DETAILED ACTION
Status of Claims
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This action is in reply to the amendment filed on 07/29/2025.
Claims 1-15 are currently pending and have been examined.
The previous objections to the claims are hereby withdrawn due to applicant’s amendments.
Response to Arguments
Applicant’s arguments, see pages 17-20, filed 07/29/2025, with respect to claims 1-15 rejected under 35 USC 103 have been fully considered and are persuasive. The 103 rejection of claims 1-15 has been withdrawn.
Applicant's arguments filed with respect to 101 and the 112(f) interpretation have been fully considered but they are not persuasive.
With respect to 112(f), applicant’s cites Williamson vs Citrix Online, and argues that since the claims do not recite “means” or “step” for they should not be interpreted under 112(f). The Examiner respectfully disagrees, as an initial matter, in the conclusion of court decision, the Court stated it did not err in construing the term “distributed learning control module” in claims 8–16 of the ’840 patent as a means-plus-function claim term lacking corresponding structure. Similar to the findings in the decision, the claimed limitation of instant application invokes 112(f) due to the use of the nonce word “unit” and failing recite the corresponding structure in the limitation. For these reasons, the Examiner must interpret “a storage unit that stores” under 112(f). See also MPEP 2181 (I)(A) “With respect to the first prong of this analysis, a claim element that does not include the term "means" or "step" triggers a rebuttable presumption that 35 U.S.C. 112(f) does not apply. When the claim limitation does not use the term "means," examiners should determine whether the presumption that 35 U.S.C. 112(f) does not apply is overcome. The presumption may be overcome if the claim limitation uses a generic placeholder (a term that is simply a substitute for the term "means"). The following is a list of non-structural generic placeholders that may invoke 35 U.S.C. 112(f): "mechanism for," "module for," "device for," "unit for," "component for," "element for," "member for," "apparatus for," "machine for," or "system for."… Note that there is no fixed list of generic placeholders that always result in 35 U.S.C. 112(f) interpretation, and likewise there is no fixed list of words that always avoid 35 U.S.C. 112(f) interpretation. Every case will turn on its own unique set of facts… The standard is whether the words of the claim are understood by persons of ordinary skill in the art to have a sufficiently definite meaning as the name for structure. “
With respect to 101:
Applicant argues #1:
Under Step 2A, Prong One, the claims are not directed merely to an abstract idea such as organizing human activity or analyzing information in the abstract. Rather, the claims recite a specific, structured computing system that performs a series of defined operations: acquiring social-network data from a tenant, extracting structured information (hashtags and keywords) using natural-language processing, generating tenant-attribute data using a trained machine-learning model, and estimating predicted sales for a physical retail space by fusing that tenant data with space-feature data derived from real-time sensor inputs. The system then ranks candidate spaces using the output of a neural-network sales-prediction model and transmits the ranking to a user terminal. These steps are performed by an integrated architecture that includes a registration-assistance server, an edge server coupled to a sensor group, and a tenant terminal. The system is not abstract it is a specific arrangement of physical and logical components designed to improve the accuracy and efficiency of retail-space selection.
Examiners response:
The Examiner respectfully disagrees, under Step 2A, Prong One of the steam-lined analysis, as laid out in MPEP 2106, Prong One asks does the claim recite an abstract idea, law of nature, or natural phenomenon? The answer to this question is definitely yes, as there are several abstract steps recited in the claims the amount to collecting data, analyzing the data and sending the results similar to several ineligible decisions, one for example, Electric Power Group and the claim to "collecting information, analyzing it, and displaying certain results of the collection and analysis," where the data analysis steps are recited at a high level of generality such that they could practically be performed in the human mind, Electric Power Group v. Alstom, S.A., 830 F.3d 1350, 1353-54, 119 USPQ2d 1739, 1741-42 (Fed. Cir. 2016);. The additional elements of the claims (the registration-assistance server, an edge server coupled to a sensor group, and a tenant terminal) are analyzed under Step 2A Prong Two and Step 2B of the analysis.
Applicant argues #2:
Even if the claims were deemed to recite an abstract idea under Step 2A, Prong One, they still qualify as patent-eligible under Prong Two because they are integrated into a practical application. The claims do not merely analyze data and display results. Instead, they integrate multiple real-time data streams including demographic vectors generated by sensors measuring passer-by traffic into a predictive framework that applies machine-learning models trained on historical tenant data. The architecture allows for automatic, continuous updates and dynamic re-estimation of predicted sales as new social-network content becomes available.
This integration yields a practical and concrete outcome: it enables a tenant to select a retail location with lower onboarding time and greater predictive certainty, addressing a real-world problem that cannot be solved solely by human judgment or pen-and-paper analysis.
Examiners response:
The Examiner respectfully disagrees, with regards to the human mind/pen and paper test, as an initial matter, just because an idea cannot be performed with a pen and paper or in the human mind does not mean it’s not directed towards an abstract idea and the Examiner did not rely on grouping the claims into the Mental Processes grouping of abstract ideas for the analysis. Furthermore Examiners are directed to continue to use the Mayo Alice framework (as laid out in MPEP 2106 which incorporates Steps 2A and Step 2B of the 2019 PEG) as guidance in evaluating subject matter eligibility, which the Examiner has properly applied. With respect to the real-time data streams, sensors measuring passer-by traffic, and machine-learning models which allows for automatic, continuous updates and dynamic re-estimation of predicted sales as new social-network content becomes available, these elements and the processes they perform do not result in a practical application as they are describing the particular environment in which the idea is being limited to (with respect to the edge server and sensors) and the machine-learning model is recited in a highly generic manner such that it amounts to a generic computer component being used to analyze the data similar to A wide-area real-time performance monitoring system for monitoring and assessing dynamic stability of an electric power grid – Electric Power Group, 830 F.3d at 1351 and n.1, 119 USPQ2d at 1740 and n.1;. As per MPEP 2106.05(f) Use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone);.
Applicant argues #3:
The claims also satisfy Step 2B of the Alice framework. They include significantly more than a recitation of an abstract idea. Specifically, the amended claims recite a technological solution using non-conventional elements arranged in a non-generic manner. For example, the use of a sensor-connected edge server to derive space-feature data, the application of a tenant-similarity threshold in model inference, and the deployment of machine-learning-based prediction models trained on structured historical data all reflect a level of technical sophistication that goes beyond routine or conventional implementation. Unlike cases in which generic data collection and analysis is deemed insufficient under § 101, the instant claims recite a coordinated hardware-software system that transforms incoming data streams into a new and useful result namely, an automatically ranked list of retail spaces based on predicted revenue for a particular tenant profile.
Accordingly, the amended claims are not directed to a judicial exception and, even if one were implicated, the claims provide significantly more in the form of a specific machine-based implementation and a technological improvement. Therefore, the rejection under 35 U.S.C. § 101 should be withdrawn.
Examiners response:
The Examiner respectfully disagrees, the edge server is generic computer component being used for collecting data from the sensors. As discussed above, the edge server and machine learning models are claimed in a highly generic manner such that they amount to generic components. The sensors are also claimed and described in a highly generic manner, with [0043] describing the sensor group as possibly “The sensor group 201 is a sensor group installed in a region in which the space exists, and acquires sensor data and the like regarding people using the space. The sensor group 201 acquires images, for example.” Here the sensor are described at a high level of generality for performing observations of people using the space, using them tools for performing abstract concepts and does not amount to an inventive concept or practical application. The additional elements, as claimed are not indicative of a practical application because this is akin to 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);., thus the Examiner fails to see how the claims amount to other meaningful limitations beyond generally linking the use of the judicial exception to a particular technological environment (see MPEP 2106.05).
For the reasons above, the 101 rejection is hereby maintained.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: “a storage unit that stores” in claim 6.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
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 1-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more, and fails step 2 of the analysis because the focus of the claims is not on the devices themselves or a practical application but rather directed towards an abstract idea, the analysis is provided below.
Step 1 (Statutory Categories) - The claims pass step 1 of the subject matter eligibility test (see MPEP 2106(III)) as the claims are directed towards two systems, and a method.
Step 2A – Prong One (Do the claims recite an abstract idea?)
Claims 1, recite an abstract idea, in part, by:
periodically generates sensor data for each candidate space;
manages space features representing characteristics of the space,
store space-feature data that include a passer-by demographic attribute vector automatically derived from the sensor data received from the edge server;
receive, from the tenant, account credentials for a social-networking service (SNS) used by a tenant,
access the SNS with the account credentials and extract hashtags and natural-language-processed keywords included from tenant posts to obtain SNS information;
generate tenant-attribute data comprising at least a sales-item category, target customer gender distribution, and target customer age group by applying a model to the SNS information;
for each candidate space, compute a predicted sales figure, expressed in monetary units, by inputting (i) the tenant-attribute data, (ii) the space-feature data, and (iii) historical store-opening records of past tenants whose tenant-attribute similarity exceeds a threshold, into a model and write the predicted sales figures and corresponding space identifiers into a structured ranking table and transmit the ranking table, together with the space-feature data, to the tenant.
Claim 9, while varying in scope, recites a similar abstract idea, in part, by:
a) storing space-feature data that include a passer-by demographic attribute vector automatically generated from sensor data acquired by the edge server;
b) acquiring, from the tenant, account credentials for a social-networking service (SNS);
c) accessing the SNS with the credentials and extracting hashtags and natural-language-processed keywords from tenant posts to obtain SNS information;
d) deriving tenant attribute data by executing a model that takes the SNS information as input;
e) predicting monetary sales for each candidate space using (i) the tenant-attribute data, (ii) the space-feature data, and (iii) store-opening history of tenants having a tenant-attribute similarity above a threshold; and
f) sending to the tenant a ranking of the candidate spaces together with the predicted sales figures and corresponding space-feature data.
Claim 15, while varying in scope, recites a similar abstract idea, in part, by:
periodically generates sensor data for each candidate space;
store space-feature data, including a passer-by demographic attribute vector derived from sensor data provided by the edge server;
acquire, from the tenant, account credentials for a social-networking service (SNS);
access the SNS using the credentials and extract hashtags and natural-language-processed keywords from tenant posts to obtain SNS information;
generate tenant-attribute data by applying a model to the SNS information;
receive, from the tenant, store-opening conditions that the candidate space must satisfy;
compute, for each candidate space that meets the store-opening conditions, a predicted monetary sales figure that consumes (i) the tenant-attribute data, (ii) the space-feature data, and (iii) historical store-opening records of tenants having similar tenant- attribute data; and
transmit to the tenant a list of the candidate spaces together with the predicted sales figures and corresponding space-feature data.
The steps recited above under Step 2A Prong One of the analysis under the broadest reasonable interpretation covers commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations) but for the recitation of generic computer components. That is other than reciting a computer system, a registration assistance server that includes at least one processor and memory, an edge server coupled to a sensor group, a tenant terminal, a storage unit, at least one computer including at least one processor, non-volatile memory, storage device and network interface, a trained tenant-attribute estimation model, and a trained neural-network sales-prediction model nothing in the claim elements are directed towards anything other than commercial or legal interactions. If a claim limitation, under its broadest reasonable interpretation, covers commercial or legal interactions, then it falls within the “Certain Methods of Organizing Human Activities” groupings of abstract ideas. Accordingly, the claims recite an abstract idea.
Step 2A – Prong Two (Does the claim recite additional elements that integrate the judicial exception into a practical application?) - This judicial exception is not integrated into a practical application. In particular, the claims only recite the additional elements of a computer system, a registration assistance server that includes at least one processor and memory, an edge server coupled to a sensor group, a tenant terminal, a storage unit, at least one computer including at least one processor, non-volatile memory, storage device and network interface, a trained tenant-attribute estimation model, and a trained neural-network sales-prediction model. The aforementioned additional elements are recited at a high level of generality such that it amounts to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply the judicial exception using generic computer components is not indicative of a practical application (see MPEP 20106.05(f) and MPEP 20106.05(h)). With respect to the trained models, the models are recited at a highly generic level such that they amount generic computer components being used as tools to perform abstract concepts. As per MPEP 2106.05(f), use of a computer or other machinery in its ordinary capacity for economic or other tasks (e.g., to receive, store, or transmit data) or simply adding a general purpose computer or computer components after the fact to an abstract idea (e.g., a fundamental economic practice or mathematical equation) does not integrate a judicial exception into a practical application or provide significantly more. See Affinity Labs v. DirecTV, 838 F.3d 1253, 1262, 120 USPQ2d 1201, 1207 (Fed. Cir. 2016) (cellular telephone);. Similarly, with respect to the edge server and sensor group, these are recited in a highly generic manner, and amounts to data gathering in conjunction with the abstract idea and are part of the technical environment in the which the idea is being limited to akin to 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);. Additionally [0043] describes the sensor group as “The sensor group 201 is a sensor group installed in a region in which the space exists, and acquires sensor data and the like regarding people using the space. The sensor group 201 acquires images, for example.” Here the sensor are described at a high level of generality for performing observations of people using the space, using them tools for performing abstract concepts. 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 towards an abstract idea.
Step 2B (Does the claim recite additional elements that amount to significantly more than the judicial exception?) - The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, as discussed above, with respect to integration of the abstract idea into a practical application, using the additional elements to perform the steps recited in Step 2A Prong One of the analysis amounts to no more than mere instructions to apply the exception using generic computer components and limits the judicial exception to a particular environment. Mere instructions to apply an exception using generic computer components and limiting the judicial exception to a particular environment does not provide an inventive concept. The additional elements have been considered separately, and as an ordered combination, and do not add significantly more (also known as an “inventive concept”) to the judicial exception. Further, MPEP 2106.05(d)(ii) provides that receiving and transmitting data over a network (see buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network), Performing repetitive calculations, Flook, 437 U.S. at 594, 198 USPQ2d at 199 (recomputing or readjusting alarm limit values); Ultramercial, 772 F.3d at 716, 112 USPQ2d at 1755 (updating an activity log); and Electronically scanning or extracting data from a physical document, Content Extraction and Transmission, LLC v. Wells Fargo Bank, 776 F.3d 1343, 1348, 113 USPQ2d 1354, 1358 (Fed. Cir. 2014) (optical character recognition); are well-understood routine and conventional, similar to the instant application claims which recites and sending and receiving data presumably over network from the SNS, and analyzing the data to estimate sales related to a space for a tenant, akin to performing repetitive calculations. The claims are not patent eligible.
The dependent claims have been given the full analysis including analyzing the additional limitations both individually and in combination as a whole. For instance, 2-8 are all steps that fall within the “Certain Methods of Organizing Human Activities” groupings of abstract ideas, further limiting the abstract idea, and while the claims recite using models to perform some of the analysis, these models are recited at high level such that the models are generic components perform repetitive calculations similar to as discussed above. With respect to the storage unit, MPEP 2106.05(d) shows that Storing and retrieving information in memory, Versata Dev. Group, Inc. v. SAP Am., Inc., 793 F.3d 1306, 1334, 115 USPQ2d 1681, 1701 (Fed. Cir. 2015); OIP Techs., 788 F.3d at 1363, 115 USPQ2d at 1092-93; is a well‐understood, routine, and conventional function of computers and therefor does not amount to significantly more. The Dependent claims when analyzed both individually and in combination are also held to be patent ineligible under 35 U.S.C. 101 for the same reasoning as above and the additional recited limitations fail to establish that the claims are not directed to an abstract idea. The additional limitations of the dependent claims when considered individually and as an ordered combination do not amount to significantly more than the abstract idea.
Conclusion
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to GREGORY S CUNNINGHAM II whose telephone number is (313)446-6564. The examiner can normally be reached Mon-Fri 8:30am-4pm.
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GREGORY S. CUNNINGHAM II
Primary Examiner
Art Unit 3694
/GREGORY S CUNNINGHAM II/Primary Examiner, Art Unit 3694