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
Claim 2, 8, and 11-14 have been cancelled by Applicant. Therefore, Claims 1, 3-7, and 9-10 are currently pending in application 18/625,585.
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.
Claim 1 is rejected under 35 U.S.C. 112(b), as being incomplete for omitting essential steps, such omission amounting to a gap between the steps. See MPEP § 2172.01. The omitted steps are: obtaining an initial listing of a real property; and obtaining an address of a real property.
Independent Claim 1 includes the method step of “augmenting the property data by fetching external data from an external data source”; and “generating a listing an updated description for the real property …”. However, while the claim does recite obtaining an image of a real property, the claim fails to recite receiving initial listing data, necessary for updating the description data; and receiving address data, necessary for fetching the external data from an external data source. (See Applicant’s Specification Para 0070-0071)
Dependent Claims 3-7 and 9-10 are rejected for the same reason as independent claim 1 above.
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, 3-7, and 9-10 are rejected under 35 U.S.C. § 101 because the claimed invention is directed to non-statutory subject matter, specifically an abstract idea.
Claims 1, 3-7, and 9-10 are directed to a judicial exception (i.e., abstract idea), without providing a practical application, and without providing significantly more.
Under the 35 U.S.C. §101 subject matter eligibility two-part analysis, Step 1 addresses whether the claim is directed to one of the four statutory categories of invention, i.e., process, machine, manufacture, or composition of matter. See MPEP §2106.03. If the claim does fall within one of the statutory categories, it must then be determined in Step 2A [prong 1] whether the claim is directed to a judicial exception (i.e., law of nature, natural phenomenon, and abstract idea). See MPEP §2106.04. If the claim is directed toward a judicial exception, it must then be determined in Step 2A [prong 2] whether the judicial exception is integrated into a practical application. See MPEP §2106.04(d). Finally, if the judicial exception is not integrated into a practical application, it must additionally be determined in Step 2B whether the claim recites "significantly more" than the abstract idea. See MPEP §2106.05.
Examiner note: The Office’s 2019 Revised Patent Subject Matter Eligibility Guidance (2019 PEG) is currently found in the Ninth Edition, Revision 10.2019 (revised June 2020) of the Manual of Patent Examination Procedure (MPEP), specifically incorporated in MPEP §2106.03 through MPEP §2106.07(c).
Regarding Step 1,
Claims 1, 3-7, and 9-10 are directed toward a process (method). Thus, all claims fall within one of the four statutory categories as required by Step 1.
Regarding Step 2A [prong 1],
Claims 1, 3-7, and 9-10 are directed toward the judicial exception of an abstract idea. Independent claim 1 is directed specifically to the abstract idea of generating a property description/ listing.
Regarding independent claim 1, the underlined limitations emphasized below correspond to the abstract ideas of the claimed invention:
A method comprising:
obtaining an image of a real property; [Collecting or gathering information - Simply obtaining or receiving information before processing it is deemed an abstract idea (MPEP § 2106.04(a)))]
performing, using an encoder of an image processing network, a convolution process on the image to obtain an image embedding representing features of the image; [Mathematical concepts (mathematical operations, algorithms) - Describes the underlying mathematical operations and algorithms that machine learning models use, without a specific structural improvement to the computer itself (e.g., a novel neural network architecture) or technology]
decoding, using a decoder of the image processing network, the image embedding to obtain property data for the real property including a plurality of property features; [Mental processes or mathematical concepts - Translating visual embeddings into textual property features is an abstract data transformation. This mirrors human cognitive analysis, which is a judicial exception]
ranking the plurality of property features; [Methods of organizing human activity (rules for sorting, ranking, or evaluating criteria) - Ranking information based on relevance or established criteria is an abstract process of structuring information, reflecting economic or business principles of evaluation]
generating, using a language generation model, a description of the real property based on the image, the property data, and the ranking; [Mental processes or methods of organizing human activity - Utilizing a language model to organize, synthesize, and output a description is considered a mental process unless it changes how a computer itself operates]
augmenting the property data by fetching external data from an external data source;
identifying a description format for the real property; and generating an updated description for the real property based on the description format, the augmented property data, and the description of the real property. [Mental processes or methods of organizing human activity - Identifying formats and adjusting generated text to fit those formats is a conventional mental or business practice; automating traditional copywriting tasks using generic computing tools]
As the underlined claim limitations above demonstrate, independent claim 1 is directed to the abstract idea of Mathematical concepts (mathematical relationships, mathematical formulas or equations, mathematical calculations); Mental processes (concepts performed in the human mind (including an observation, evaluation, judgment, or opinion)); and Certain methods of organizing human activity (fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations).
Dependent claims 3-7, and 9-10 provide further details to the abstract idea of claim 1 regarding the received data, therefore, these claims include mathematical concepts, mental processes, and certain methods of organizing human activities for similar reasons provided above for claim 1.
After considering all claim elements, both individually and in combination and in ordered combination, it has been determined that the claims do not amount to significantly more than the abstract idea itself.
Regarding Step 2A [prong 2],
Claims 1, 3-7, and 9-10 fail to integrate the recited judicial exception into any practical application. The claims recite additional limitations which are hardware or software elements or particular technological environment, such as an “image processing network”, an “encoder”, a “decoder”, an “image embedding”, a “language generation model”, and a “machine learning model”. However, these limitations are not enough to qualify as “practical application” being recited in the claims along with the abstract idea since these limitations are merely invoked as a tool to perform instruction of an abstract idea in a particular technological environment and/or are generally linking the use of the abstract idea to a particular technological environment or field of use, and merely applying and abstract idea in a particular technological environment and merely limiting use of an abstract idea to a particular field or a technological environment do not provide practical application for an abstract idea (MPEP 2106.05 (f) & (h)). The claims do not amount to "practical application" for the abstract idea because they neither (1) recite any improvements to another technology or technical field; (2) recite any improvements to the functioning of the computer itself; (3) apply the judicial exception with, or by use of, a particular machine; (4) effect a transformation or reduction of a particular article to a different state or thing; (5) provide other meaningful limitations beyond generally linking the use of the judicial exception to a particular technological environment.
The presence of a machine learning algorithm does not necessarily restrict the claim from reciting an abstract idea. The machine learning algorithm claimed herein is a black box simply automating a task (listing a home) that a human agent would do, without a specific technical improvement. As claimed, machine learning algorithm is not iteratively trained to improve the accuracy of the model itself, it merely processes data as computer-implemented business method. Examiner notes that the additional limitations of machine learning and computer processing do not result in computer functionality or technical/technology improvement and hence do not result in a practical application. The machine learning algorithm and the computer limitation simply process the data through inputting and outputting data. Processing data is mere automation of manual processes, such as using a generic computer to process an application for financing a purchase, Credit Acceptance Corp. v. Westlake Services, 859 F.3d 1044, 1055, 123 USPQ2d 1100, 1108-09 (Fed.Cir. 2017) or speeding up a loan application process by enabling borrowers to avoid physically going to or calling each lender and filling out a loan application, Lending Tree, LLLC v. Zillow, Inc., 656 Fed. App'x 991, 996-97 (Fed. Cir. 2019)(non-precedential). Thus, the additional limitations of machine learning algorithm and computer limitations do not transform the abstract idea into a practical application.
The relevant question under Step 2A [prong 2] is not whether the claimed invention itself is a practical application, instead, the question is whether the claimed invention includes additional elements beyond the judicial exception that integrate the judicial exception into a practical application by imposing a meaningful limit on the judicial exception. This is not the case with Applicant’s claimed invention. Automating the recited claimed features as a combination of computer instructions implemented by computer hardware and/or software elements as recited above does not qualify an otherwise unpatentable abstract idea as patent eligible. Examples where the Courts have found selecting a particular data source or type of data to be manipulated to be insignificant extra-solution activity include selecting information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display, Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354-55, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016); Applicant’s limitations as recited above do nothing more than supplement the abstract idea using additional hardware/software computer components as a tool to perform the abstract idea and generally link the use of the abstract idea to a technological environment, which is not sufficient to integrate the judicial exception into a practical application since they do not impose any meaningful limits. Dependent claims 3-7, and 9-10 merely incorporate the additional elements recited above, along with further embellishments of the abstract idea of independent claims respectively, but these features only serve to further limit the abstract idea of independent claims. Therefore, the additional elements recited in the claimed invention individually, and in combination fail to integrate the recited judicial exception into any practical application.
Regarding Step 2B,
Claims 1, 3-7, and 9-10 fail to amount to “significantly more” than an abstract idea. The claims recite additional limitations which are hardware or software elements or particular technological environment, such as an “image processing network”, an “encoder”, a “decoder”, an “image embedding”, a “language generation model”, and a “machine learning model”. However, these limitations are not enough to qualify as “significantly more” being recited in the claims along with the abstract idea since these limitations are merely invoked as a tool to perform instruction of Abstract idea in a particular technological environment and/or are generally linking the use of the abstract idea to a particular technological environment or field of use, and merely applying and abstract idea in a particular technological environment and merely limiting use of an abstract idea to a particular field or a technological environment do not provide significantly more to an abstract idea (MPEP 2106.05(f) & (h)). The claims do not amount to "significantly more" than the abstract idea because they neither (1) recite any improvements to another technology or technical field; (2) recite any improvements to the functioning of the computer itself; (3) apply the judicial exception with, or by use of, a particular machine; (4) effect a transformation or reduction of a particular article to a different state or thing; (5) add a specific limitation other than what is well-understood, routine and conventional in the field; (6) add unconventional steps that confine the claim to a particular useful application; nor (7) provide other meaningful limitations beyond generally linking the use of the judicial exception to a particular technological environment.
Dependent claims 3-7, and 9-10 merely recite further additional embellishments of the abstract idea of independent claim 1, but these features only serve to further limit the abstract idea of independent claim 1; however, none of the dependent claims recite an improvement to a technology or technical field or provide any meaningful limits. The addition of another abstract concept to the limitations of the claims does not render the claim other than abstract. Under the Interim Guidance on Patent Subject Matter Eligibility (PEG 2019), it specifically states that narrowing an abstract idea of claims do not resolve the claims of being "significantly more" than the abstract idea. Thus, the additional elements in the dependent claims only serve to further limit the abstract idea utilizing the computer components as a tool and/or generally link the use of the abstract idea to a particular technological environment.
Therefore, since there are no limitations in the claims 1, 3-7, and 9-10 that transform the exception into a patent eligible application such that the claims amount to significantly more than the exception itself, and looking at the limitations as a combination and as an ordered combination adds nothing that is not already present when looking at the elements taken individually, claims 1, 3-7, and 9-10 are rejected under 35 USC § 101 as being directed to non-statutory subject matter under 35 U.S.C. § 101.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(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.
Claims 1-20 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Kappagantula et al. (US 12,380,675 B2).
As per independent Claim 1, Kappagantula discloses a method (See at least C2 L19-36) comprising:
obtaining an image of a real property; performing, using an encoder of an image processing network, a convolution process on the image to obtain an image embedding representing features of the image; decoding, using a decoder of the image processing network, the image embedding to obtain property data for the real property including a plurality of property features (See at least Fig.2; C6 L4-29, “The method may include cropping and categorizing images from a selected property using the trained third NN, at 112. For example, the trained third NN may categorize images in bulk from one or more sources (e.g., such as property image or MLS databases, or appraisal or broker price opinion images), or it may receive user-submitted images from a single property, or may otherwise be applied to categorize or evaluate property images based on the training. At 114, the method may include generating property data for the selected property based on the cropped and categorized images from the third NN. For example, the third NN may be trained to categorize images into a plurality of different groups, and a computer program may be able to recognize the categories and assign one or more labels or property data outputs based on the categorization. In one embodiment, a property listing from MLS or another property site may be submitted to the third NN, for example via a web interface. The third NN may perform cropping and categorization on one or more property images from the listing. Based on the categorization, a computer system or software may determine that the kitchen for the property is modern or updated, and possibly determine that the kitchen includes shaker-style cabinets, granite countertops, and chrome plumbing fixtures. This data may be used to automatically update property listings for large numbers of properties without manual supervision or verification.; C16L34-67, “At 808, the method may include generating and concatenating one or more vectors for rooms of the property based on the cropped images. Vectors may refer to data objects that can represent something, such as images or the depicted rooms or properties themselves, in vector space. …”, generating one or more vectors for the image - the definition of generating embeddings);
ranking the plurality of property features (See at least C20 L32-61, “… The property evaluation module 1020 may use algorithms or computer processes to consider and weigh multiple image classifications …”;
generating, using a language generation model, a description of the real property based on the image, the property data, and the ranking (See at least C6 L4-29 (See above); C17L1-7, “In some examples, vectors for multiple rooms or images of a same property can be grouped or combined (e.g., concatenated) to generate one or more vectors for the property as a whole. In some examples, information about the property obtained outside the images (e.g., address, square footage, etc.) can be incorporated into vectors for a property.”;
augmenting the property data by fetching external data from an external data source (See at least C21L10-20, “Property data 1014 may represent data about a current selected property for evaluation, or about other properties used for comparison. Property data may include address, neighborhood, or zip code information; number of rooms; square footage; room or property layout, orientation, or facing; valuation or sales data; coordinates; elevation; other property data, or any combination thereof. The property data 1014 may be obtained from any source, including data storage 1022, user interface 1008, or from various sources via communication interface 1006, including remote user front-ends 202, MLS servers 214, or GIS server 216.”;
identifying a description format for the real property (See at least C7 L22-31, and C8 L18-27); and
generating an updated description for the real property based on the description format, the augmented property data, and the description of the real property (See at least C6 L4-29 (See above), and C9 L33-56).
As per Claim 3, Kappagantula discloses distributing the updated description via a public listing distribution (See at least C2 L37-67, Property data used to generate targeted advertising/ listing; C9 L50-56, “In some examples, the property classification or evaluation results may be provided to other systems, such as an automated valuation model, added to an entry for the property for finding comparable properties in an appraisal software, uploaded to a corresponding property listing of MLS 214 in cloud infrastructure 206.”).
As per Claim 4, Kappagantula discloses identifying a compliance rule for the updated description, wherein the updated description is generated based at least in part on the compliance rule (See at least C6 L4-29, C20 L31- C21 L9).
As per Claim 5, Kappagantula discloses generating, using a predictive machine learning model, a property prediction based on the image (See at least Figs.1-2; See at least C2 L39-43, “In particular, the method of FIG. 1 may present an example process for applying computer vision, machine learning, or both, to property images and data in order to generate property evaluations on a variety of metrics.”; C6 L4-29; See also C3 L1-30).
As per Claim 6 (5), Kappagantula discloses generating a private updated description including the property prediction (See at least C2 L37-67, Property data used to generate targeted advertising/ listing).
As per Claim 7 (6), Kappagantula discloses wherein distributing the private listing comprises: distributing the private updated description via a restricted listing distribution (See at least C2 L37-67).
As per Claim 9, Kappagantula discloses detecting a change in the property data; and regenerating the updated description based on the detected change (See at least C6 L4-29, i.e. user-submitted images).
As per Claim 10, Kappagantula discloses generating a caption for the image, wherein the updated description includes the caption (See at least C8 L9-27, i.e. image labels).
Response to Arguments
Applicant's arguments filed on 5/22/2026, with respect to Claims 1, 3-7, and 9-10, have been considered but are not persuasive. The rejection will remain as FINAL, based on the rejection above.
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) 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.
The Applicant has made the argument that the claims are directed to patent eligible subject matter.8
However, while the Applicant's claims are directed to a Process, Machine, Manufacture or Composition of Matter (Step 1), the claims fail to recite limitations that are “significantly more” than an abstract idea (Step 2a-2b).
The claim limitations (under their broadest reasonable interpretation) recite Certain methods of organizing human activity, Mathematical concepts, and/or Mental processes as defined in the guidance set forth in the 2019 Memorandum. This is so because the claimed limitations recite steps that automates a standard real-estate analysis and copywriting workflow using conventional computer and AI tools/ models. Accordingly, the Examiner concludes that the claims recite a judicial exception of a Mental process, Mathematical concepts, and/or Certain methods of organizing human activity.
Furthermore, having determined that claims recite a judicial exception, analysis under the Memorandum turns now to determining whether there are “additional elements that integrate the judicial exception into a practical application.” See Memorandum (Step 2A, prong 2), see also MPEP § 2106.05(a)-(c), (e)-(h)). This judicial exception is not integrated into a practical application because the combination of additional elements fails to integrate the judicial exception into a practical application within the meaning defined in the Subject Matter Eligibility Guidelines, Examiner notes the following. While the computer technology does make the steps more easily performed, in principle, the steps can be performed without such computer and the notion of ‘practicality’ is not evidenced. ‘Practicality’ is based on whether the invention demonstrates:
Improvements to the functioning of a computer, or to any other technology or technical field - see MPEP 2106.05(a)
Applying or using a judicial exception to effect a particular treatment or prophylaxis for a disease or medical condition – see Vanda Memo
Applying the judicial exception with, or by use of, a particular machine - see MPEP 2106.05(b)
Effecting a transformation or reduction of a particular article to a different state or thing - see MPEP 2106.05(c)
Applying or using the judicial exception in some other meaningful way beyond generally linking the use of the judicial exception to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception - see MPEP 2106.05(e) and Vanda Memo
The claims are simply directed to an abstract idea (searching, correlating, and transmitting/ displaying data based on saved rules and characteristics) with additional generic computer elements, because the generically recited computer elements do not add a meaningful limitation to the abstract idea, and because they amount to simply implementing the abstract idea on a computer.
Finally, the examination proceeds to evaluating whether the claims add specific limitations beyond the judicial exception that are not “well-understood, routine, conventional” in the field (see MPEP § 2106.05(d)) or simply appends well-understood, routine, conventional activities previously known to the industry, specified at a high level of generality, to the judicial exception. See Memorandum (Step 2B). The claims do not add specific limitations beyond what is well-understood, routine, and conventional. As such, there is no inventive concept sufficient to transform the claimed subject matter into a patent-eligible application. The claim does not amount to significantly more than the abstract idea itself.
The Examiner therefore maintains the 35 USC 101 rejections.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure can be found in the PTO-892 Notice of References Cited. The Examiner suggests the applicant review all of these documents before submitting any amendments.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to JONATHAN P OUELLETTE whose telephone number is (571)272-6807. The examiner can normally be reached on M-F 8am-6pm.
If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Lynda C Jasmin, can be reached at telephone number (571) 272-6782. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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July 13, 2026
/JONATHAN P OUELLETTE/Primary Examiner, Art Unit 3629
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