DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1 – 20 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Independent claim 11, representative of claim 1, in part is directed toward a statutory category of invention, the claim appears to be directed toward a judicial exception namely an abstract idea. Claim 1 recites invention directed to
Generating webpage style profile by analyzing visual properties of a target webpage. Schema of source advertising object is read, subsequent to which a display advertising object aligned with the said display-object for webpage is generated. When a user interacts with said display-object, its properties is analyzed to create a display-object-style profile. A blueprint for a personalized landing-page is generated based on the created display-object-style profile, and said personalized landing page is constructed according to said blueprint, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of organizing certain methods of human activity related to advertising, marketing or sales activities or behaviors but for the recitation of generic computer components. Accordingly, the claim recites an abstract idea.
Next, the aforementioned claims recite additional functional elements that are associated with the judicial exception, including: generating using artificial intelligence, according to said webpage style profile and schema, adaptation commands for said source CHA to generate a display CHA visually aligned with said target webpage. Not only do these features fail to integrate the abstract idea into a practical application (see below), but it can also reasonably be seen as the conventional applying of well-known machine learning concepts to generate a display CHA visually aligned with said target webpage to implement the abstract idea on a computer, and merely uses a computer as a tool to perform the abstract idea. See MPEP 2106.05(f).
Represented claim 1, which do recite statutory categories (machine, product of manufacture, for example), the same analysis as above applies to these claims since the method steps are the same. However, the judicial exception is not integrated into a practical application. These claims add the generic computer components (additional elements) of a system comprising one or more hardware processors and a memory (claim 1) to perform the method addressed above.
The processor and memory are recited at a high-level of generality such that they amount to no more than mere instructions to apply the exception using a generic computer component. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element of the processor and memory amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claims are not patent eligible.
When taken as an ordered combination, nothing is added that is not already present when the elements are taken individually. When viewed as a whole, the marketing activities amount to instructions applied using generic computer components.
As for dependent claims 2 – 10 and 12 - 20, these claims recite limitations that further define the same abstract idea of applying artificial intelligence support to ensure said adaptation commands are implemented according to brand consistency rules. Storing, managing data and command signals between plurality of devices, determining changes required to visually align said source CHA with said target webpage by reading said schema of said source CHA; and detecting said user interaction with said display CHA; defining how required changes to visually align said source CHA with said target webpage; defining that a predefined template with at least one of: said webpage style profile and said display CHA style profile for assembling a structured prompt by populating; defining data defined by schema and blueprint, performing color analysis of visible elements of determine color pallet, font families, sizes to establish a typographic hierarchy, and defining maintaining multiple states of said source CHA, said multiple states comprising its original state, its live adapted state, and a history of previous states, thereby enabling A/B testing between different adaptations, as drafted, is a process that, under its broadest reasonable interpretation, covers performance of organizing certain methods of human activity related to advertising, marketing or sales activities or behaviors but for the recitation of generic computer components. Accordingly, the claim recites an abstract idea.
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.
Claims 1 – 20 are rejected under 35 U.S.C. 103 as being unpatentable over Website Learners YouTube Video “How to Make a Website – Wix Tutorial for Beginners” hereinafter to as Website-Learners in view of Pinel et al. US Publication 2020/0167832 and Google.com published article “Introduction to structured data markup in Google Search” hereinafter referred to as Google.
Regarding claim 11 and representative claim 1, Website-Learners teaches a website building system (WBS) comprising:
at least one processor (Website-Learners, www.wix.com);
a website building system (WBS) running on said at least one processor (Website-Learners, www.wix.com);
a site generation system (Website-Learners, www.wix.com) configured to construct said personalized landing page according to said blueprint (Website-Learners, Choose a design for your website; Add you content to the design; Publish the site on the internet) [ref1, pages 33 – 35].
Website-Learners does not explicitly teach adaptive advertisement integration with the webpage. However, Website-Learners teaches Wix.com appends advertisement on the webpage when its associated user selects Free Plan to publish their website [see at least “Remove Ads on your site”, page 41]. However, Pinel teaches system and method for adaptive advertisement integration with webpages (Pinel, The present invention relates generally to the field of designing advertisement displays to be distributed to potential customer devices (for example, smart phones, laptops) over communication networks.) [Pinel, 0001].
Therefore, at the time of filing, it would have been obvious to one of ordinary skill in the art to modify Website-Learners by adopting teachings of Pinel to enable marketers create thousands of customized ads on the fly, without having their creative department create every combination.
Website-Learners in view of Pinel teaches system and method for adaptive advertisement integration with webpages [Pinel, 0001], said system and method comprising:
analyzing visual properties of a target webpage to create a webpage style profile (Pinel, Some embodiments of the present invention may include one, or more, of the following features, characteristics and/or advantages: …. (vi) actually analyzes the background image for possible overlay regions; (vii) uses harmonic color schemes to recolor ad elements (including images); (viii) considers color as one of the main drivers of user attention ….) [Pinel, 0065];
Website-Learners in view of Pinel does not teach reading of schema of sources advertising object. However, Google teaches Google Search works hard to understand the content of a page. Google further teaches adding structured data can enable search results that are more engaging to user [Google, page 1]. In addition Google teaches that they use structured data that it finds on the web to understand the content of the page, as well as to gather information about the web and the world in general, such as information about the people, books, or companies that are included in the markup [Google, page 1, 2].
Therefore, at the time of filing, it would have been obvious to one of ordinary skill in the art to modify Website-Learners in view of Pinel by adopting teachings of Google to read schema of the web content to understand the content of the page, as well as to gather information about the web.
Website-Learners in view of Pinel and Google teaches system and method further comprising:
reading the schema of a source chameleon advertisement object (CHA) [Google, page 1, 2];
generating using artificial intelligence, according to said webpage style profile and schema, adaptation commands for said source CHA to generate a display CHA visually aligned with said target webpage (Pinel, Some embodiments of the present invention may include one, or more, of the following features, characteristics and/or advantages: …. (vi) actually analyzes the background image for possible overlay regions; (vii) uses harmonic color schemes to recolor ad elements (including images); (viii) considers color as one of the main drivers of user attention ….) [Pinel, 0065]; and
in response to a user interaction with said display CHA, analyzing properties of said display CHA to create a display CHA style profile (Google, Because the structured data labels each individual element of the recipe, users can search for your recipe by ingredient, calorie count, cook time, and so on.) [Google, page 3]; and
generating using artificial intelligence, a blueprint for a personalized landing page according to said display CHA style profile (Pinel, (ii) determining, by machine logic, a set of layout(s) for the plurality of visual elements; (iii) determining, by machine logic, a set of color scheme(s) including a plurality of colors, where each color scheme has a color harmony value that is relatively large;) [Pinel, 0007]; and
constructing said personalized landing page according to said blueprint (Pinel, (iv) for each given layout of the set of layout(s) and each given color scheme of the set of color scheme(s ), coloring, by machine logic, the given layout according to the given color scheme to generate a set of colored first advertisement version(s);) [Pinel, 0007].
Regarding claim 12 and representative claim 2, as combined and under the same rationale as above, Website-Learners in view of Pinel and Google teaches system and method, wherein said generating said display CHA further comprises providing artificial intelligence support within said source CHA to ensure said adaptation commands are implemented according to brand consistency rules (Pinel, (iv) for each given layout of the set of layout(s) and each given color scheme of the set of color scheme(s ), coloring, by machine logic, the given layout according to the given color scheme to generate a set of colored first advertisement version(s);) [Pinel, 0007].
Regarding claim 13 and representative claim 3, as combined and under the same rationale as above, Website-Learners in view of Pinel and Google teaches system and method further comprising:
managing data and command signals between said source CHA, said target webpage, and said display CHA (Pinel, Processing proceeds to operation S285, where test mod 312 tests the colored ad version(s) (in this simple example, the yellow-red version) using a click through rate (CTR) predictor (not separately shown in FIG. 3). The CTR predictor is trained and re-trained using historical data, to test colored ad version(s). As discussed in the following sub-section, this testing may additionally, or alternatively, include A/B testing.) [Pinel, 0049];
storing and managing data defining said source CHA (Pinel, Each colored ad version will have a different color combination and is stored in ad version data store 310.) [Pinel, 0047]; and
determining changes required to visually align said source CHA with said target webpage (Pinel, The live audience data from the ad exchange is fed into a DCO platform that serves as the decision criteria for restructuring the creative. This data can be augmented over time using personality insights, text analytics and weather Apis from IBM Watson thereby increasing the CTR and conversion rates of display advertising. The auto learning capabilities of Watson and algorithmic improvements over time aid in enhancing the data which can then be used to optimize creative choices according to campaign objectives .... The marketer can create thousands of customized ads on the fly, without having their creative department create every combination.") [Pinel, 0006].
Regarding claim 14 and representative claim 4, as combined and under the same rationale as above, Website-Learners in view of Pinel and Google teaches system and method, wherein said managing data and command signals comprises:
reading said schema of said source CHA (Google teaches Google Search works hard to understand the content of a page. Google further teaches adding structured data can enable search results that are more engaging to user [Google, page 1]. In addition Google teaches that they use structured data that it finds on the web to understand the content of the page, as well as to gather information about the web and the world in general, such as information about the people, books, or companies that are included in the markup) [Google, page 1, 2]; and
detecting said user interaction with said display CHA (Pinel, Processing proceeds to operation S510 where CTR statistics for the served, selected advertisements are collected based on "click throughs" of the selected advertisements by the potential customers to whom the selected advertisements were served.) [Pinel, 0063].
Regarding claim 15 and representative claim 5, as combined and under the same rationale as above, Website-Learners in view of Pinel and Google teaches system and method, wherein said determining changes required to visually align said source CHA with said target webpage comprises:
retrieving attributes of said target webpage from a local content management system;
analyzing at least one of: said target webpage and said display CHA to determine said webpage style profile and said display CHA style profile accordingly(Pinel, Some embodiments of the present invention may include one, or more, of the following features, characteristics and/or advantages: …. (vi) actually analyzes the background image for possible overlay regions; (vii) uses harmonic color schemes to recolor ad elements (including images); (viii) considers color as one of the main drivers of user attention ….) [Pinel, 0065];
performing an optimization calculation that reduces visual discrepancy between said display CHA and said target webpage by determining a set of modifications for both while preserving each party's brand identity (Pinel, (ii) determining, by machine logic, a set of layout(s) for the plurality of visual elements; (iii) determining, by machine logic, a set of color scheme(s) including a plurality of colors, where each color scheme has a color harmony value that is relatively large;) [Pinel, 0007]; and
generating a prompt according to at least one of: said webpage style profile and said display CHA style profile (Website-Learners, page 21].
Regarding claim 16 and representative claim 6, as combined and under the same rationale as above, Website-Learners in view of Pinel and Google teaches system and method, wherein said schema comprises a set of protected brand elements and a list of modifiable elements, and wherein said generating adaptation commands is further based on said protected brand elements and said list of modifiable elements [Website-Learners, page 21].
Regarding claim 17 and representative claim 7, as combined and under the same rationale as above, Website-Learners in view of Pinel and Google teaches system and method, wherein said generating a prompt comprises:
assembling a structured prompt by populating a predefined template with at least one of: said webpage style profile and said display CHA style profile (Pinel, Using machine logic that determines color harmony values, select best fitting harmonic template (that is, predetermined combination of colors that exhibit color harmony with each other) for the background image-which is to say that the colors of the harmonic template will have good color harmony with the background image as well as with each other. In some embodiments, more than one harmonic scheme is selected, which results in more generated versions of the ad.) [Pinel, 0058, also see 0006]; and
receiving and parsing an output comprising said adaptation commands [Pinel, 0058, also see 0006].
Regarding claim 18 and representative claim 8, as combined and under the same rationale as above, Website-Learners in view of Pinel and Google teaches system and method, wherein said generating a blueprint comprises generating a machine-readable instruction set comprising a definition of a content structure and a set of associated styling rules for said personalized landing page (Pinel, (ii) determining, by machine logic, a set of layout(s) for the plurality of visual elements; (iii) determining, by machine logic, a set of color scheme(s) including a plurality of colors, where each color scheme has a color harmony value that is relatively large;) [Pinel, 0007].
Regarding claim 19 and representative claim 9, as combined and under the same rationale as above, Website-Learners in view of Pinel and Google teaches system and method, wherein said analyzing comprises at least one of:
deconstructing foundational code of said target webpage to parse its structural hierarchy;
performing a color analysis of visible elements to determine a dominant color palette; and
conducting a typography analysis to identify font families, sizes, and weights to establish a typographic hierarchy
(Pinel, (ii) determining, by machine logic, a set of layout(s) for the plurality of visual elements; (iii) determining, by machine logic, a set of color scheme(s) including a plurality of colors, where each color scheme has a color harmony value that is relatively large; (1v) for each given layout of the set of layout(s) and each given color scheme of the set of color scheme(s ), coloring, by machine logic, the given layout according to the given color scheme to generate a set of colored first advertisement version(s);) [Pinel, 0007].
Regarding claim 20 and representative claim 10, as combined and under the same rationale as above, Website-Learners in view of Pinel and Google teaches system and method, wherein said storing and managing data further comprises maintaining multiple states of said source CHA, said multiple states comprising its original state, its live adapted state, and a history of previous states, thereby enabling A/B testing between different adaptations (Pinel, Each colored ad version will have a different color combination and is stored in ad version data store 310.) [Pinel, 0047].
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Naresh Vig whose telephone number is (571)272-6810. The examiner can normally be reached Mon-Fri 06:30a - 04:00p.
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/NARESH VIG/Primary Examiner, Art Unit 3622
August 19, 2026
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