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 .
Status of Claims
This office action is in response to the RCE filed on 7/6/2026.
Claims 1 and 9 have been amended.
Claims 8 has been canceled.
Claims 1, 2, 6, 7, 9-10, 14, and 15 are pending and have been examined.
Priority
Acknowledgment is made of applicant’s claim for foreign priority under 35 U.S.C. 119 (a)-(d). The certified copy has been filed in parent Application No. EP 24175419 filed on 5/13/2024.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1, 2, 6, 7, 9-10, 14, and 15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1: Claims 1, 2, 6, 7 are directed to a method. Claims 9, 10, 14 and 15 are directed to a system. Thus, on their face they fall within the four statutory categories of patentable subject matter.
Step 2A prong 1:
Claims 1 and 9 recite virtually identical claim limitations. Claim 1 will be used as representative for the analysis. Each claims additional elements will be addressed individually. The following limitations, when considered individually and as an ordered combination, are merely descriptive of abstract concepts:
Claims 1 and 9:
transmitting an access address to the public display, the access address being associated with an input entity for inputting user-input text comments about a predetermined merchandise;
displaying, by the public display, the access address thereon;
receiving, from a user via the input entity, a user-input text comment;
in response to receipt of the user-input text comment from the user via the input entity, performing a filtering operation on the user-input text comment so as to obtain a filtered input string, wherein the filtering operation includes applying the user-input text comment to a filtering model that is pre-trained to filter out parts of the user-input text comment deemed not suitable for use in generating a user-related advertisement and to obtain the filtered input string;
feeding the filtered input string as an input into a generative model, so as to obtain an advertising text as an output of the generative model;
generating a user-related advertisement for the predetermined merchandise based on at least the advertising text by applying the filtered input string to the generative model, and transmitting the user-related advertisement to the public display; and
displaying, by the public display, the user-related advertisement;
wherein the filtering operation further includes:
a partition mechanism of the filtering model splitting the user- input comment into a plurality of segments,
a sentiment mechanism of the filtering model determining that a first segment of the plurality of segments is associated with a negative sentiment, and
discarding the first segment associated with the negative sentiment;
the sentiment mechanism determining that a second segment of the plurality of segments is associated with a positive sentiment and providing the second segment to a relevance detection mechanism of the filtering model;
the relevance detection mechanism determining that the second segment is related to the user experience of the predetermined merchandise; and
upon determining that the second segment is related to the user experience of the predetermined merchandise, the filtering model outputting the second segment as part of the filtered input string;
wherein the applying the filtered input string to the generative model includes automatically inputting into the generative model the filtered input string and a prompt to prepare a poem or prose that includes the filtered input string in the advertising text
wherein the method further includes providing a reward token to the user after generating the user-related advertisement based on the advertising text, the reward token being able to be redeemed for purchasing the merchandise associated with the user-related advertisement.
The following dependent claim limitations, when considered individually and as an ordered combination, are merely further descriptive of abstract concepts:
Claims 2, 10:
further comprising: in response to receipt of the access address, encoding the access address in a two-dimensional code readable by the user, and further displaying the code;
Claims 6, 14:
further comprising a step of receiving a user multimedia from the user via the input entity,
wherein the generating of the user-related advertisement is further based on the user multimedia
Claims 7, 15:
storing a merchandise multimedia for the predetermined merchandise, wherein the generating of the user-related advertisement is further based on the merchandise multimedia.
The claims provide a manner of displaying an address where a user can access an input mechanism to provide comments about predetermined merchandise. Upon receiving the comments, the comments are filtered and used to generate an advertisement for the predetermined merchandise. Thus, when considered individually and as an ordered combination, the claims embody certain methods of organizing human activity. Specifically, such activity is in the form of commercial interactions (in the form of advertising, marketing or sales activities or behaviors).
Step 2A prong 2: This judicial exception is not integrated into a practical application. The claims recite the following additional elements: communication unit (claim 1, 9); server (claim 1, 6, 7, 9, 14, 15); processor of the server (claims 1, 9); wireless network (claims 1, 9); link (claim 1, 2, 9, 10); public display device (claim 1, 2, 9, 10); processor of the public display device controlling a display of the public display device to display a link (claims 1, 9); input website (claim 1, 6, 9, 14); field of an input website (claim 1, 9); user device (claim 1, 2, 6, 9, 10, 14); wherein the two-dimensional code is a Quick Response (QR) code (claims 2, 10); filtering neural network model (claims 1, 9); generative neural network model (claim 1, 9); advertising text file (claim 1, 9), multimedia file (6, 7, 14, 15); database (7, 15);
The server, processor of the server, wireless network, communication unit, public display device, user device, processor of the public display device controlling a display of the public display device to display a link, and database are recited at a high level of generality. They are merely used to “apply it” (the abstract idea) using generic computing devices (paragraphs [0021], [0022], [0023], [0027], [0028], [0034]). The generic computing devices are merely used to send and receive data (transmitting, receiving, providing), processing data (displaying, feeding, filtering, generating, encoding, determining, discarding, splitting, applying), and storing data (storing). Nothing in the claims improves upon computer technology, database technology, or a technical field (See MPEP 2106.05(f)).
The link, input website, advertising text file, field of an input website, and multimedia file merely provide a general link to a particular technological environment. The link merely provides an address in an online environment as opposed to a physical address where the user can provide their comments about the merchandise. The website merely provides that the comments are obtained online as opposed to using pen and paper. Similarly, the input field on the website is little more than entering information in a website environment as opposed to providing the information in any other manner. The advertising text file and multimedia file merely provide the providing information is in an electronic computing environment as opposed to receiving the text or multimedia in print, such as being written down on paper (see MPEP 2106.05 (h)).
The high level use of a quick response code to provide the link does not go beyond the “apply it” level of implementation. Nothing in the claims improves QR code technology or a technical field. It is merely used to provide the particular link of the invention as opposed to any other link (See MPEP 2106.05(f)).
The generative neural network model and filtering neural network model is recited at a high level of generality. Nothing in the claims improves upon neural network technology or a technical field. The neural networks are merely used to process the particular data of the invention. Thus, the high level use of a neural network is considered generic computer implementation and does not go beyond the “apply it” level.
Accordingly, when considered both individually and as an ordered combination, the additional elements do not impose any meaningful limits on practicing the abstract idea.
Step 2B: The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception. Similarly, as above with regard to practical application, the additional elements when considered both individually and as an ordered combination, do not provide an inventive concept as they merely provide generic computing components used as a tool to implement the abstract idea or provide a general link to a particular technological environment or field of use (i.e. online, on a computer).
As a result, the claims are not patent eligible.
Regarding Prior Art:
While each limitation may be found individually in prior art, the examiner was unable to find a reasonable combination of references to teach each and every limitation in the context of the claimed invention. As a result, such rejection has been withdrawn.
Soon-Shiong (US 2014/0129393) is considered the closest prior art of record. Soon-Shiong teaches an electronic billboard that displays advertisements in a public place. The display includes QR codes for accessing purchasable products and at least providing comments on the products.
Boyce et al (Us 2020/0327585) teaches filtering reviews and providing them on a public display. The advertisement provided can include reviews and a rating. For example, “Service was excellent. Will definitely return.”
Gee et al (US 2022/0194401) teaches using a neural network to provide personalized recommendations to users. Resultant advertisements, predictions, or recommendations may include direct quotes from users who supplied the reviews and may include information, e.g., images, provided by these users. In one specific example, an advertisement for a highly rated tire may be created and include quotes from a specific person who reviewed the tire, as well as an image from the person of the actual tire from the person's vehicle that the person reviewed.
Krishnamoorthy (US 2012/0059848) teaches various techniques are contemplated in relation to generating advertisements. For example, in some embodiments, a whole review may be used as or re-formatted as an advertisement. In some embodiments, positive or interesting points only from a review are selected and used in or converted to an advertisement.
Longano (US 2020/0364746) teaches storing one or more of product advertisements which may include one or more of a product image, a product price, and a product review in a database.
Mysen et al (US 2018/0285953) generally teaches storing advertisements including images of products and product reviews
Li (US 2016/0307227) generally teaches capturing images of users using products, uploading reviews, and providing advertisements including the images and product review
Carlisle et al (US 2018/0349485) teaches using artificial intelligence to filter out negative reviews. Thus, all negative content can be filtered out, and never shown to the user, such that the user only reviews positive content in his or her search results and/or content feeds.
Chung (US 2013/0262198) teaches sending a reward or coupon to the mobile device of a user.
Response to Arguments
The examiner has considered but does not find persuasive applicant’s arguments regarding rejections under 35 USC 101.
The claims are very clearly directed to certain methods of organizing activity as they focus on generating an providing advertising as outlined in the rejection above.
With regard to the use neural networks, all of the operations performed using the neural networks are merely part of the abstract idea. The neural networks are recited at a high level of generality. They are claimed by what they do rather than how they do it. Nothing in the claims describes an improvement to neural network technology or a technical field. Thus, they do not go beyond the “apply it” level of implementation. The computing devices recited in the claims are also generic computing devices as discussed above.
Similarly, as discussed above with regard to practical application, the additional elements do not provide significantly more as outlined in the rejection above. Applicant merely recites the use of the neural network. None of the claims recite anything remotely close to an improvement to neural network technology. They are little more than “do it” with a neural network. Further, providing a user with a reward token, such as a voucher or coupon for example, is merely part of the abstract idea and clearly in now way improves technology or a technical field.
Lack of prior art does not render the claims any less abstract. For example, in Ultramercial, Inc. v. Hulu, LLC, 772 F.3d 709, 714‐15 (Fed. Cir. 2014) (“Ultramercial”), the court found claims to the use of attention to digital advertising as a currency to be directed to an abstract idea despite the patentee’s arguments that the concept was “new”. Therefore, simply because the examiner has not applied prior art to the claims does not render the claims patent eligible.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to CHRISTOPHER STROUD whose telephone number is (571)272-7930. The examiner can normally be reached Mon. - Fri. 9AM-5PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Waseem Ashraff can be reached at (571) 270-3948. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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CHRISTOPHER STROUD
Primary Examiner
Art Unit 3621
/CHRISTOPHER STROUD/ Primary Examiner, Art Unit 3621
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