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 .
Status of Claims
This action is in reply to the communications filed on May 26, 2026. The Applicants’ Amendment and Request for Reconsideration has been received and entered.
Claims 1-20 are currently pending and have been examined. Claims 1-2, 9-10, and 17-18 have been amended.
The previous rejection of claims 1-20 under 35 USC 101 has been withdrawn.
Response to Arguments
Applicants’ amendments necessitated any new grounds of rejection.
The previous rejection of claims 1-20 under 35 USC 101 has been withdrawn in view of Applicants’ amendments. The Examiner notes that claims 1, 9, and 17 recite an abstract idea that is a method of organizing a human activity. However, the Examiner further notes that the abstract idea is integrated into a practical application. For example, claim 1 recites “predicting, by the at least one processor, at least one resource required to complete the scope of work, the predicting comprising processing the user data with a machine learning (ML) process; determining, by the at least one processor, at least one provisioning property of the at least one resource; applying, by the at least one processor, the at least one provisioning property to the standard product offering during the user session, thereby creating a customized product offering commensurate with the scope of work; receiving, by the at least one processor, a user request through the UI of the customized product offering during the user session; and performing, by the at least one processor, processing responsive to the user request using the customized product offering.” Claims 9 and 17 recite similar limitations. The combination of at least these elements uses the judicial exception in a 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. For example, per paragraphs [0010]-[0011] of the as-filed application, a standard software product may be provisioned and customized for a user before the user starts using the software and, additionally, while the user is using the software.
Applicants’ arguments regarding the rejections under 35 USC 102 and 35 USC 103 have been fully considered but, as they are directed to the instantly amended claims, they are moot in view of the new grounds of rejection.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 2-3 and 10-11 rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 2 recites “the receiving comprises.” It is unclear which receiving step in claim 1 “the receiving” is referring to. For purposes of examination, the Examiner is interpreting “the receiving” as referring to the receiving user data step in claim 1.
Claim 10 is rejected for similar reasons.
Claims 3 and 11 inherit the deficiencies of claims 2 and 10.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-3, 5, 8-11, 13, and 16 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by US 11,436,654 B2 to Coldwell et al. (hereinafter “Coldwell”).
Claims 1 and 9: Coldwell discloses systems and methods for a computing device to “display a build-to-order user interface to enable a default configuration of a configurable device to be modified.” (See Coldwell, at least Abstract). Coldwell further discloses at least one processor; and at least one non-transitory computer readable medium (See Coldwell, at least FIG. 5 and associated text; col. 15, lines 10-30, computing device to implement systems and methods includes processor, memory, storage devices). Coldwell further discloses:
receiving, by at least one processor, user data indicating a scope of work through a user interface (UI) of a standard product offering during a user session (See Coldwell, at least FIG. 1 and associated text; col. 2, lines 62-67, user opens a web browser and navigates to a manufacturer’s site to custom configure a device; col. 3, lines 34-67 manufacturer’s site provides a user interface (UI) so that the user can select various options for the device such as the CPU manufacturer, type of processor, clock speed, type of disk drive, etc.; UI pre-fills the options with default values (such as the most popular options); col. 4, lines 8-15, user modifies one or more options of the default values);
predicting, by the at least one processor, at least one resource required to complete the scope of work, the predicting comprising processing the user data with a machine learning (ML) process (See Coldwell, at least col. 4, lines 65-67, system keeps track of an order in which the user modifies the default configuration and determine a priority associated with each modification based on the order; col. 9, lines 15-37, if the user modifies the type of processor first, and then the delivery options, the suggestion algorithm determines the priority order to be processor type and faster delivery; machine learning may be used to determine the priorities);
determining, by the at least one processor, at least one provisioning property of the at least one resource (See Coldwell, at least col. 4, lines 65-67, system keeps track of an order in which the user modifies the default configuration and determine a priority associated with each modification based on the order; col. 9, lines 15-37, user modifies the type of processor to be i5 instead of i3);
applying, by the at least one processor, the at least one provisioning property to the standard product offering during the user session, thereby creating a customized product offering commensurate with the scope of work (See Coldwell, at least FIG. 1 and associated text; col. 9, lines 15-37, user modifies the default options; for example, user modifies the type of processor to be i5 instead of i3, the delivery options to provide faster delivery, the drive type to be SSD, and the device capacity to be 512 Gb; col. 11, lines 10-20, based on the options the user has modified and order in which the user identified them, suggestion algorithm identifies matching devices, i.e., the system has applied to the user’s selections; col. 4, lines 15-25, matching devices are displayed in substantially real time);
receiving, by the at least one processor, a user request through the UI of the customized product offering during the user session (See Coldwell, at least col. 11, lines 10-20, based on the options the user has modified and order in which the user identified them, suggestion algorithm identifies and displays matching devices; col. 4, lines 15-25, matching devices are displayed in substantially real time; col. 5, lines 15-25, after viewing the matching devices, user may enter a selection to acquire (lease or purchase) a particular device); and
performing, by the at least one processor, processing responsive to the user request using the customized product offering (See Coldwell, at least col. 5, lines 15-25, after viewing the matching devices, user may enter a selection to acquire (lease or purchase) a particular device; in response, the system may send an order indicating an acquisition of the particular device).
Claim 9 is rejected for similar reasons.
Claims 2 and 10: Coldwell further discloses wherein:
the UI comprises a progression of interface elements presented to the user (See Coldwell, at least FIG. 1 and associated text; col. 3, lines 34-67 manufacturer’s site provides a user interface (UI) so that the user can select various options for the device such as the CPU manufacturer, type of processor, clock speed, type of disk drive, etc.; UI pre-fills the options with default values (such as the most popular options); col. 4, lines 8-15, user modifies one or more options of the default values; col. 9, lines 15-37, user modifies the default options; for example, user modifies the type of processor to be i5 instead of i3, the delivery options to provide faster delivery, the drive type to be SSD, and the device capacity to be 512 Gb); and
the receiving comprises, as the UI progresses through the interface elements, receiving and updating the user data through the UI (See Coldwell, at least FIG. 1 and associated text; col. 3, lines 34-67 manufacturer’s site provides a user interface (UI) so that the user can select various options for the device such as the CPU manufacturer, type of processor, clock speed, type of disk drive, etc.; UI pre-fills the options with default values (such as the most popular options); col. 4, lines 8-15, user modifies one or more options of the default values; col. 9, lines 15-37, user modifies the default options; for example, user modifies the type of processor to be i5 instead of i3, the delivery options to provide faster delivery, the drive type to be SSD, and the device capacity to be 512 Gb).
Claim 10 is rejected for similar reasons.
Claims 3 and 11: Coldwell further discloses repeating the predicting, determining, and applying in response to the updating of the user data (See Coldwell, at least col. 7, lines 30-40, after user’s initial selection of an i5 processor, suggestion algorithm extracts matching devices from database; as the user continues to make additional modifications, such as the processor speed, SSD, and capacity, suggestion algorithm continues to filter matching devices in substantially real time).
Claim 11 is rejected for similar reasons.
Claims 5 and 13: Coldwell further discloses:
determining, by the at least one processor, an estimated product offering from the at least one resource (See Coldwell, at least col. 9, lines 15-37, user modifies the default options; for example, user modifies the type of processor to be i5 instead of i3, the delivery options to provide faster delivery, the drive type to be SSD, and the device capacity to be 512 Gb; col. 11, lines 10-20, based on the options the user has modified and order in which the user identified them, suggestion algorithm identifies and displays matching devices, i.e., the system has applied to the user’s selections; col. 4, lines 15-25, matching devices are displayed in substantially real time); and
providing, by the at least one processor, information describing the estimated product offering to a user (See Coldwell, at least col. 9, lines 15-37, user modifies the default options; for example, user modifies the type of processor to be i5 instead of i3, the delivery options to provide faster delivery, the drive type to be SSD, and the drive capacity to be 512 Gb; col. 11, lines 10-20, based on the options the user has modified and order in which the user identified them, suggestion algorithm identifies and displays matching devices, i.e., the system has applied to the user’s selections; col. 4, lines 15-25, matching devices are displayed in substantially real time).
Claim 13 is rejected for similar reasons.
Claims 8 and 16: Coldwell further discloses wherein the at least one provisioning property includes at least one price, and the customized product offering includes a product price incorporating the at least one price (See Coldwell, at least col. 4, lines 65-67, system keeps track of an order in which the user modifies the default configuration and determine a priority associated with each modification based on the order; col. 11, lines 10-20, based on the options the user has modified and order in which the user identified them, suggestion algorithm identifies and displays matching devices, i.e., the system has applied to the user’s selections; col. 4, lines 29-48, system may indicate that the prebuilt devices have lower prices; col. 5, lines 14-20, at least some of the prebuilt devices may have a lower price compared to the modified custom configuration; col. 7, lines 62-67, lower price may be emphasized and user may be provided with incentives to purchase one of the prebuilt devices).
Claim 16 is rejected for similar reasons.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 17-18 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Coldwell in view of US 2024/0296400 A1 to Sinha et al. (hereinafter “Sinha”).
Claim 17: Coldwell discloses:
receiving, by at least one processor, user data indicating a scope of work through a user interface (UI) of a standard product offering during a user session (See Coldwell, at least FIG. 1 and associated text; col. 2, lines 62-67, user opens a web browser and navigates to a manufacturer’s site to custom configure a device; col. 3, lines 34-67 manufacturer’s site provides a user interface (UI) so that the user can select various options for the device such as the CPU manufacturer, type of processor, clock speed, type of disk drive, etc.; UI pre-fills the options with default values (such as the most popular options); col. 4, lines 8-15, user modifies one or more options of the default values);
predicting, by the at least one processor, at least one resource required to complete the scope of work, the predicting comprising processing the user data with a machine learning (ML) [process]… (See Coldwell, at least col. 4, lines 65-67, system keeps track of an order in which the user modifies the default configuration and determine a priority associated with each modification based on the order; col. 9, lines 15-37, if the user modifies the type of processor first, and then the delivery options, the suggestion algorithm determines the priority order to be processor type and faster delivery; machine learning may be used to determine the priorities);
determining, by the at least one processor, at least one provisioning property of the at least one resource (See Coldwell, at least col. 4, lines 65-67, system keeps track of an order in which the user modifies the default configuration and determine a priority associated with each modification based on the order; col. 9, lines 15-37, user modifies the type of processor to be i5 instead of i3);
applying, by the at least one processor, the at least one provisioning property to the standard product offering during the user session, thereby creating a customized product offering commensurate with the scope of work (See Coldwell, at least FIG. 1 and associated text; col. 9, lines 15-37, user modifies the default options; for example, user modifies the type of processor to be i5 instead of i3, the delivery options to provide faster delivery, the drive type to be SSD, and the device capacity to be 512 Gb; col. 11, lines 10-20, based on the options the user has modified and order in which the user identified them, suggestion algorithm identifies matching devices, i.e., the system has applied to the user’s selections; col. 4, lines 15-25, matching devices are displayed in substantially real time);
receiving, by the at least one processor, a user request through the UI of the customized product offering during the user session (See Coldwell, at least col. 11, lines 10-20, based on the options the user has modified and order in which the user identified them, suggestion algorithm identifies and displays matching devices; col. 4, lines 15-25, matching devices are displayed in substantially real time; col. 5, lines 15-25, after viewing the matching devices, user may enter a selection to acquire (lease or purchase) a particular device); and
performing, by the at least one processor, processing responsive to the user request using the customized product offering (See Coldwell, at least col. 5, lines 15-25, after viewing the matching devices, user may enter a selection to acquire (lease or purchase) a particular device; in response, the system may send an order indicating an acquisition of the particular device).
Coldwell does not expressly disclose the predicting comprising processing the user data with a machine learning (ML) multi-label classifier trained on at least a first training data set indicative of example scopes of work and a second training data set indicative of example resources.
However, Sinha discloses systems and methods “for obtaining a suggested configuration for a configurable object.” (See Sinha, at least Abstract). Sinha further discloses the predicting comprising processing the user data with a machine learning (ML) multi-label classifier trained on at least a first training data set indicative of example scopes of work and a second training data set indicative of example resources (See Sinha, at least para. [0056], configuration information associated with a given set of customer needs serve as labels for training a classification model; para. [0011], machine learning model is trained using a first data set including requirements data (i.e., scope of work) and configuration data for a plurality of solutions. A plurality of second machine learning models are trained using a respective plurality of second data sets, where a respective second data set of the respective plurality of second data sets includes configuration data for a respective solution (i.e., resource) of the plurality of solutions)..
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include in the custom configuration system and method of Coldwell the ability of the predicting comprising processing the user data with a machine learning (ML) multi-label classifier trained on at least a first training data set indicative of example scopes of work and a second training data set indicative of example resources as disclosed by Sinha 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. One of ordinary skill in the art would have been motivated to do so because “employ[ing] machine learning models that are customized to a particular set of products, having similar characteristics and operational needs, can provide more accurate results than a more general model that includes products with different characteristics and which satisfy different operational needs.” (See Sinha, at least para. [0051]).
Claim 18: The combination of Coldwell and Sinha discloses all the limitations of claim 17 discussed above.
Coldwell further discloses wherein:
the UI comprises a progression of interface elements presented to the user (See Coldwell, at least FIG. 1 and associated text; col. 3, lines 34-67 manufacturer’s site provides a user interface (UI) so that the user can select various options for the device such as the CPU manufacturer, type of processor, clock speed, type of disk drive, etc.; UI pre-fills the options with default values (such as the most popular options); col. 4, lines 8-15, user modifies one or more options of the default values; col. 9, lines 15-37, user modifies the default options; for example, user modifies the type of processor to be i5 instead of i3, the delivery options to provide faster delivery, the drive type to be SSD, and the device capacity to be 512 Gb), and the receiving comprises, as the UI progresses through the interface elements, receiving and updating the user data through the UI (See Coldwell, at least FIG. 1 and associated text; col. 3, lines 34-67 manufacturer’s site provides a user interface (UI) so that the user can select various options for the device such as the CPU manufacturer, type of processor, clock speed, type of disk drive, etc.; UI pre-fills the options with default values (such as the most popular options); col. 4, lines 8-15, user modifies one or more options of the default values; col. 9, lines 15-37, user modifies the default options; for example, user modifies the type of processor to be i5 instead of i3, the delivery options to provide faster delivery, the drive type to be SSD, and the device capacity to be 512 Gb); and
the method further comprises repeating the predicting, determining, and applying in response to the updating of the user data (See Coldwell, at least col. 7, lines 30-40, after user’s initial selection of an i5 processor, suggestion algorithm extracts matching devices from database; as the user continues to make additional modifications, such as the processor speed, SSD, and capacity, suggestion algorithm continues to filter matching devices in substantially real time).
Claim 20: The combination of Coldwell and Sinha discloses all the limitations of claim 17 discussed above.
Coldwell further discloses:
determining, by the at least one processor, an estimated product offering from the at least one resource (See Coldwell, at least col. 9, lines 15-37, user modifies the default options; for example, user modifies the type of processor to be i5 instead of i3, the delivery options to provide faster delivery, the drive type to be SSD, and the device capacity to be 512 Gb; col. 11, lines 10-20, based on the options the user has modified and order in which the user identified them, suggestion algorithm identifies and displays matching devices, i.e., the system has applied to the user’s selections; col. 4, lines 15-25, matching devices are displayed in substantially real time); and
providing, by the at least one processor, information describing the estimated product offering to a user (See Coldwell, at least col. 9, lines 15-37, user modifies the default options; for example, user modifies the type of processor to be i5 instead of i3, the delivery options to provide faster delivery, the drive type to be SSD, and the drive capacity to be 512 Gb; col. 11, lines 10-20, based on the options the user has modified and order in which the user identified them, suggestion algorithm identifies and displays matching devices, i.e., the system has applied to the user’s selections; col. 4, lines 15-25, matching devices are displayed in substantially real time).
Claims 6-7 and 14-15 are rejected under 35 U.S.C. 103 as being unpatentable over Coldwell as applied to claims 1 and 9 above, and further in view of Sinha.
Claims 6 and 14: Coldwell discloses all the limitations of claims 1 and 9 discussed above.
Coldwell does not expressly disclose wherein the ML process comprises predicting the at least one resource using a multi-label classifier.
However, Sinha discloses wherein the ML process comprises predicting the at least one resource using a multi-label classifier (See Sinha, at least para. [0056], configuration information associated with a given set of customer needs serve as labels for training a classification model).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include in the custom configuration system and method of Coldwell the ability wherein the ML process comprises predicting the at least one resource using a multi-label classifier as disclosed by Sinha 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. One of ordinary skill in the art would have been motivated to do so because “employ[ing] machine learning models that are customized to a particular set of products, having similar characteristics and operational needs, can provide more accurate results than a more general model that includes products with different characteristics and which satisfy different operational needs.” (See Sinha, at least para. [0051]).
Claim 14 is rejected for similar reasons.
Claims 7 and 15: Coldwell discloses all the limitations of claims 1 and 9 discussed above.
Coldwell does not expressly disclose training, by the at least one processor, at least one ML model used in the ML process with at least a first training data set indicative of example scopes of work and a second training data set indicative of example resources.
However, Sinha discloses training, by the at least one processor, at least one ML model used in the ML process with at least a first training data set indicative of example scopes of work and a second training data set indicative of example resources (See Sinha, at least para. [0011], machine learning model is trained using a first data set including requirements data (i.e., scope of work) and configuration data for a plurality of solutions. A plurality of second machine learning models are trained using a respective plurality of second data sets, where a respective second data set of the respective plurality of second data sets includes configuration data for a respective solution (i.e., resource) of the plurality of solutions).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include in the custom configuration system and method of Coldwell the ability of training, by the at least one processor, at least one ML model used in the ML process with at least a first training data set indicative of example scopes of work and a second training data set indicative of example resources as disclosed by Sinha 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. One of ordinary skill in the art would have been motivated to do so because “employ[ing] machine learning models that are customized to a particular set of products, having similar characteristics and operational needs, can provide more accurate results than a more general model that includes products with different characteristics and which satisfy different operational needs.” (See Sinha, at least para. [0051]).
Claim 15 is rejected for similar reasons.
Claims 4 and 12 are rejected under 35 U.S.C. 103 as being unpatentable over Coldwell as applied to claims 1 and 9 above, and further in view of US 2021/0241036 A1 to Benkreira et al. (hereinafter “Benkreira”).
Coldwell discloses all the limitations of claims 1 and 9 discussed above.
Coldwell does not expressly disclose wherein the determining comprises: determining at least one resource code of the at least one resource; mapping the at least one resource code to at least one application programming interface (API) code; sending at least one API call including the at least one API code to at least one API; and receiving, from the at least one API in response to the sending, data indicating the at least one provisioning property.
However, Benkreira discloses systems and methods “to facilitate machine learning for prediction using distinct dataset types.” (See Benkreira, at least Abstract). Benkreira further discloses wherein the determining comprises:
determining at least one resource code of the at least one resource (See Benkreira, at least para. [0041], software application including the API may automatically identify types of HTML tags of interest (i.e., resource code) according to set of HTML tags upon user selection of the interface object; para. [0040] content (i.e., resource) is web-based content, such as a website. Accordingly, the content may include hypertext markup language (HTML) structures);
mapping the at least one resource code to at least one application programming interface (API) code (See Benkreira, at least para. [0041], API may automatically identify types of HTML tags of interest according to set of HTML tags upon user selection of the interface object; para. [0042] user computing device 101 may compare the tags in the HTML code to the set of HTML tags of interest);
sending at least one API call including the at least one API code to at least one API (See Benkreira, at least para. [0042], Upon finding a match, the user computing device 101 may generate the request with the matching tags and communicate the request to the content detection engine 111; para. [0041] software application may convey the HTML tags of interest to the content detection engine 111 via the API along with the request); and
receiving, from the at least one API in response to the sending, data indicating the at least one provisioning property (See Benkreira, at least para. [0044] content detection engine 111 may utilize the tags provided with the request to identify the content including the product associated with the product identifier (e.g., a name, serial number, vendor, manufacturer, or other identifier associated with the HTML tag for the product identifier), and the product price; para. [0039] content detection engine 111 may receive the request and automatically identify content, including appropriate data items for which to predict future variations and/or states).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include in the custom configuration system and method of Coldwell the ability wherein the determining comprises: determining at least one resource code of the at least one resource; mapping the at least one resource code to at least one application programming interface (API) code; sending at least one API call including the at least one API code to at least one API; and receiving, from the at least one API in response to the sending, data indicating the at least one provisioning property disclosed by Benkreira 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. One of ordinary skill in the art would have been motivated to do so to improve the efficiency of the user computing device. (See Benkreira, at least para. [0043).
Claim 12 is rejected for similar reasons.
Claim 19 is rejected under 35 U.S.C. 103 as being unpatentable over Coldwell in view of Sinha as applied to claim 17 above, and further in view of Benkreira.
The combination of Coldwell and Sinha discloses all the limitations of claim 17 discussed above.
Neither Coldwell nor Sinha expressly discloses wherein the determining comprises: determining at least one resource code of the at least one resource; mapping the at least one resource code to at least one application programming interface (API) code; sending at least one API call including the at least one API code to at least one API; and receiving, from the at least one API in response to the sending, data indicating the at least one provisioning property.
However, Benkreira discloses wherein the determining comprises:
determining at least one resource code of the at least one resource (See Benkreira, at least para. [0041], software application including the API may automatically identify types of HTML tags of interest (i.e., resource code) according to set of HTML tags upon user selection of the interface object; para. [0040] content (i.e., resource) is web-based content, such as a website. Accordingly, the content may include hypertext markup language (HTML) structures);
mapping the at least one resource code to at least one application programming interface (API) code (See Benkreira, at least para. [0041], API may automatically identify types of HTML tags of interest according to set of HTML tags upon user selection of the interface object; para. [0042] user computing device 101 may compare the tags in the HTML code to the set of HTML tags of interest);
sending at least one API call including the at least one API code to at least one API (See Benkreira, at least para. [0042], Upon finding a match, the user computing device 101 may generate the request with the matching tags and communicate the request to the content detection engine 111; para. [0041] software application may convey the HTML tags of interest to the content detection engine 111 via the API along with the request); and
receiving, from the at least one API in response to the sending, data indicating the at least one provisioning property (See Benkreira, at least para. [0044] content detection engine 111 may utilize the tags provided with the request to identify the content including the product associated with the product identifier (e.g., a name, serial number, vendor, manufacturer, or other identifier associated with the HTML tag for the product identifier), and the product price; para. [0039] content detection engine 111 may receive the request and automatically identify content, including appropriate data items for which to predict future variations and/or states).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to include in the custom configuration system and method of Coldwell and the configuration system and method of Sinha the ability wherein the determining comprises: determining at least one resource code of the at least one resource; mapping the at least one resource code to at least one application programming interface (API) code; sending at least one API call including the at least one API code to at least one API; and receiving, from the at least one API in response to the sending, data indicating the at least one provisioning property disclosed by Benkreira 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. One of ordinary skill in the art would have been motivated to do so to improve the efficiency of the user computing device. (See Benkreira, at least para. [0043).
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 extension fee 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 date of this final action.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ANNE MARIE GEORGALAS whose telephone number is (571)270-1258 E.S.T.. The examiner can normally be reached on Monday-Friday 8:30am-5:00pm.
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, Marissa Thein can be reached on 571-272-6764. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/Anne M Georgalas/
Primary Examiner, Art Unit 3689
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