DETAILED ACTION
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Responsive to the communication dated 05/12/2026
Claims 1-20 are presented for examination
Information Disclosure Statement
The IDS dated 04/15/2026 and 07/14/2026 has been reviewed. See attached.
Drawings
The drawings dated 09/28/2022 have been reviewed. They are accepted.
Abstract
The abstract dated 05/12/2026 has been reviewed. It has 142 words, and contains no legal phraseology. It is accepted.
Finality
THIS ACTION IS MADE FINAL. 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 mailing date of this final action.
Response to Arguments- Double Patenting
Applicant’s arguments, see pages 14-15, filed 05/12/2026, with respect to the rejection of claims 1-20 under various forms of Double Patenting rejection have been fully considered and are persuasive. The rejection of claims 1-20 under various forms of Double Patenting rejection has been withdrawn.
In particular, as terminal disclaimers have been filed for all three patents/applications cited in the previous rejection, which were all commonly owned by the applicants, (See US Pat. 11,733,853, US Pat. 12,147,659, and US Pat. App. 17/955,392) the Double Patenting rejections based on these patents/applications have been withdrawn.
Response to Arguments- Claim Objections
Applicant’s arguments, see 15, filed 05/12/2026, with respect to the have been fully considered and are persuasive. The objections tohave been withdrawn.
Response to Arguments- 35 USC § 112
Applicant's arguments filed 05/12/2026 have been fully considered but they are not persuasive.
Applicant provides no arguments and simply states that the previous rejections under 35 USC § 112 are “respectfully traversed.” However, the issues the claims were previously rejected for have not been fixed by the amendments.
Firstly, Claims 1, 8, and 15 recite the limitation "... at least one parameter, of the plurality of corresponding parameters.” There is insufficient antecedent basis for this limitation in the claim. It is unclear what these parameters are referring to. The claim had previously described “corresponding control points,” and “adjustment parameters,” but no “corresponding parameters” were previously identified. The new amendments have not clarified what these “corresponding parameters” correspond to.
Claims 1, 8, and 15 recite the limitation “the plurality of adjustment parameters of a particular parametric model.” There is insufficient antecedent basis for this limitation in the claim. While a plurality of adjustment parameters was previously introduced, it was not previously introduced as being specific to particular parametric models. Similarly to the previous issue, the claim amendments do not clarify or introduce model-specific adjustment parameters, with the with each particular parametric model merely “having at least one parameter.” It is important to note that the claims do not identify the “at least one parameter” previously introduced as being from the “plurality of adjustment parameters. Are these particular parametric model-specific adjustment parameters a separate set of adjustment parameters, unconnected to the previous adjustment parameters, or are the previous adjustment parameters a global set from which certain parameters are chosen for particular parametric models?
Response to Arguments- 35 USC § 101
Applicant’s arguments, see pages 15-22, filed 05/12/2026, with respect to the rejection of claims 1-20 under 35 USC § 101 have been fully considered and are persuasive. The rejection of claims 1-20 under 35 USC § 101 has been withdrawn.
The particular way the claimed system generates the custom clothing models through dynamic control point interpolation to improve fit using a specific series of user interfaces and then manufactures the clothing using the interpolated data to generate custom in-between clothing sizes specifically matched to individuals successfully integrates the claims into a practical application.
Response to Arguments- 35 USC § 103
Applicant's arguments filed 05/12/2026 have been fully considered but they are not persuasive.
Applicant argues that no prior art teaches based on the plurality of adjustment parameters [received via the first user interface, for improving the clothing fits of the custom product in relation to user-specific data] and the plurality of parametric models, determining two particular parametric models for the custom product, each having at least one parameter, of the plurality of corresponding parameters, for improving the clothing fit of the custom product; [...]
generating, for the custom product, a parametric fit model having a plurality of fit model parameters; wherein each fit model parameter, of the plurality of fit model parameters, is computed by interpolating, for the at least one parameter of the two particular parametric models, between one or more corresponding control points of a first parametric model of the two particular parametric models and one or more corresponding control points of a second parametric model of the two particular parametric models; [...]
transmitting the parametric fit model to a manufacturer to cause the manufacturer to produce a parametric physical product based on the plurality of fit model parameters of the parametric fit model.
Examiner responds by explaining that these features are taught by the combination of Beaver, Terai, and Donelly. Particularly,
Beaver teaches based on the plurality of adjustment parameters [received via the first user interface, for improving the clothing fits of the custom product in relation to user-specific data] and the plurality of parametric models, ([Par 110] “The models may be parametric, i.e., they may have parameters that, through coded relationships, adjust the form of the model for a specific need. For instance, a set of 3D models may represent a bike helmet. Each model may fit a statistically normed human head of a specific age.” [Par 145-147] “ In some embodiments, a product option framework is configured to generate a product option framework user interface. Accordingly, each product options set is associated with logic and code to build a user interface element for each parametric product option. Furthermore, each product options set contains style hints so that each user interface element may be artfully placed to produce a high quality user experience…. The user interface elements may include… a size selector” [Par 128-129] “In some embodiments, the product option set contains the logic to enumerate each customizable option in a manner that presents a complete user interface to change the parametric product instructions… The instructions for manufacturing a customized product are usually parametric. The parameters include the size of the customized product (this can be multi-dimensional, and include width, height, depth). The parameters may also relate to human sizes or ages. The parameters may also be custom and based on biometric information.”) ([Par 110] “The models may be parametric, i.e., they may have parameters that, through coded relationships, adjust the form of the model for a specific need. For instance, a set of 3D models may represent a bike helmet. Each model may fit a statistically normed human head of a specific age.” [Par 145-147] “ In some embodiments, a product option framework is configured to generate a product option framework user interface. Accordingly, each product options set is associated with logic and code to build a user interface element for each parametric product option. Furthermore, each product options set contains style hints so that each user interface element may be artfully placed to produce a high quality user experience…. The user interface elements may include… a size selector”) [...]
generating, for the custom product, a parametric fit model having a plurality of fit model parameters; wherein each fit model parameter, of the plurality of fit model parameters, is computed by ([Par 201-202] “In some embodiments, the computer collaboration system may cause displaying, in a user interface executing in a user device of the customer, an interactive design along with annotations representing attributes, attribute groups and the locations within the design to which the attributes apply. The attributes, default values for the attributes and default ranges for the values for the attributes may be provided by an attribute engine which may be part of the computer collaboration system. The attribute engine may define and/or filter the attributes according to constraints provided by manufacturers, designers, or system administrators. In response to receiving, in the user interface, a rendering of the interactive design with the annotations, a user may select, using the functionalities of the user interface, a specific attribute or a specific attribute group at a specific location within the depiction of the interactive design and select or adjust a value associated with the attribute. For example, the user may select a width-attribute and use a slider object, provided by the user interface, to set a new value for the width parameter” [Par 145-147] “ In some embodiments, a product option framework is configured to generate a product option framework user interface. Accordingly, each product options set is associated with logic and code to build a user interface element for each parametric product option. Furthermore, each product options set contains style hints so that each user interface element may be artfully placed to produce a high quality user experience…. The user interface elements may include… a size selector” [Par 128-129] “In some embodiments, the product option set contains the logic to enumerate each customizable option in a manner that presents a complete user interface to change the parametric product instructions… The instructions for manufacturing a customized product are usually parametric. The parameters include the size of the customized product (this can be multi-dimensional, and include width, height, depth). The parameters may also relate to human sizes or ages. The parameters may also be custom and based on biometric information.” [Par 110] “The product instructions may also include models, including 2D and 3D models that are used to form, through additive manufacturing, or subtractive manufacturing, portions of a product. The models may be parametric, i.e., they may have parameters that, through coded relationships, adjust the form of the model for a specific need. For instance, a set of 3D models may represent a bike helmet.” [Examiner’s note: the “adjustment parameters” refer to the input custom sizing parameters while the “fit model” and its associated parameters refer to the model of the customized product itself after adjustment]) [...]
transmitting the parametric fit model to a manufacturer to cause the manufacturer to produce a parametric physical product based on the plurality of fit model parameters of the parametric fit model. .([Par 80] “Digital designs may be transmitted from a product collaboration platform to manufacturing servers, or manufacturing entities, that may use the received digital designs to manufacture products either digitally or physically. The manufactured product may, in turn, be delivered to recipients.” [Par 186] “Based on, at least in part, the plurality of global-key-values pairs, an ownership-attribution tree is constructed. Based on, at least in part, the ownership-attribution tree, manufacturing instructions for customizing the physical product and according to the plurality of variable product attributes are generated. The manufacturing instructions may be transmitted to a product customization server to cause a manufacturing entity to proceed with generating a customized product based on the manufacturing instructions.” [Par 128-129] “In some embodiments, the product option set contains the logic to enumerate each customizable option in a manner that presents a complete user interface to change the parametric product instructions… The instructions for manufacturing a customized product are usually parametric. The parameters include the size of the customized product (this can be multi-dimensional, and include width, height, depth). The parameters may also relate to human sizes or ages. The parameters may also be custom and based on biometric information.”)
Terai makes obvious determining two particular parametric models for the custom product, each having at least one parameter, interpolating, for data of the two particular parametric models, between one or more corresponding control points of a first parametric model of the two particular parametric models and one or more corresponding control points of a second parametric model of the two particular parametric models; ([Abstract] “For a knit product to be graded, 2 sizes of pattern data are converted into knit data. Feature points that specify the shape of the knit product are generated for the converted 2 sizes of pattern data and an intermediate shape that specifies the shape of the knit product among the feature points are generated. The feature points and the intermediate shape for a target size are generated by interpolating or extrapolating among the feature points and the intermediate shapes according to the target size of the knit product. A closed loop is generated by connecting the feature points and the intermediate shapes and knit data for the target size is created by arranging a knit in a pattern specified by the loop.” [Page 2 Par 9-11] “The interpolation extrapolation unit 6 interpolates or extrapolates between the corresponding feature points and interpolates or extrapolates between the corresponding intermediate points with respect to the knit data for, for example, the maximum and the minimum two sizes. When using knit data for two sizes, interpolation or extrapolation may be performed linearly, and when three sizes or more exist, interpolation or extrapolation may be performed in a curved line with a quadratic curve or the like. When knit data for two sizes, maximum and minimum, is used, interpolation is performed. In other cases, for example, interpolation and extrapolation are performed…” [Page 4 Par 5-7] “We will consider the case where an apparel product tailored to each user is realized by knitting. When considering only the two components of width and length, the same processing as in FIG. 8 may be performed. When considering other components, FIG. 8 may be expanded to perform interpolation or extrapolation in a space of three or more dimensions. Although the intermediate points are used in the embodiment, the shape of the knit product between the feature points may be approximated by a curve or a straight line, and the feature points may be treated as the end points of the curve or the straight line. Using the parameter t, which is, for example, 0 for the feature point that is one end of the curve and 1 for the feature point that is the other end, approximates the shape of the knit product between the feature points as an algebraic curve of degree 2 or higher. be able to. If the shape of the knit product between the feature points is straight, it may be straight. Such a curve or a straight line and an intermediate point in the embodiment are called an intermediate shape between feature points, and the intermediate point generation unit 4 generates an intermediate shape automatically or by dialogue with a user. These curves or straight lines can be interpolated or extrapolated between sizes as well as intermediate points by interpolating or extrapolating between points with the same value of parameter t. Interpolation or extrapolation produces feature points at the target size and curves or straight lines that are intermediate shapes. Then, when the feature points and the intermediate shapes are connected in order, a closed loop is generated. Since feature points are the endpoints of curves or straight lines, interpolating or extrapolating between feature points means interpolating or extrapolating the endpoints of curves or straight lines. Further, connecting the feature points and the intermediate shapes means connecting the curves or straight lines having the intermediate shapes so that the end points are connected to each other.” [Page 3 Par 3] “FIG. 4 shows an intermediate generated by interpolation of the minimum size pattern data 10 and the maximum size pattern data 20, the minimum size knit data 15 and the maximum size knit data 25, and the knit data 15 and 25. The size knit data 35 is shown.” [Examiner’s note: the system of Terai takes 2 parametric models of clothing at different sizes then uses interpolation to generate models between those sizes based on the interpolation of feature points (i.e. control points)])
Clearly, Beaver teaches the base system features such as fit model parameters and interfaces for improving the fit of custom clothing using user-specific data as well as the transmitting of such data to a manufacturer to manufacture the customized product, while Terai teaches the specific method of generating a particular fit by interpolating between the control points of two different sizes of the article being customized. While neither reference taken in isolation teaches the entire claim on its own, it is clear that the combination of these references, which would have been obvious to one of ordinary skill in the art, teaches the claimed features.
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 1-20 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.
Claims 1, 8, and 15 recite the limitation "... at least one parameter, of the plurality of corresponding parameters.” There is insufficient antecedent basis for this limitation in the claim. It is unclear what these parameters are referring to. The claim had previously described “corresponding control points,” and “adjustment parameters,” but no “corresponding parameters” were previously identified
Claims 1, 8, and 15 recite the limitation “the plurality of adjustment parameters of a particular parametric model.” There is insufficient antecedent basis for this limitation in the claim. While a plurality of adjustment parameters was previously introduced, it was not previously introduced as being specific to particular parametric models.
Claim Rejections - 35 USC § 103
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.
(1) Claims 1-20 are rejected under 35 U.S.C. 103 as being unpatentable over Beaver (US 20210266352 A1) in view of Terai (JP 2021123826 A) in further view of Donelly (US 20220253923 A1)
Claim 1. Beaver teaches A method for custom fitting and manufacturing parametric products, the method comprising: generating a plurality of parametric models of a custom product based on, at least in part, past learned data pertaining to the custom product, each parametric model identified by a parametric model identifier and ([Abstract] “In some embodiments, a method for generating customized products in collaboration with live designers is disclosed. [Par 342] “In some embodiments, computer collaboration system 100 stores, for a designer, the designer's designs, samples stock pictures, and the like. That may be stored either in designer database 562 and/or designs database 564.” [Par 348] “For each interactive design available for customization using platform 100, default values of the attributes associated with the product may be modified by users according to the roles assigned to the users and according to the manufacturing constraints provided by a manufacturer. For example, if a customized product is a t-shirt, its default color may be red, but a user may modify the color by selecting any of three colors (e.g., red, green, or blue) to the tee-shirt. The modification may be stored in, for example, product data definitions 104.” [Par 110] “The models may be parametric, i.e., they may have parameters that, through coded relationships, adjust the form of the model for a specific need. For instance, a set of 3D models may represent a bike helmet. Each model may fit a statistically normed human head of a specific age.” [Par 107-108] “Referring again to FIG. 1. a customization process performed by a user, of users 10, and intended to generate a digital design of a customized product is captured in so-called product description data, which then may be translated into a manufacturing description comprising product and manufacturing instructions. The product and manufacturing instructions may include digital design specifications, data, and code needed to manufacture a custom product. That may include instructions for generating, for example, a 3D geometry for digital final products. This may also include generating instructions for generating 2D and/or 3D patterns that may be used to cut, cast, or form physical components of physical final products. The patterns may be parametric, i.e., they may have parameters that, through encoded relationships, adjust the form of the pattern for a specific need.” [Par 352] “In some embodiments, a product description may include, or be associated with, a journaled list of modifications that have been submitted by users for an interactive design. The list may also include other information such as identifiers of the users who provided the modifications, global-key-values generated as the collaborators collaborated on the customized product, a history log of the modifications that have been accepted, reverted or deleted, comments that have been provided by the user, and the like. For example, one or more modifications stored in the list may be undone or redone by using a couple of clicks, not by performing countless clicks to undo or redo the customization as in conventional customization platforms.” [Par 93] “ product description data that captures key-value pairs describing the parameters and characteristics of the interactive digital designs as the customer and the designers collaborate on the designs.” [Par 96] “generate tokens that allow recipients of the final products to request services and access to core services 16, and attach the tokens to, or depict the token on, the final products.”[Par 347] “Descriptions of the attributes for each interactive design, or groups of designs, may be stored as part of collaboration components 106 or in a separate data structure that may be organized as a data table or storage space that is accessible to collaboration components 106.”) ([Par 145-147] “ In some embodiments, a product option framework is configured to generate a product option framework user interface. Accordingly, each product options set is associated with logic and code to build a user interface element for each parametric product option. Furthermore, each product options set contains style hints so that each user interface element may be artfully placed to produce a high quality user experience…. The user interface elements may include a design view, a color editor, a font editor, a size selector, a texture selector, a text editor, a fabric swatch selector, a product real view, and the like. In some embodiments, a product options framework cooperates with a user product renderer that may be implemented in, for example, a RealView server 16A. The user product renderer may be configured to render views of a custom product as though it is already manufactured. Typically, it uses a product option set of key-values as input. It creates one or more run-time assets using computational photography of the manufactured product.”) receiving, via the first user interface, a plurality of adjustment parameters for improving a clothing fit of the custom product in relation to user-specific data; ([Par 145-147] “ In some embodiments, a product option framework is configured to generate a product option framework user interface. Accordingly, each product options set is associated with logic and code to build a user interface element for each parametric product option. Furthermore, each product options set contains style hints so that each user interface element may be artfully placed to produce a high quality user experience…. The user interface elements may include… a size selector” [Par 128-129] “In some embodiments, the product option set contains the logic to enumerate each customizable option in a manner that presents a complete user interface to change the parametric product instructions… The instructions for manufacturing a customized product are usually parametric. The parameters include the size of the customized product (this can be multi-dimensional, and include width, height, depth). The parameters may also relate to human sizes or ages. The parameters may also be custom and based on biometric information.”) based on the plurality of adjustment parameters and the plurality of parametric models, ([Par 110] “The models may be parametric, i.e., they may have parameters that, through coded relationships, adjust the form of the model for a specific need. For instance, a set of 3D models may represent a bike helmet. Each model may fit a statistically normed human head of a specific age.” [Par 145-147] “ In some embodiments, a product option framework is configured to generate a product option framework user interface. Accordingly, each product options set is associated with logic and code to build a user interface element for each parametric product option. Furthermore, each product options set contains style hints so that each user interface element may be artfully placed to produce a high quality user experience…. The user interface elements may include… a size selector” [Par 128-129] “In some embodiments, the product option set contains the logic to enumerate each customizable option in a manner that presents a complete user interface to change the parametric product instructions… The instructions for manufacturing a customized product are usually parametric. The parameters include the size of the customized product (this can be multi-dimensional, and include width, height, depth). The parameters may also relate to human sizes or ages. The parameters may also be custom and based on biometric information.”) ([Par 110] “The models may be parametric, i.e., they may have parameters that, through coded relationships, adjust the form of the model for a specific need. For instance, a set of 3D models may represent a bike helmet. Each model may fit a statistically normed human head of a specific age.” [Par 145-147] “ In some embodiments, a product option framework is configured to generate a product option framework user interface. Accordingly, each product options set is associated with logic and code to build a user interface element for each parametric product option. Furthermore, each product options set contains style hints so that each user interface element may be artfully placed to produce a high quality user experience…. The user interface elements may include… a size selector” [Par 128-129] “In some embodiments, the product option set contains the logic to enumerate each customizable option in a manner that presents a complete user interface to change the parametric product instructions… The instructions for manufacturing a customized product are usually parametric. The parameters include the size of the customized product (this can be multi-dimensional, and include width, height, depth). The parameters may also relate to human sizes or ages. The parameters may also be custom and based on biometric information.”) ([Par 145-147] “ In some embodiments, a product option framework is configured to generate a product option framework user interface. Accordingly, each product options set is associated with logic and code to build a user interface element for each parametric product option. Furthermore, each product options set contains style hints so that each user interface element may be artfully placed to produce a high quality user experience…. The user interface elements may include… a size selector” [Par 128-129] “In some embodiments, the product option set contains the logic to enumerate each customizable option in a manner that presents a complete user interface to change the parametric product instructions… The instructions for manufacturing a customized product are usually parametric. The parameters include the size of the customized product (this can be multi-dimensional, and include width, height, depth). The parameters may also relate to human sizes or ages. The parameters may also be custom and based on biometric information.”) a parametric fit model having a plurality of fit model parameters; wherein each fit model parameter, of the plurality of fit model parameters, is computed by ([Par 201-202] “In some embodiments, the computer collaboration system may cause displaying, in a user interface executing in a user device of the customer, an interactive design along with annotations representing attributes, attribute groups and the locations within the design to which the attributes apply. The attributes, default values for the attributes and default ranges for the values for the attributes may be provided by an attribute engine which may be part of the computer collaboration system. The attribute engine may define and/or filter the attributes according to constraints provided by manufacturers, designers, or system administrators. In response to receiving, in the user interface, a rendering of the interactive design with the annotations, a user may select, using the functionalities of the user interface, a specific attribute or a specific attribute group at a specific location within the depiction of the interactive design and select or adjust a value associated with the attribute. For example, the user may select a width-attribute and use a slider object, provided by the user interface, to set a new value for the width parameter” [Par 145-147] “ In some embodiments, a product option framework is configured to generate a product option framework user interface. Accordingly, each product options set is associated with logic and code to build a user interface element for each parametric product option. Furthermore, each product options set contains style hints so that each user interface element may be artfully placed to produce a high quality user experience…. The user interface elements may include… a size selector” [Par 128-129] “In some embodiments, the product option set contains the logic to enumerate each customizable option in a manner that presents a complete user interface to change the parametric product instructions… The instructions for manufacturing a customized product are usually parametric. The parameters include the size of the customized product (this can be multi-dimensional, and include width, height, depth). The parameters may also relate to human sizes or ages. The parameters may also be custom and based on biometric information.” [Par 110] “The product instructions may also include models, including 2D and 3D models that are used to form, through additive manufacturing, or subtractive manufacturing, portions of a product. The models may be parametric, i.e., they may have parameters that, through coded relationships, adjust the form of the model for a specific need. For instance, a set of 3D models may represent a bike helmet.” [Examiner’s note: the “adjustment parameters” refer to the input custom sizing parameters while the “fit model” and its associated parameters refer to the model of the customized product itself after adjustment]) wherein a fit model parameter, of the plurality of fit model parameters of the parametric fit model, is represented as a fit key-value pair; ([Par 93] “The approach also includes managing access to product description data that captures key-value pairs describing the parameters and characteristics of the interactive digital designs as the customer and the designers collaborate on the designs” [Par 132] “In some embodiments, a product option may be represented as a key-value pair. The key-value pair is a label that may span individual products and represent a class of products. The keys of pairs may include a material type, a color, a size, and the like.” [Par 335] “Each modification may be automatically saved as a serialized key-value pair, and this solves the technical problem of navigating through countless sets of attributes and dealing with, for example, countless clicks to complete the customization as required in conventional customization platforms. The pairs may be transmitted to a product options framework, which would update the product description for the interactive digital design.” [Par 107] “Referring again to FIG. 1. a customization process performed by a user, of users 10, and intended to generate a digital design of a customized product is captured in so-called product description data, which then may be translated into a manufacturing description comprising product and manufacturing instructions.”) transmitting the parametric fit model to a manufacturer to cause the manufacturer to produce a parametric physical product based on the plurality of fit model parameters of the parametric fit model.([Par 80] “Digital designs may be transmitted from a product collaboration platform to manufacturing servers, or manufacturing entities, that may use the received digital designs to manufacture products either digitally or physically. The manufactured product may, in turn, be delivered to recipients.” [Par 186] “Based on, at least in part, the plurality of global-key-values pairs, an ownership-attribution tree is constructed. Based on, at least in part, the ownership-attribution tree, manufacturing instructions for customizing the physical product and according to the plurality of variable product attributes are generated. The manufacturing instructions may be transmitted to a product customization server to cause a manufacturing entity to proceed with generating a customized product based on the manufacturing instructions.” [Par 128-129] “In some embodiments, the product option set contains the logic to enumerate each customizable option in a manner that presents a complete user interface to change the parametric product instructions… The instructions for manufacturing a customized product are usually parametric. The parameters include the size of the customized product (this can be multi-dimensional, and include width, height, depth). The parameters may also relate to human sizes or ages. The parameters may also be custom and based on biometric information.”)
Beaver does not explicitly teach models having a plurality of corresponding control points; determining two particular parametric models for the custom product, each having at least one parameter wherein the at least one parameter is within a particular tolerance of at least one parameter of a particular parametric model of the two particular parametric models; interpolating, for data of the two particular parametric models, between one or more corresponding control points of a first parametric model of the two particular parametric models and one or more corresponding control points of a second parametric model of the two particular parametric models;
Terai makes obvious models having a plurality of corresponding control points; determining two particular parametric models for the custom product, each having at least one parameter wherein the at least one parametersecond parametric model of the two particular parametric models; ([Abstract] “For a knit product to be graded, 2 sizes of pattern data are converted into knit data. Feature points that specify the shape of the knit product are generated for the converted 2 sizes of pattern data and an intermediate shape that specifies the shape of the knit product among the feature points are generated. The feature points and the intermediate shape for a target size are generated by interpolating or extrapolating among the feature points and the intermediate shapes according to the target size of the knit product. A closed loop is generated by connecting the feature points and the intermediate shapes and knit data for the target size is created by arranging a knit in a pattern specified by the loop.” [Page 2 Par 9-11] “The interpolation extrapolation unit 6 interpolates or extrapolates between the corresponding feature points and interpolates or extrapolates between the corresponding intermediate points with respect to the knit data for, for example, the maximum and the minimum two sizes. When using knit data for two sizes, interpolation or extrapolation may be performed linearly, and when three sizes or more exist, interpolation or extrapolation may be performed in a curved line with a quadratic curve or the like. When knit data for two sizes, maximum and minimum, is used, interpolation is performed. In other cases, for example, interpolation and extrapolation are performed…” [Page 4 Par 5-7] “We will consider the case where an apparel product tailored to each user is realized by knitting. When considering only the two components of width and length, the same processing as in FIG. 8 may be performed. When considering other components, FIG. 8 may be expanded to perform interpolation or extrapolation in a space of three or more dimensions. Although the intermediate points are used in the embodiment, the shape of the knit product between the feature points may be approximated by a curve or a straight line, and the feature points may be treated as the end points of the curve or the straight line. Using the parameter t, which is, for example, 0 for the feature point that is one end of the curve and 1 for the feature point that is the other end, approximates the shape of the knit product between the feature points as an algebraic curve of degree 2 or higher. be able to. If the shape of the knit product between the feature points is straight, it may be straight. Such a curve or a straight line and an intermediate point in the embodiment are called an intermediate shape between feature points, and the intermediate point generation unit 4 generates an intermediate shape automatically or by dialogue with a user. These curves or straight lines can be interpolated or extrapolated between sizes as well as intermediate points by interpolating or extrapolating between points with the same value of parameter t. Interpolation or extrapolation produces feature points at the target size and curves or straight lines that are intermediate shapes. Then, when the feature points and the intermediate shapes are connected in order, a closed loop is generated. Since feature points are the endpoints of curves or straight lines, interpolating or extrapolating between feature points means interpolating or extrapolating the endpoints of curves or straight lines. Further, connecting the feature points and the intermediate shapes means connecting the curves or straight lines having the intermediate shapes so that the end points are connected to each other.” [Page 3 Par 3] “FIG. 4 shows an intermediate generated by interpolation of the minimum size pattern data 10 and the maximum size pattern data 20, the minimum size knit data 15 and the maximum size knit data 25, and the knit data 15 and 25. The size knit data 35 is shown.” [Examiner’s note: the system of Terai takes 2 parametric models of clothing at different sizes then uses interpolation to generate models between those sizes based on the interpolation of feature points (i.e. control points)])
Terai is analogous art because it is within the field of automatic clothes model generation. It would have been obvious to one of ordinary skill in the art to combine Terai with Beaver before the effective filing date. One of ordinary skill in the art would have been motivated to make this combination in order to make the customization and production of certain types of products easier. As noted by Terai, the customization and production, particularly the generation of new sizes from a base design, is notoriously difficult with knit products and frequently requires manual trial and error ([Page 1 Par 3] “Shoe uppers come in multiple sizes for the same design. Therefore, pattern data is prepared for the shoe upper of each size and converted into knit data for each size. The knit data is data for driving the knitting machine. By the way, even if the shoe upper is knitted according to the knit data converted from the pattern data, the shape of the shoe upper often does not match the pattern data. Therefore, it is necessary to correct the knit data by trial and error so that the shoe upper can be knitted according to the pattern data. However, for many sizes, it is difficult to correct the knit data by trial and error.”) To this end, Terai presents a method for the automatic grading (i.e. generation of new sizes from a base design) of knit products without unnecessary steps or the need to manually create intermediate sizes ([Abstract] “For a knit product to be graded, 2 sizes of pattern data are converted into knit data. Feature points that specify the shape of the knit product are generated for the converted 2 sizes of pattern data and an intermediate shape that specifies the shape of the knit product among the feature points are generated. The feature points and the intermediate shape for a target size are generated by interpolating or extrapolating among the feature points and the intermediate shapes according to the target size of the knit product. A closed loop is generated by connecting the feature points and the intermediate shapes and knit data for the target size is created by arranging a knit in a pattern specified by the loop. EFFECT: Since knit data such as an intermediate size can be generated from 2 sizes of knit data without passing through pattern data such as an intermediate size, conversion from the pattern data to the knit data is unnecessary for the intermediate size and the like.”) Overall, one of ordinary skill in the art would have recognized that combining Terai with Beaver would result in a system that makes customization and production of products with particular manufacturing methods, such as knit products, significantly easier.
The combination of Beaver and Terai does not explicitly teach at least one parameter that is within a particular tolerance of at least one parameter of a model
Donnelly makes obvious at least one parameter that is within a particular tolerance of at least one parameter of a model ([Par 69] “Size prediction is implemented by first determining a number of fit factors for a given garment model. Fit factors for a jacket may include such measurements as overarm circumference, biceps circumference, sleeve length and major circumference. Then, for each fit factor, a method of measuring the key dimensions on both the garment model and the body scan fit model are determined. Also for each fit factor, threshold values of the key dimension are determined to place the user into an appropriate size category.”)
Donelly is analogous art because it is within the field of clothing modelling. It would have been obvious to combine it with Beaver and Terai before the effective filing date. One of ordinary skill in the art would have been motivated to make this combination in order to better ensure fit and thus product satisfaction. As noted by Donelly, a significant reason of product dissatisfaction and subsequent return is poor sizing. ([Par 2-4] “Recent years have seen an overwhelming growth of electronic commerce in the apparel industry. One of the greatest problems plaguing both electronic apparel merchants and customers is the difficulty in determining how a garment will fit the customer. Customers are nervous about purchasing garments electronically, because they are unsure of what size to order, and how that garment will look on them. Merchants are nervous about the high volume of apparel returns. For a merchant, the handling of an apparel return can cost up to four times what it cost to process the initial sale of the apparel. Industry analysts have estimated that apparel returns for electronic merchants range from about 10% for very basic items to between 35%-40% for high end clothing. The single biggest reason for returns of apparel purchased electronically is poor fit.”) To this end, Donelly presents a method for fit preview and analysis using actual body scans of a customer, ensuring proper sizing can be selected ([Par 18-19] “A system and method for implementing a “virtual fitting room” is disclosed. The virtual fitting room of the present invention, hereinafter referred to as the software, is a software program that will, among other features, provide an actual analysis of how a garment will fit a customer, and which will provide a realistic visual representation of the garment's fit on the customer. … The software uses a full-body scanner (using any scanning technique, such as white light, laser, or infrared, radar, lidar, ultraviolet, and other methods) to generate a cloud of data points to collectively describe the surface geometry of a body. The cloud of data is defined as a plurality of points defined as XYZ coordinates. By working with a cloud of data points, the system can remain scanner-independent; that is, it can use data generated by any scanner capable of generating a cloud of data points). The system then processes this data to achieve an accurate body scan fit model of the user.”) Overall, one of ordinary skill in the art would have recognized that combining Donelly with Beaver and Terai would result in a system that not only allowed for the rich customization and size adjustment of production, but also allowed for those customizations and adjustments to be made based on actual morphological data of the customer, ultimately leading to better fit and higher satisfaction.
Claim 2. Beaver teaches further comprising storing the parametric fit model, having the plurality of fit model parameters, in association with a user profile of a user. ([Par 352] “ In some embodiments, a product description may include, or be associated with, a journaled list of modifications that have been submitted by users for an interactive design. The list may also include other information such as identifiers of the users who provided the modifications, global-key-values generated as the collaborators collaborated on the customized product, a history log of the modifications that have been accepted, reverted or deleted, comments that have been provided by the user, and the like” [Par 369] “User interface elements may be specific not only to a role assigned to a user, but also to an interactive design itself. For example, if platform 10 offers customizable ties and customizable scarfs, and a user profile for a user includes information indicating that the user is a male, then it is assumed that the user might want to customize a tie, not a scarf. Furthermore, it may be assumed that the user would like to customize a color, a material, and a shape of the tie. Based on that information, collaboration components 106 may select the user interface elements that are specific to the tie and to the selection of the tie attributes.”)
Claim 3. Beaver teaches receiving a request to invite an agent to collaborate on adjusting the parametric fit model; ([Par 175] “Furthermore, collaboration server 155 may cooperate with request analyzer 159 and transmit (20E2) a request made by customer 202 for, for example, assistance from designer 212 (or agent 216), to request analyzer 159.” [Par 193] “ A customer may collaborate with a designer, also referred to as a live designer or an agent. For example, a customer may ask for assistance from a designer to help the customer to customize an interactive design and show the customer how the designer would modify the interactive design to achieve the design that the customer would like to see.”) based on, at least in part, a plurality of fit parameters of the parametric fit model, generating a second graphical representation of the parametric physical product; generating a second user interface and displaying, on a user computer display device, the second user interface comprising at least the second graphical representation of the parametric physical product; generating a third user interface and displaying, on an agent computer display device, the third user interface comprising at least the second graphical representation of the parametric physical product; ([Par 201-202] “In some embodiments, the computer collaboration system may cause displaying, in a user interface executing in a user device of the customer, an interactive design along with annotations representing attributes, attribute groups and the locations within the design to which the attributes apply. The attributes, default values for the attributes and default ranges for the values for the attributes may be provided by an attribute engine which may be part of the computer collaboration system. The attribute engine may define and/or filter the attributes according to constraints provided by manufacturers, designers, or system administrators. In response to receiving, in the user interface, a rendering of the interactive design with the annotations, a user may select, using the functionalities of the user interface, a specific attribute or a specific attribute group at a specific location within the depiction of the interactive design and select or adjust a value associated with the attribute. For example, the user may select a width-attribute and use a slider object, provided by the user interface, to set a new value for the width parameter. The new value of the parameter may be transmitted as a serialized key-value pair to a product options framework.” [Par 303-305] “Also in step 716, the collaboration computer transmits to the particular user device associated with the particular designer, the product description data for rendering the interactive digital design. At this point, the particular designer may access the interactive digital design, modify it, and otherwise update it to help the customer with the interactive design. In step 718, in response to receiving modifications to the interactive digital design from the particular designer, the collaboration computer automatically generates updated product description data by updating the product description data based on the modifications received from the particular designer. Furthermore, the collaboration computer propagates the updated product description data to the user interface of the customer and to the particular user interface of the particular designer to cause the interfaces to update their displays of the interactive digital design based on the updated product description data.” [Par 196] “Customization of an interactive design in collaboration between a customer and a live designer may include creating the design and modifying the design by both the customer and the designer. To be able to customize the design, the customer and the designer may share access to product description data associated with the design.”) receiving, via the second user interface, a plurality of user adjustment parameters for improving a clothing fit of the parametric physical product; receiving, via the third user interface, a plurality of agent adjustment parameters for improving a clothing fit of the parametric physical product; based on the plurality of user adjustment parameters, the plurality of agent adjustment parameters and the plurality of fit parameters of the parametric physical product, generating, for the custom product, an adjusted parametric fit model having a plurality of new fit model parameters; wherein a new fit model parameter, of the plurality of new fit model parameters of the adjusted parametric fit model, is represented as an adjusted fit key-value pair; sending the adjusted parametric fit model to the manufacturer to cause the manufacturer to produce the parametric physical product based on a plurality of adjusted fit model parameters of the adjusted parametric fit model. ([Par 302] “In step 716, in response to receiving an acceptance of the electronic digital collaboration invitation from the particular designer, the collaboration computer grants the particular designer access to product description data as an editor. The product description data includes data that are associated with an interactive design which the customer tries to create, and that comprise key-value pairs, described above.” [Par 305-306] “Furthermore, the collaboration computer propagates the updated product description data to the user interface of the customer and to the particular user interface of the particular designer to cause the interfaces to update their displays of the interactive digital design based on the updated product description data. The process of modifying the product description data during a collaboration session between the customer and the designer may be repeated several times. In some embodiments, the collaboration server may handle editing of the same user interface modifying the same key-value pair within interaction time in several ways depending on agreement between the customer and the designer. In one method, the designer's modification is always selected. In another method, the customer's edit is shown to the designer to accept or reject. In another method, the designer's edit is shown to the customer to accept or reject. In yet another method, the customer's edit is applied, and then the designer's edit. In other embodiments there are methods to apply all edits in the order in which they reach the collaboration server” [Par 201-202] “In some embodiments, the computer collaboration system may cause displaying, in a user interface executing in a user device of the customer, an interactive design along with annotations representing attributes, attribute groups and the locations within the design to which the attributes apply. The attributes, default values for the attributes and default ranges for the values for the attributes may be provided by an attribute engine which may be part of the computer collaboration system. The attribute engine may define and/or filter the attributes according to constraints provided by manufacturers, designers, or system administrators. In response to receiving, in the user interface, a rendering of the interactive design with the annotations, a user may select, using the functionalities of the user interface, a specific attribute or a specific attribute group at a specific location within the depiction of the interactive design and select or adjust a value associated with the attribute. For example, the user may select a width-attribute and use a slider object, provided by the user interface, to set a new value for the width parameter. The new value of the parameter may be transmitted as a serialized key-value pair to a product options framework.” [Par 80] “Digital designs may be transmitted from a product collaboration platform to manufacturing servers, or manufacturing entities, that may use the received digital designs to manufacture products either digitally or physically. The manufactured product may, in turn, be delivered to recipients.” [Par 186] “Based on, at least in part, the plurality of global-key-values pairs, an ownership-attribution tree is constructed. Based on, at least in part, the ownership-attribution tree, manufacturing instructions for customizing the physical product and according to the plurality of variable product attributes are generated. The manufacturing instructions may be transmitted to a product customization server to cause a manufacturing entity to proceed with generating a customized product based on the manufacturing instructions.” [Par 128-129] “In some embodiments, the product option set contains the logic to enumerate each customizable option in a manner that presents a complete user interface to change the parametric product instructions… The instructions for manufacturing a customized product are usually parametric. The parameters include the size of the customized product (this can be multi-dimensional, and include width, height, depth). The parameters may also relate to human sizes or ages. The parameters may also be custom and based on biometric information.”)
Claim 4. Beaver teaches receiving a request to adjust the parametric fit model; ([Par 197] “In some embodiments, to be able to collaborate on an interactive design with a graphics designer, a customer may request a collaboration session between the customer and the designer and supported by a collaboration platform. Once the session is established, the customer and the designer may share access to product description data that are associated with the interactive design and that include corresponding key-value pairs.”) based on, at least in part, a plurality of fit parameters of the parametric fit model, generating a third graphical representation of the parametric physical product; generating a fourth user interface and displaying, on a user computer display device, the third user interface comprising at least the fourth graphical representation of the parametric physical product; receiving, via the fourth user interface, a plurality of user adjustment parameters for improving a clothing fit of the parametric physical product; based on the plurality of user adjustment parameters and the plurality of fit parameters of the parametric physical product, generating, for the custom product, an adjusted parametric fit model having a plurality of new fit model parameters; wherein a new fit model parameter, of the plurality of new fit model parameters of the adjusted parametric fit model, is represented as an adjusted fit key-value pair; sending the adjusted parametric fit model to the manufacturer to cause the manufacturer to produce the parametric physical product based on a plurality of adjusted fit model parameters of the parametric fit model.([Par 309-313] “In the description below, it is assumed that the steps described in FIG. 7B have been already performed, and updated product description data have been generated by updating the product description data using the modifications received from the particular designer. It is possible, however, that the customer modifies the product description data before the particular designer does. Nevertheless, for the simplicity of the explanation, it is assumed that the particular designer has already provided his modifications to the product description data and that the modifications have been used to generate the updated product description data. In some embodiments, in response to receiving an editing request from a customer interface generated on a customer device, to edit the interactive digital design, a collaboration computer grants the customer access to the updated product description data as an editor. Furthermore, the collaboration computer transmits to the customer device associated with the customer, the updated product description data for rendering the interactive digital design in the user interface executing on the user device of the customer. As the customer modifies the interactive design, new modifications are generated and the key-value pairs corresponding to the updated product description data are modified, edited, and then saved. Upon receiving new modifications to the updated product description data from the user interface of the customer, the collaboration computer automatically generates a second updated product description data by updating the updated product description data based on the new modifications and propagates the second updated product description data to the user interface of the customer and to a particular user interface of the particular designer to cause the interfaces to update their displays of the interactive digital design based on the second updated product description data.” [Par 80] “Digital designs may be transmitted from a product collaboration platform to manufacturing servers, or manufacturing entities, that may use the received digital designs to manufacture products either digitally or physically. The manufactured product may, in turn, be delivered to recipients.” [Par 186] “Based on, at least in part, the plurality of global-key-values pairs, an ownership-attribution tree is constructed. Based on, at least in part, the ownership-attribution tree, manufacturing instructions for customizing the physical product and according to the plurality of variable product attributes are generated. The manufacturing instructions may be transmitted to a product customization server to cause a manufacturing entity to proceed with generating a customized product based on the manufacturing instructions.” [Par 128-129] “In some embodiments, the product option set contains the logic to enumerate each customizable option in a manner that presents a complete user interface to change the parametric product instructions… The instructions for manufacturing a customized product are usually parametric. The parameters include the size of the customized product (this can be multi-dimensional, and include width, height, depth). The parameters may also relate to human sizes or ages. The parameters may also be custom and based on biometric information.”)
Claim 5. Beaver teaches wherein the first user interface displays, on the computer display device, the first graphical representation of the custom product as a visualization of the parametric model of the custom product showing how the parametric physical product, manufactured based on the plurality of fit model parameters using a plurality of fit key-values of the parametric fit model, ([Par 145-147] “ In some embodiments, a product option framework is configured to generate a product option framework user interface. Accordingly, each product options set is associated with logic and code to build a user interface element for each parametric product option. Furthermore, each product options set contains style hints so that each user interface element may be artfully placed to produce a high quality user experience…. The user interface elements may include a design view, a color editor, a font editor, a size selector, a texture selector, a text editor, a fabric swatch selector, a product real view, and the like. In some embodiments, a product options framework cooperates with a user product renderer that may be implemented in, for example, a RealView server 16A. The user product renderer may be configured to render views of a custom product as though it is already manufactured. Typically, it uses a product option set of key-values as input. It creates one or more run-time assets using computational photography of the manufactured product.”) ([Par 132-133] “In some embodiments, a product option may be represented as a key-value pair. The key-value pair is a label that may span individual products and represent a class of products. The keys of pairs may include a material type, a color, a size, and the like. The value in a key-value pair is a specific discrete or continuous value that sets a manufacturing instruction. Examples of discrete (enumerated) values may include a discrete type of fabric such as cotton, cotton-polyester blend, silk, and the like. The discrete values may also include specific colors, such as white, navy, black, and the like.”)
Donelly makes obvious wherein the system shows how the product fits the user having the user-specific data; ([Par 18] “A system and method for implementing a “virtual fitting room” is disclosed. The virtual fitting room of the present invention, hereinafter referred to as the software, is a software program that will, among other features, provide an actual analysis of how a garment will fit a customer, and which will provide a realistic visual representation of the garment's fit on the customer.”)
Claim 6. Beaver teaches wherein the first user interface further displays one or more regions of the visualization of the parametric model of the custom product; wherein a region of the one or more regions of the visualization is adjustable using one or more functionalities of the first user interface; wherein the one or more functionalities of the first user interface allow adjusting a clothing fit of the parametric physical product to the user having the user-specific data. ([Par 145-147] “ In some embodiments, a product option framework is configured to generate a product option framework user interface. Accordingly, each product options set is associated with logic and code to build a user interface element for each parametric product option. Furthermore, each product options set contains style hints so that each user interface element may be artfully placed to produce a high quality user experience…. The user interface elements may include a design view, a color editor, a font editor, a size selector, a texture selector, a text editor, a fabric swatch selector, a product real view, and the like. In some embodiments, a product options framework cooperates with a user product renderer that may be implemented in, for example, a RealView server 16A. The user product renderer may be configured to render views of a custom product as though it is already manufactured. Typically, it uses a product option set of key-values as input. It creates one or more run-time assets using computational photography of the manufactured product.” [Par 349] “An interactive design can be defined as the subset of the custom product attributes that may be altered, added, manufactured, or embellished for the purpose of custom product manufacturing. While the product attributes are product specific, they may include the substrate color or material choice for an area of the product, the trim material or color of a product, printed, engraved, or embroidered embellishments, and/or color palettes applied to the design.” [Par 371] “Collaboration components 106 may include a component that is used to store a representation of graphical user interface elements (not shown) associated with design areas of a customizable product. Design areas may include one or more areas defined within the customized product that a user may customize and/or modify. For example, if platform 100 offers customizable mugs, then design areas may include an area for showing an outside surface of the mug, an area for showing an inside surface of the mug, and an area for showing a surface of the mug handle. A product description for the design may specify that a user may modify the appearance of each of the surfaces separately, or that the user may group the surfaces and modify the group.”)
Claim 7. Beaver teaches receiving, from the first user interface, a selection of a region, from the one or more regions, and an indication that the custom product should have either a looser fit or a tighter fit. (Par 145-147] “ In some embodiments, a product option framework is configured to generate a product option framework user interface. Accordingly, each product options set is associated with logic and code to build a user interface element for each parametric product option. Furthermore, each product options set contains style hints so that each user interface element may be artfully placed to produce a high quality user experience…. The user interface elements may include a design view, … a size selector, ... product real view, and the like. In some embodiments, a product options framework cooperates with a user product renderer that may be implemented in, for example, a RealView server 16A. The user product renderer may be configured to render views of a custom product as though it is already manufactured. Typically, it uses a product option set of key-values as input. It creates one or more run-time assets using computational photography of the manufactured product.” [Par 371] “Collaboration components 106 may include a component that is used to store a representation of graphical user interface elements (not shown) associated with design areas of a customizable product. Design areas may include one or more areas defined within the customized product that a user may customize and/or modify. For example, if platform 100 offers customizable mugs, then design areas may include an area for showing an outside surface of the mug, an area for showing an inside surface of the mug, and an area for showing a surface of the mug handle. A product description for the design may specify that a user may modify the appearance of each of the surfaces separately, or that the user may group the surfaces and modify the group.”[Examiner’s note: a “size selector” menu option that allows for the selection of clothing sizes allows for the selection of clothes that are looser or tighter, i.e. going down a size for tighter and up a size for looser])
Claims 8-14. The elements of claims 8-14 are substantially the same as those of claims 1-7. Therefore, the elements of claims 8-14 are rejected due to the same reasons as outlined above for claims 1-7. Further, Beaver makes obvious the additional elements of “A non-transitory computer-readable medium storing one or more instructions, which, when executed by one or more processors, cause the one or more processors to perform:…” ([Par 167] “FIG. 2 is a block diagram showing an example of a role-based collaboration platform 1. In the example depicted in FIG. 2, a computer collaboration system 100 includes a user profiles database 102, a global-key-values database 103, a product data definitions database 104, an attribution trees database 105, collaboration components 106, a product options framework 110, an attribute engine 108, one or more processors 120, one or more memory units 122, and one or more frameworks 129-136.”).
Claim 15-20. The elements of claims 15-20 are substantially the same as those of claims 1-6. Therefore, the elements of claims 15-20 are rejected due to the same reasons as outlined above for claims 1-6. Further, Beaver makes obvious the additional elements of “A custom product computer system generator comprising: a memory unit; one or more processors; and a custom product computer storing one or more instructions, which, when executed by one or more processors, cause the one or more processors to perform:” ([Par 167] “FIG. 2 is a block diagram showing an example of a role-based collaboration platform 1. In the example depicted in FIG. 2, a computer collaboration system 100 includes a user profiles database 102, a global-key-values database 103, a product data definitions database 104, an attribution trees database 105, collaboration components 106, a product options framework 110, an attribute engine 108, one or more processors 120, one or more memory units 122, and one or more frameworks 129-136.”).
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Michael P Mirabito whose telephone number is (703)756-1494. The examiner can normally be reached M-F 10:30 am - 6:30 pm.
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/M.P.M./Examiner, Art Unit 2187
/EMERSON C PUENTE/Supervisory Patent Examiner, Art Unit 2187
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