent rights may impede innovation rather than promote it. See Alice Corp., 573 U.S. at 216, 110 USPQ2d at 1980; Mayo Collaborative Servs. v. Prometheus Labs., Inc., 566 U.S. 66, 71, 101 USPQ2d 1961, 1965 (2012). However, the Court has also emphasized that an invention is not considered to be ineligible for patenting simply because it involves a judicial exception. Alice Corp., 573 U.S. at 217, 110 USPQ2d at 1980-81 (citing Diamond v. Diehr, 450 U.S. 175, 187, 209 USPQ 1, 8 (1981)). See also Thales Visionix Inc. v. United States, 850 F.3d. 1343, 1349, 121 USPQ2d 1898, 1902 (Fed. Cir. 2017) ("That a mathematical equation is required to complete the claimed method and system does not doom the claims to abstraction."). Accordingly, the Court has said that integration of an abstract idea, law of nature or natural phenomenon into a practical application may be eligible for patent protection. See, e.g., Alice, 573 U.S. at 217, 110 USPQ2d at 1981 (explaining that "in applying the §101 exception, we must distinguish between patents that claim the ‘buildin[g] block[s]’ of human ingenuity and those that integrate the building blocks into something more" (quoting Mayo, 566 U.S. at 89, 110 USPQ2d at 1971) and stating that Mayo "set forth a framework for distinguishing patents that claim laws of nature, natural phenomena, and abstract ideas from those that claim patent-eligible applications of those concepts"); Mayo, 566 U.S. at 80, 84, 101 USPQ2d at 1969, 1971. The Supreme Court in Mayo laid out a framework for determining whether an applicant is seeking to patent a judicial exception itself, or a patent-eligible application of the judicial exception. See Alice Corp., 573 U.S. at 217-18, 110 USPQ2d at 1981 (citing Mayo, 566 U.S. 66, 101 USPQ2d 1961). This framework, which is referred to as the Mayo test or the Alice/Mayo test, is discussed in further detail in subsection III, below. The first part of the Mayo test is to determine whether the claims are directed to an abstract idea, a law of nature or a natural phenomenon (i.e., a judicial exception). Id. If the claims are directed to a judicial exception, the second part of the Mayo test is to determine whether the claim recites additional elements that amount to significantly more than the judicial exception. Id. citing Mayo, 566 U.S. at 72-73, 101 USPQ2d at 1966). The Supreme Court has described the second part of the test as the "search for an 'inventive concept'". Alice Corp., 573 U.S. at 217-18, 110 USPQ2d at 1981 (citing Mayo, 566 U.S. at 72-73, 101 USPQ2d at 1966). The examiner does agree that the broadest reasonable interpretation of the claim must be established and considered in the determination of patent eligibility under 35 USC 101.
In considering the pending claims, the examiner submits the following: Claim 1 of the pending application (as well as the claims that depend therefrom) recite: A computer-implemented method comprising: receiving a request from a client device of a fulfillment agent; based on receipt of the request, applying a trained prediction model to each of a plurality of discretized time slots of a time period to predict a likelihood that the fulfillment agent receives, during the discretized time slot, a favorite order from a requesting user that has favorited the fulfillment agent, wherein the trained prediction model is trained by: retrieving a profile for the fulfillment agent comprising a list of one or more requesting users that have favorited the fulfillment agent, and training the trained prediction model based on order histories of the one or more requesting users that have favorited the fulfillment agent; generating an interface displaying the plurality of discretized time slots with a visual indication for each discretized time slot based on the predicted likelihood for the discretized time slot, wherein generating the interface comprises: applying a thresholding filter to the likelihood of each discretized time slot to determine a display color as the visual indication, and generating a heat map with the plurality of discretized time slots colored according to the determined display colors; and providing, in response to the request, the interface to the client device of the fulfillment agent.
The language of at least claim 1 is reproduced above, with the significant structural language and method steps emboldened. In considering the claims, the examiner has taken into consideration the state of the art at the time of filing consistent with Applicant’s specification, as originally filed. The examiner further submits that the language of the computer readable storage medium as recited in independent claim 11, recites language that is similar to that recited in the method of claim 1, so that the 101 analysis as applied to claim 1, similarly applies to claim 11, at least based on its resemblance to claim 1. Based on the broadest reasonable interpretation of claim 1, it is clear that the pending claim 1 and similarly recited independent claim 11 falls into the judicial exception category of certain methods of organizing human activity, which includes fundamental economic principles or practices including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions) (see MPEP § 2106.04(a)(2), subsection II). The aforementioned categorization is evidenced at least in the steps of: “generating an interface displaying the plurality of discretized time slots with a visual indication for each discretized time slot based on the predicted likelihood for the discretized time slot” (claim 1 of the pending application) which constitutes a providing an instruction, and therefore places the pending claim into the category of certain methods of organizing human activity. If the identified limitation(s) falls within at least one of the groupings of abstract ideas, it is reasonable to conclude that the claim recites an abstract idea in Step 2A Prong One. The claim then requires further analysis in Step 2A Prong Two, to determine whether any additional elements in the claim integrate the abstract idea into a practical application, see MPEP § 2106.04(d). The Supreme Court has identified a number of concepts falling within the "certain methods of organizing human activity" grouping as abstract ideas. In particular, in Alice, the Court concluded that the use of a third party to mediate settlement risk is a ‘‘fundamental economic practice’’ and thus an abstract idea. 573 U.S. at 219–20, 110 USPQ2d at 1982. In the aforementioned claims, the request and designation of tasks and order fulfillment is being implemented on a computer processor. An example that would be considered analogous to the pending claims would be manual processing of a pick order within a warehouse, Inventor Holdings, LLC v. Bed Bath Beyond, 876 F.3d 1372, 1378-79, 125 USPQ2d 1019, 1023 (Fed. Cir. 2017).
The Supreme Court has long distinguished between principles themselves (which are not patent eligible) and the integration of those principles into practical applications (which are patent eligible). See, e.g., Mayo Collaborative Servs. v. Prometheus Labs., Inc., 566 U.S. 66, 80, 84, 101 USPQ2d 1961, 1968-69, 1970 (2012). The Federal Circuit has distinguished between claims that are ‘‘directed to’’ a judicial exception (which require further analysis to determine their eligibility) and those that are not (which are therefore patent eligible), e.g., claims that improve the functioning of a computer or other technology or technological field. See Diamond v. Diehr, 450 U.S. 175, 209 USPQ 1 (1981); Gottschalk v. Benson, 409 U.S. 63, 175 USPQ 673 (1972), MPEP 2106.06(b) (summarizing Enfish, LLC v. Microsoft Corp., 822 F.3d 1327, 118 USPQ2d 1684 (Fed. Cir. 2016), McRO, Inc. v. Bandai Namco Games Am. Inc., 837 F.3d 1299, 120 USPQ2d 1091 (Fed. Cir. 2016), and other cases that were eligible as improvements to technology or computer functionality instead of being directed to abstract ideas). Accordingly, after determining that a claim recites a judicial exception in Step 2A Prong One, examiners should evaluate whether the claim as a whole integrates the recited judicial exception into a practical application of the exception in Step 2A Prong Two. A claim that integrates a judicial exception into a practical application will apply, rely on, or use the judicial exception in a manner that imposes a meaningful limit on the judicial exception, such that the claim is more than a drafting effort designed to monopolize the judicial exception.
The Supreme Court and Federal Circuit have identified a number of considerations as relevant to the evaluation of whether the claimed additional elements demonstrate that a claim is directed to patent-eligible subject matter. The list of considerations here is not intended to be exclusive or limiting. Additional elements can often be analyzed based on more than one type of consideration and the type of consideration is of no import to the eligibility analysis. Additional discussion of these considerations, and how they were applied in particular judicial decisions, is provided in MPEP § 2106.05(a) through (c) and MPEP § 2106.05(e) through (h).
Limitations the courts have found indicative that an additional element (or combination of elements) may have integrated the exception into a practical application include:
• An improvement in the functioning of a computer, or an improvement to other technology or technical field, as discussed in MPEP §§ 2106.04(d)(1) and 2106.05(a);
• Applying or using a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition, as discussed in MPEP § 2106.04(d)(2);
• Implementing a judicial exception with, or using a judicial exception in conjunction with, a particular machine or manufacture that is integral to the claim, as discussed in MPEP § 2106.05(b);
• Effecting a transformation or reduction of a particular article to a different state or thing, as discussed in MPEP § 2106.05(c); and
• Applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception, as discussed in MPEP § 2106.05(e).
The courts have also identified limitations that did not integrate a judicial exception into a practical application:
• Merely reciting the words "apply it" (or an equivalent) with the judicial exception, or merely including instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP § 2106.05(f);
• Adding insignificant extra-solution activity to the judicial exception, as discussed in MPEP § 2106.05(g); and
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• Generally linking the use of a judicial exception to a particular technological environment or field of use, as discussed in MPEP § 2106.05(h).
Examiners evaluate integration into a practical application by: (1) identifying whether there are any additional elements recited in the claim beyond the judicial exception(s); and (2) evaluating those additional elements individually and in combination to determine whether they integrate the exception into a practical application, using one or more of the considerations introduced in subsection I supra, and discussed in more detail in MPEP §§ 2106.04(d)(1), 2106.04(d)(2), 2106.05(a) through (c) and 2106.05(e) through (h).
In determining if the language of the pending claims integrate the judicial exception into a practical application, the examiner identifies the method steps and the system components of exemplary claim 1, which are provided in bold below:
Claim 1. : A computer-implemented method comprising: receiving a request from a client device of a fulfillment agent; based on receipt of the request, applying a trained prediction model to each of a plurality of discretized time slots of a time period to predict a likelihood that the fulfillment agent receives, during the discretized time slot, a favorite order from a requesting user that has favorited the fulfillment agent, wherein the trained prediction model is trained by: retrieving a profile for the fulfillment agent comprising a list of one or more requesting users that have favorited the fulfillment agent, and training the trained prediction model based on order histories of the one or more requesting users that have favorited the fulfillment agent; generating an interface displaying the plurality of discretized time slots with a visual indication for each discretized time slot based on the predicted likelihood for the discretized time slot, wherein generating the interface comprises: applying a thresholding filter to the likelihood of each discretized time slot to determine a display color as the visual indication, and generating a heat map with the plurality of discretized time slots colored according to the determined display colors; and providing, in response to the request, the interface to the client device of the fulfillment agent.
A claim reciting a judicial exception is not directed to the judicial exception if it also recites additional elements demonstrating that the claim as a whole integrates the exception into a practical application. One way to demonstrate such integration is when the claimed invention improves the functioning of a computer or improves another technology or technical field. The application or use of the judicial exception in this manner meaningfully limits the claim by going beyond generally linking the use of the judicial exception to a particular technological environment and thus transforms a claim into patent-eligible subject matter. Such claims are eligible at Step 2A because they are not "directed to" the recited judicial exception.
The courts have not provided an explicit test for this consideration but have instead illustrated how it is evaluated in numerous decisions. These decisions, and a detailed explanation of how examiners should evaluate this consideration are provided in MPEP § 2106.05(a). In short, first the specification should be evaluated to determine if the disclosure provides sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. The specification need not explicitly set forth the improvement, but it must describe the invention such that the improvement would be apparent to one of ordinary skill in the art. Conversely, if the specification explicitly sets forth an improvement but 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 the claim improves technology. Second, if the specification sets forth an improvement in technology, the claim must be evaluated to ensure that the claim itself reflects the disclosed improvement. That is, the claim includes the components or steps of the invention that provide the improvement described in the specification. The claim itself does not need to explicitly recite the improvement described in the specification (e.g., "thereby increasing the bandwidth of the channel").
One of ordinary skill in the art would recognize that Applicant’s specification fails to identify or explicitly disclose any improvement in the function of a computer or any other technology or technological field, as evidenced by the aforementioned citations from Applicant’s specification. Applicant’s specification merely combines generic, well understood computing elements in the performance of the well understood, routine, and conventional steps. Claims 2,4-10, 12, and 14-20 fail to cure the deficiencies under 35 USC 101 of the claims from which they depend and are similarly rejected for the same reasoning as applied to independent claim 1, and similarly recited claim 11.
For the aforementioned reasoning, the claims are found to be ineligible, and the rejection of the pending claims in view of 35 USC 101 is hereby maintained and made final.
Applicant’s arguments pertaining to the rejection of the pending claims under 35 USC 103 in view of the applied prior art of record is found to be moot in view of the new grounds of rejection presented below.
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, 2, 4-12, and 14-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed towards an abstract idea without significantly more or transforms the abstract idea into a practical application.
The independent claim 1 is directed towards scheduling pickers in accordance with shopper preferences, under broadest reasonable interpretation, are directed towards an abstract idea through the system merely gathering data (shopper preference data), generally analyzing the data (applying prediction model), and displaying results based on the analysis (providing a response to the request to the interface of the client device of the fulfillment agent). All the elements are directed towards the abstract idea of “certain method of organizing human activity” where the system is merely determining scheduling availability for a service provider (fulfillment agent) based on customer preferences. The analysis techniques are merely generic analysis techniques that are applying a general purpose business method to a computer. That general business method being the Scheduling of a worker based on predetermined and historical preferences. The independent claims are merely providing this business practice using generic analysis techniques (comparing, matching, and other various criterion) that are performed in determining a work schedule.
Step 2(a)(II) analysis considers the additional elements of the independent claim as to whether or not they are directed towards a practical application. The additional elements of “client device”, and an “interface”. The additional elements are described in Figs 1A, and at least paragraph [0064] in the originally filed specification. Based on the paragraphs and figures, there is no indication that the additional elements are integrating the abstract idea into a practical application. These technological elements are merely applying the abstract idea using the computer/system as a tool for the abstract idea (MPEP 2106.05(f)). Originally filed specification further discusses the processor in terms of standard components of a processor which further emphasizes that the additional elements are merely generic elements.
Step 2(b) analysis considers the additional elements in regard to being significantly more than the abstract idea identified. The additional elements of “client device” and a “interface”. The additional elements are described in Figs 1A, and at least paragraph [0064] in the originally filed specification. Based on the paragraphs and figures, as well as the analysis above, the additional elements are not significantly more than the abstract idea as they recite general links to a field of use and merely using the additional elements as a tool to implement the abstract idea (MPEP 2106.05(f) and 2106.05(h)).
The examiner further submits that the machine learning technique is described in the originally filed specification [0064], however, the description does not provide any specific examples or algorithms that show the machine learning technique is more than generically linking the additional element to a field of use (trained prediction model). The examiner submits that the machine learning is a generic recitation of an analysis and determination technique that provides no indication of what specific technique is being used within the system. Machine learning is merely an umbrella term that includes specific and non-specific (generic) techniques, and because broadest reasonable interpretation includes these generic techniques, then the determination using machine learning is a generic analysis technique.
Merely having the determination based on training the model does not preclude the technique to be indicative of applying the additional element in some meaningful way.
Machine learning includes generic and specific techniques, and without further discussion provided in the originally filed specification, then the broadest reasonable interpretation like that of exemplary independent claim 1 is merely generic analysis techniques that are not indicative of a practical application or significantly more than the abstract idea identified.
Similarly recited independent claim 11, as well as dependent claims 2,4-10, and 12, and 14-20 are directed towards an abstract idea without significantly more or transforming into a practical application. Therefore, claims 1, 2, 4-12, and 14-20 are rejected under 35 U.S.C. 101 for being directed towards non-statutory subject matter.
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 (i.e., changing from AIA to pre-AIA ) 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, 2, 4-12, and 14-20 are rejected under 35 U.S.C. 103 as being unpatentable over Krishnan et al (US 2024/0144191) in view of Kassam (US 2022/0101240), further i/n view of Cantrell et al (US 2018/0225620).
Regarding claim 1, the prior art discloses a computer-implemented method comprising:
receiving a request from a client device of a fulfillment agent (see at least paragraph [0069] to Krishnan et al, wherein there is a request for the picker to build their own schedule);
based on receipt of the request, applying a trained prediction model to each of a plurality of discretized time slots of a time period to predict a likelihood that the fulfillment agent receives, during the discretized time slot (see at least paragraph [0057] to Krishnan et al, wherein the earnings module 250 may then apply the order availability model to predict the likelihood for each time slot-location pair included in a set of time slot-location pairs described by availability information for a picker), and training the trained prediction model based on order histories of the one or more requesting users that have favorited the fulfillment agent (see at least paragraph [0053] to Krishnan et al, wherein the machine learning training module 230 may train the order availability model via supervised learning based on order data describing orders previously placed with the online concierge system 140 stored in the data store 240); generating an interface displaying the plurality of discretized time slots with a visual indication for each discretized time slot based on the predicted likelihood for the discretized time slot; and providing, in response to the request, the interface to the client device of the fulfillment agent (see at least paragraph [0080] to Krishnan et al, wherein the suggested schedule 440 may be sent 350 to the picker client device 110 in association with a map generated by the online concierge system 140… the map generated by the online concierge system 140 may correspond to a heat map, in which the amounts of earnings for different locations 420 depicted in the heat map are represented visually (e.g., with different colors, shades, etc.).
Krishnan et al does not appear to explicitly disclose a favorite order from a requesting user that has favorited the fulfillment agent, wherein the trained prediction model is trained by: retrieving a profile for the fulfillment agent comprising a list of one or more requesting users that have favorited the fulfillment agent.
However, Kassam discloses a shopping system and method with improved matching, further comprising a favorite order from a requesting user that has favorited the fulfillment agent, wherein the trained prediction model is trained by: retrieving a profile for the fulfillment agent comprising a list of one or more requesting users that have favorited the fulfillment agent (see at least paragraphs [0063] and [0068] to Kassam, wherein a customer may select a preferred picker and the picker has an associated profile).
The previously applied prior art of record does not appear to explicitly disclose wherein generating the interface comprises: applying a thresholding filter to the likelihood of each discretized time slot to determine a display color as the visual indication, and generating a heat map with the plurality of discretized time slots colored according to the determined display colors.
However, Cantrell et al discloses a task management in retail environment system and method, wherein generating the interface comprises: applying a thresholding filter to the likelihood of each discretized time slot to determine a display color as the visual indication, and generating a heat map with the plurality of discretized time slots colored according to the determined display colors (see at least paragraph [0022] to Cantrell et al, wherein a management tool, comprises a heat map generator that displays a heat map that provides a graphical representation of data where values cross-references employee tasks and values, which are represented as colors of a display of the mobile device; a graphical user interface for displaying the graphical representation at an electronic display; and an input for receiving data regarding an event that requires a task of the tasks to be performed, and used to determine the values, and indicating where tasks need to be performed based on sensors at store items, shelves, or other locations in the store).
The examiner recognizes that obviousness may be established by combining or modifying the teachings of the prior art to produce the claimed invention where there is some teaching, suggestion, or motivation to do so found either in the references themselves or in the knowledge generally available to one of ordinary skill in the art. See In re Fine, 837 F.2d 1071, 5 USPQ2d 1596 (Fed. Cir. 1988), In re Jones, 958 F.2d 347, 21 USPQ2d 1941 (Fed. Cir. 1992), and KSR International Co. v. Teleflex, Inc., 550 U.S. 398, 82 USPQ2d 1385 (2007). The examiner submits that the combination of the teaching of the system and method for generating a schedule for a picker of an online concierge system based on an earnings goal and availability information, as disclosed by Krishnan et al and the shopping system and method with improved matching, as taught by Kassam, further in view of the task management system and method as taught by Cantrell et al, in order to increase the probability of increasing customer satisfaction and delivery order fulfillment outcomes (see at least paragraph [0038] to Kassam) could have been readily and easily implemented, with a reasonable expectation of success. As such, the aforementioned combination is found to be obvious to try, given the state of the art at the time of filing.
Regarding claim 2, the prior art discloses the method of claim 1, wherein generating the interface displaying the plurality of discretized time slots comprises displaying the likelihood for each discretized time slot (see at least paragraph [0053] to Krishnan et al, wherein the earnings module 250 accesses an order availability model that is trained to predict a likelihood that an order placed with the online concierge system 140 will be available for a picker to service for a time slot).
Regarding claim 4, the prior art discloses the method of claim 1, wherein generating the interface displaying the plurality of discretized time slots comprises: identifying one or more of the discretized time slots as optimal time slots having highest likelihoods; and visually distinguishing the optimal time slots in the scheduling interface (see at least paragraph [0038] to Krishnan et al, wherein The content presentation module 210 also may present a scheduling interface for generating a suggested schedule for a picker based on information received from a picker client device 110 associated with the picker).
Regarding claim 5, the prior art discloses the method of claim 1, wherein generating the interface displaying the plurality of discretized time slots comprises: generating an option for each discretized time slot that, when selected, provides an indication that the fulfillment agent is available during that discretized time slot (see at least paragraph [0076] to Kassam et al, wherein if the consumer wishes to select a picker (step 709) then the application displays a GUI (such as GUI 400 and optionally one or more of window 500 and window 600) of available pickers (step 710) to allow selection of a picker. Upon receiving selection of a picker (step 712) the application 114 then associates the selected picker with the cart (step 716)).
Regarding claim 6, the prior art discloses the method of claim 1, wherein the trained prediction model is further trained by: retrieving user preference data for the fulfillment agent based on historical orders fulfilled for one or more requesting users during discretized time slots in prior periods, wherein at least one of the requesting users has favorited the fulfillment agent; and training the prediction model with the user preference data to predict the likelihood that the fulfillment agent is favorited by a requesting user upon completion of an order request during a discretized time slot (see at least paragraph [0053] to Krishnan et al, wherein the machine learning training module 230 may receive a set of training examples including attributes of time slot-location pairs associated with orders previously placed with the online concierge system 140. In this example, the machine learning training module 230 also may receive a label for each time slot-location pair indicating whether an order placed with the online concierge system 140 was available for a picker to service for the corresponding time slot-location pair).
Regarding claim 7, the prior art discloses the method of claim 1, wherein the trained prediction model is further trained by: retrieving other historical orders fulfilled by other fulfillment agents in one or more retailer locations where the fulfillment agent has also fulfilled historical orders, wherein the other historical order indicate which other historical order was favorited by the corresponding requesting user; and training the prediction model with the other historical orders (see at least paragraph [0052] to Krishnan et al, wherein the machine learning training module 230 trains a machine learning model based on a set of training examples. Each training example includes input data to which the machine learning model is applied to generate an output. For example, each training example may include customer data, picker data, item data, or order data. In some cases, the training examples also include a label which represents an expected output of the machine learning model. In these cases, the machine learning model is trained by comparing its output from input data of a training example to the label for the training example).
Regarding claim 8, the prior art discloses the method of claim 1, further comprising:
receiving requesting user feedback on one or more new orders during a first discretized time slot in the time period fulfilled by the fulfillment agent, wherein at least one new order is favorited by the corresponding requesting user; and retraining the trained prediction model with the one or more new orders and the likelihood of the first discretized time slot predicted by the trained prediction
model (see at least paragraph [0032] to Krishnan et al, wherein Order data may further include information describing how the order was serviced, such as which picker serviced the order, when the order was delivered, or a rating that the customer gave the delivery of the order).
Regarding claim 9, the prior art discloses the method of claim 1, wherein the request from the client device requests to set an availability schedule for the time period (see at least Figure 4A to Krishnan et al).
Regarding claim 10, the prior art discloses the method of claim 9, further comprising:
receiving, via the interface, an availability selection from the client device of the fulfillment agent indicating that the fulfillment agent is available for one or more of the discretized time slots; and
updating an availability schedule for the time period to reflect the availability of the fulfillment agent during the one or more discretized time slots (see at least paragraph [0076] to Kassam, wherein if the consumer wishes to select a picker (step 709) then the application displays a GUI (such as GUI 400 and optionally one or more of window 500 and window 600) of available pickers (step 710) to allow selection of a picker. Upon receiving selection of a picker (step 712) the application 114 then associates the selected picker with the cart (step 716)).
Claims 11, 12, and 14-20 each contain recitations substantially similar to those addressed above and, therefore, are likewise rejected.
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.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
The examiner has considered all references listed on the Notice of References Cited, PTO-892.
The examiner has considered all references cited on the Information Disclosure Statement submitted by Applicant, PTO-1449.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to TALIA F CRAWLEY whose telephone number is (571)270-5397. The examiner can normally be reached on Monday thru Thursday; 8:30 AM-4:30 PM EST.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Fahd A Obeid can be reached on 571-270-3324. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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Signature: ______________________________________
Certificate of Transmission by Facsimile
I hereby certify that this correspondence is being facsimile transmitted to the United States Patent and Trademark Office, Fax No. (___)_____ -_________ on _____________. (Date)
Typed or printed name of person signing this certificate:
_________________________________________
Signature: ________________________________________
Certificate of Transmission via USPTO Patent Electronic Filing System
I hereby certify that this correspondence is being transmitted via the U.S. Patent and Trademark Office (USPTO) patent electronic filing system to the USPTO
on _____________.
(Date)
Typed or printed name of person signing this certificate:
_________________________________________
Signature: ________________________________________
Please refer to 37 CFR 1.6(a)(4), 1.6(d) and 1.8(a)(2) for filing limitations concerning transmissions via the USPTO patent electronic filing system, facsimile transmissions and mailing, respectively.
/TALIA F CRAWLEY/ Primary Examiner, Art Unit 3627
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