DETAILED ACTION
Notice of Pre-AIA or AIA Status
01. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Preliminary Amendment
02. The present Office Action is based upon the original patent application filed on 05/07/2024 as modified by the preliminary amendment filed on 07/16/2025. Claims 11 – 22 and 33 – 40 are now pending in the present application.
Information Disclosure Statement
03. The information disclosure statement (IDS) filed on 07/16/2024, 07/16/2024 has been considered by the examiner and made of record in the application file.
Claim Objections
04. Claim 19 is objected to because it depends on itself. Based on the claim language present, it is believed that claim 19 was intended to depend on claim 18, and has been treated as such for the remainder of the office action.
Drawings
05. The drawings were received on 05/07/2024, 07/16/2025. These drawings are accepted.
Claim Rejections - 35 USC § 101
06. 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.
07. Claims 11 – 22 and 33 – 40 are rejected under 35 U.S.C. 101 because the claims are directed to an abstract idea without significantly more. The claims are directed to transmitting data, which amounts to an abstract idea, as explained in detail below. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional computer elements, which are recited at a high level of generality, provide conventional computer functions that do not add meaningful limits to practicing the abstract idea.
Step 1: The claim (claim 11) recites a method which recites a series of acts for determining a citation for output content. Thus, the claim is directed to a process, which is one of the statutory categories of invention. Claim 33 recites a system comprising control circuitry that determines a citation for output content. Thus, the claim is directed to a machine, which is one of the statutory categories of invention.
Step 2A, prong one: The claim (claim 11) recites the limitations of “transmitting” data. Nothing in the claim elements precludes the step from practically being performed in the human mind. The three “transmitting” steps in the claim encompasses a mental process, in that it is simply the organization and/or sending of data. For example, a person can store data in their mind, or perform searches in order to obtain data through a search engine.
If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claims recites an abstract idea.
Step 2A, prong two: The judicial exception is not integrated into a practical application. In particular, the claim includes the additional limitations of: “receiving” a citation.
The claim (claim 11) recites the additional element of “receiving, from the citation server, a citation to…” which represents mere data gathering that is necessary for use of the recited judicial exception and is recited at a high level of generality. Limitation (a) in the claim is thus insignificant extra-solution activity. This claim limitation also recites “filtering of content items in a contact database”. This limitation represents extra solution activity because it is a mere nominal or tangential addition to the claim. See MPEP 2106.05(g), discussing limitations that the Federal Circuit has considered to be insignificant extra-solution activity, for instance the step of printing a menu that was generated through an abstract process in Apple, Inc. v. Ameranth, Inc., 842 F.3d 1229, 1241-42 (Fed. Cir. 2016) and the mere generic presentation of collected and analyzed data in Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354 (Fed. Cir. 2016).
Even when viewed in combination, the additional elements in this claim do no more than perform the process on generic computing components. This does not provide an improvement to the computers and other technology that are recited in the claim. Thus this claim cannon improve computer functionality or other technology.
Step 2B: As discussed previously with respect to Step 2A prong two, the controller in the claim amounts to no more than mere instructions to apply the exception using a generic computer component. The same analysis applies here in 2B, i.e., mere instructions to apply an exception using a generic computer component cannot integrate a judicial exception into a practical application at Step 2A or provide an inventive concept in Step 2B. The claims do not include additional elements that are sufficient to amount to significantly more than the abstract idea, but are instead limited to appending well-understood, routine, and conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception (abstract idea).
In this instance, the claims include that the text prompt embedding is based on a text prompt used to generate the output content. However, this is generally how a text prompt embedding would be understood to be generated, as it is necessitated on utilizing a text prompt input. Similarly, the claims include the output content embedding being based on the output content, which would be analyzed the same way. The claims also include that the component feature is based on the output content. However, this is merely explaining where data is coming from, as all data generally is understood to have a source or origin.
The same analysis is applied to dependent claims 12 – 22 and 34 – 40, because the limitations recite additional mental processes and/or mathematical calculations and do not integrate into a practical application. Further, they do not include additional elements that amount to significantly more.
Claim 12 includes the additional limitation of determining a similarity between the base content item and the output content. However, this is merely a mental association, as a person can use their mind to determine how similar things are. This can therefore be done as an evaluation or judgment.
Claim 13 includes the additional limitation of a similarity score being based on the similarity. A person that can perform the similarity test between two things could reasonably assign a score to the association. This can therefore be done as an evaluation or judgment.
Claim 14 includes the additional limitation of the similarity score being based on a comparison of an area of the content. However, this is the same process a person would perform in their mind, by comparing two things and then making an evaluation or judgment as to what areas are similar.
Claim 15 includes the additional limitation of using a bag of visual words extracted using a scale-invariant feature transform. This is understood to be data gathering, as it is a process that is used to obtain the base content item.
Claim 16 includes the additional limitation of using a threshold similarity criterion to generate a second text prompt that is then fed to a generative ML model to generate output. The base claim already recites a first text prompt, to this is merely performing that process again, albeit based on a threshold. This is a mental process that can be performed by a person, as a person can make a judgment as to when to decide to perform an action again.
Claim 17 includes a similar additional limitation as that found in claim 16, and the same analysis is applied for the limitations found in this claim.
Claim 18 includes the additional limitation of adding a term of exclusion. This is understood to be data gathering. In this instance, a person can determine what criteria, in their mind, to be used to perform searching or the obtaining of data.
Claim 19 includes the additional limitation of processing metadata that then is used to generate the second text prompt. The step of determining metadata is something a person can do mentally, as a person can determine data about data. A person can then mentally decide to user that data to be used as input to a system.
Claim 20 includes the additional limitation of outputting a watermark, and claim 21 also includes the watermark is imperceptible to the human eye. However, this is merely the technological environment in which the judicial exception is applied to, and does not amount to significantly more than the abstract idea.
Claim 22 includes the additional limitation of determining a copyright restriction that is used to generate alternative output content. However, this is merely the technological environment in which the judicial exception is applied to, and does not amount to significantly more than the abstract idea.
Claim Rejections - 35 USC § 102
08. In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
09. The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
10. Claims 11 – 14, 16 – 19, 33 – 36, and 38 – 40 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Dicklin et al. (US PGPub 2025/0103640), hereinafter “Dicklin”.
Consider claim 1, Dicklin discloses a method of determining a citation for output content generated by a trained generative machine learning (ML) system, the method comprising:
transmitting, to a citation server, a text prompt embedding, wherein the text prompt embedding is based on a text prompt used to generate the output content (paragraphs [0031], [0032], [0048], a text prompt is input into an embedding model to generate a query embedding; paragraph [0043] shows an infrastructure, including one or more servers, that are used to store files/documents that are accessed by way of processing the query embedding);
transmitting, to the citation server, an output content embedding, wherein the output content embedding is based on the output content (paragraphs [0054] – [0057], an output is determined, such as one or more documents, which can include one or more embeddings, and can be processed at the servers);
transmitting, to the citation server, a component feature, wherein the component feature is based on the output content (paragraph [0051], [0052], [0055], [0077], the output, such as one or more documents, contains related information, e.g. a component feature, such as document portions and information);
receiving, from the citation server, a citation to an identified base content item, wherein the identification of the base content item is based at least in part on filtering of content items in a content database using the text prompt embedding, the output content embedding, and the component feature (paragraphs [0035], [0080], [0112], [0115], a citation to a particular document is obtained, which can be done by way of processing the inputs to the generative machine learning model. The input can include the text prompt to query embedding, an embedding of an output document, and documents that are found based on processing the other inputs and embeddings. This allows for the generative machine learning model to have all the inputs processed so that one or more documents can be obtained. Additionally, the documents that are obtained are only one or more of the entire database of documents and are thus filtered).
Consider claim 12, and as applied to claim 11 above, Dicklin discloses a method comprising:
determining a similarity between the base content item and the output content (paragraphs [0107], [0125], a similarity is determined between different documents)
causing, based on the similarity between the base content item and the output content, generation of an alternative output content (paragraphs [0122], [0125], one or more documents are obtained, which includes obtaining additional documents based on how well a document is scored for criteria).
Consider claim 13, and as applied to claim 12 above, Dicklin discloses a method comprising:
determining a similarity score based on a similarity between the output content and the identified base content item (paragraphs [0080], [0126], a distance can be determined for the similarity of documents).
Consider claim 14, and as applied to claim 13 above, Dicklin discloses a method comprising:
determining, based on the citation to the base content item, an area of similarity in the output content similar with an area of the base content item, and wherein the causing the generation of the alternative output content comprises altering the area of similarity (paragraphs [0032], [0059], [0080], a portion of a document can be used as a comparison to see if it is similar to either another document or an embedding, which can then cause the system to search for one or more other documents)
Consider claim 16, and as applied to claim 11 above, Dicklin discloses a method comprising:
determining a threshold similarity criterion between the base content item and the output content (paragraphs [0049], [0110], one or more criteria are used to determine the similarity of documents);
causing generation of a second text prompt; feeding the second text prompt to a generative ML model for generating alternative output content (paragraphs [0121] – [0124], additional documents can be searched for by of utilizing one or more additional searches and embeddings).
Consider claim 17, and as applied to claim 11 above, Dicklin discloses a method comprising:
determining a first threshold similarity criterion between the base content item and the output content; based on the first threshold similarity criterion, modifying the output content ((paragraphs [0057], [0078], additional search criteria can be entered by a user in response to a first search processing);
determining a second threshold similarity criterion between the base content item and the output content, wherein the second threshold similarity criterion indicates a higher degree of similarity than the first threshold similarity criterion; based on the second threshold similarity criterion, causing generation of a second text prompt, feeding the second text prompt to a generative ML model for generating alternative output content (paragraphs [0121] – [0124], additional criteria can generated and then supplied to the generative machine learning model in order to generate a second subset of documents).
Consider claim 18, and as applied to claim 17 above, Zeng discloses a method comprising:
the generating of the second text prompt comprises altering the first text prompt by adding a term of exclusion (paragraphs [0101], [0102], different terms can be determined for the input search terms, including assigning different weights to the different search terms or utilizing different search terms).
Consider claim 19, and as applied to claim 11 above, Dicklin discloses a method comprising:
processing metadata associated with the citation to the base content item, wherein the generating the second text prompt uses a result of the processing of the metadata (paragraphs [0046], [0080], [0106], [0139], metadata is associated with the documents, which can be used in order to determine different documents to be returned by the generative machine learning model).
Claims 33 – 36 and 38 – 40 are rejected under the same rational as that provided with respect to claims 11 – 14 and 38 – 40. Each of these claims recites the same limitations, except that either a method or system is claimed.
Claim Rejections - 35 USC § 103
11. In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
12. 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 of this title, 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.
13. Claims 15 and 37 are rejected under 35 U.S.C. 103 as being unpatentable over Dicklin et al. (US PGPub 2025/0103640), hereinafter “Dicklin”, in view of Murray (US PGPub 2021/0279929), hereinafter “Murray”.
Consider claim 15, and as applied to claim 11 above, Dicklin discloses the claimed invention except that a bag of visual words is extracted using a scale-invariant feature transform.
In the same field of endeavor, Murray discloses a method comprising:
the base content item is identified using a bag of visual words extracted using a scale-invariant feature transform (SIFT) process from the output content (paragraph [0002], a scale-invariant feature transform can be used in conjunction with a bag of visual words).
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the extraction and encoding techniques for obtaining data taught by Murray into the utilization of a generative machine learning model taught by Dicklin for the purpose of allowing for initial data, such as a document, to be discovered first, then then performing more advanced computations in order to determine more accurate documents for a user.
Claim 37 is rejected under the same rational as that provided with respect to claim 15. This claim recites the same limitations, except that either a method or system is claimed.
14. Claims 20 – 22 are rejected under 35 U.S.C. 103 as being unpatentable over Dicklin et al. (US PGPub 2025/0103640), hereinafter “Dicklin”, in view of Jalali et al. (US PGPub 2022/0092157), hereinafter “Jalali”.
Consider claim 20, and as applied to claim 11 above, Dicklin discloses the claimed invention except that a watermark is used.
In the same field of endeavor, Jalali discloses a method comprising:
outputting a watermark with the output content, the watermark identifying the base content item (paragraphs [0052], [0056], a digital watermark is applied to data, which is used as a means of identification for the data).
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the watermark taught by Jalali into the utilization of a generative machine learning model taught by Dicklin for the purpose of allowing digital media to be protected, so that the system would not obtain unauthorized data).
Consider claim 21, and as applied to claim 11 above, Dicklin discloses the claimed invention except that a watermark is used.
In the same field of endeavor, Jalali discloses a method comprising:
outputting a watermark on the output content identifying the base content item, wherein the watermark is a machine-detectable watermark imperceptible to humans using a naked eye (paragraphs [0056], [0058], a watermark is applied to data, wherein the watermark is invisible and cannot be visually seen by people).
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the watermark taught by Jalali into the utilization of a generative machine learning model taught by Dicklin for the purpose of allowing digital media to be protected, so that the system would not obtain unauthorized data).
Consider claim 22, and as applied to claim 11 above, Dicklin discloses the claimed invention except that a watermark is used.
In the same field of endeavor, Jalali discloses a method comprising:
determining a copyright restriction based on copyright information identified for the base content item, wherein the causing of the generation of the alternative output content is performed in response to the determining of the copyright restriction (paragraphs [0003], [0052], a copyright is applied to the data, such that the copyright provides for the obtaining of different data that is not copyrighted).
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate the copyright taught by Jalali into the utilization of a generative machine learning model taught by Dicklin for the purpose of allowing digital media to be protected, so that the system would not obtain unauthorized data).
Relevant Prior Art Directed to State of Art
15. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Su et al. (US PGPub 2025/0166135) discloses a method of generating a text prompt embedding that is based on a text prompt in order to generate or locate video content.
Conclusion
16. Any inquiry concerning this communication or earlier communications from the Examiner should be directed to Christopher Raab whose telephone number is (571) 270-1090. The Examiner can normally be reached on Monday-Friday from 9:00am to 5:00pm.
Examiner interviews are available via telephone, in-person, and video conferencing using a USPTO supplied web-based collaboration tool. To schedule an interview, applicant is encouraged to use the USPTO Automated Interview Request (AIR) at http://www.uspto.gov/interviewpractice.
If attempts to reach the Examiner by telephone are unsuccessful, the Examiner’s supervisor, Ajay Bhatia can be reached on (571) 272-3906. The fax phone number for the organization where this application or proceeding is assigned is (571) 273-8300.
Information regarding the status of an application may be obtained from the Patent Application Information Retrieval (PAIR) system. Status information for published applications may be obtained from either Private PAIR or Public PAIR. Status information for unpublished applications is available through Private PAIR only. For more information about the PAIR system, see http://pair-direct.uspto.gov. Should you have questions on access to the Private PAIR system, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free) or 703-305-3028.
/CHRISTOPHER J RAAB/Primary Examiner, Art Unit 2156
May 01, 2026
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