Detailed Action
This Non Final office action is in response to Applicant’s filing of application No. 18/784,229 on July 25, 2024. Claims 1-20 are currently pending and under examination.
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 .
Drawings
3. The drawings filed on July 25, 2024 are accepted.
Claim Rejections - 35 USC§ 101
4. 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.
5. Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Step One:
Under Step one of an analysis, claim 1 does belong to a statutory category, namely it is a system claim. Likewise, claim 9 is a process claim. Claim 15 is a non-transitory computer readable program product claim. Therefore, claims 1, 9 and 17 fall under one of the four statutory classes of invention.
Step 2A. Prong 1:
The claims recite the following limitations that are understood to recite an abstract idea without the bolded limitations.
Representative claim 1 recites:
one or more memories; and
one or more processors, communicatively coupled to the one or more memories, configured to:
receive, from a user device, an indication of a property;
determine, using the indication of the property, a location of a school associated with the property;
receive, from a first data source, statistical information associated with the location;
receive, from a second data source, a set of feedback associated with the location, where the set of feedback originated from a set of verified sources;
receive, from a third data source, background information associated with a set of staff for the location;
provide the statistical information, the set of feedback, and the background information to the machine learning model in order to receive the multi-dimensional safety indicator, wherein the multi-dimensional safety indicator comprises a plurality of scores associated with a respective plurality of dimensions; and
output, to the user device, instructions for a user interface (UI) including a representation of the multi-dimensional safety indicator.
Claim 2 further recites wherein the one or more processors are configured to: output, to the user device, instructions for a map of a geographic area that includes the property, wherein the indication of the property comprises an indication of an interaction with the map.
Claim 3 further wherein the indication of the property comprises an address or a set of coordinates.
Claim 4 further recites wherein the one or more processors, to determine the location of the school, are configured to: map, using a data structure, a location of the property to the location of the school.
Claim 5 further recites wherein the one or more processors, to map the location of the property to the location of the school, are configured to: transmit, to a database, a query indicating the location of the property; and
receive, from the database, a response indicating the location of the school.
Claim 6 further recites wherein the one or more processors are configured to:
transmit, to a database, a query indicating a set of sources associated with the set of feedback; and receive, from the database, a response indicating that the set of sources are verified.
Claim 7 further recites wherein each feedback, in the set of feedback, includes an indication of verification for a corresponding source in the set of verified sources.
Claim 8 further recites indicates a valuation for the property that was calculated, at least in part, using the multi-dimensional safety indicator.
Claim 9 further recites receiving, at an analysis system and from a user device, an indication of a property;
mapping, by the analysis system, the indication of the property to a plurality of possible locations of a plurality of possible schools associated with the property;
outputting, from the analysis system and to the user device, an indication of the plurality of possible locations;
receiving, at the analysis system and from the user device, an indication of a selected location from the plurality of possible locations;
providing a representation of the selected location to the machine learning model in order to receive the multi-dimensional safety indicator, wherein the multi-dimensional safety indicator comprises a plurality of scores associated with a respective plurality of dimensions; and
outputting, from the analysis system and to the user device, a data structure encoding the multi-dimensional safety indicator.
Claim 10 further recites wherein outputting the indication of the plurality of possible locations comprises:
transmitting, from the analysis system and to the user device, instructions for a user interface (UI) indicating the plurality of possible locations.
Claim 11 further recites wherein receiving the indication of the selected location comprises:
receiving an indication of an interaction with the UI, wherein the indication of the interaction comprises the indication of the selected location.
Claim 12 further recites outputting, from the analysis system and to the user device, an indication of a valuation for the property that was calculated, at least in part, using the multi-dimensional safety indicator.
Claim 13 further recites wherein the data structure encoding the multi-dimensional safety indicator comprises an array of scores.
Claim 14 further recites wherein the respective plurality of dimensions includes an academic dimension, a social safety dimension, and a staff safety dimension.
Claim 15 recites a non-transitory computer-readable medium storing a set of instructions for receiving a multi-dimensional safety indicator determined by a machine learning model, the set of instructions comprising: one or more instructions that, when executed by one or more processors of a device, cause the device to:
transmit, to an analysis system, an indication of a property;
receive, from the analysis system and in response to the indication of the property, an indication of a plurality of possible locations of a plurality of possible schools associated with the property;
transmit, to the analysis system, an indication of a selected location from the plurality of possible locations; and
receive, from the analysis system and in response to the indication of the selected location, a data structure encoding the multi-dimensional safety indicator associated with the selected location, wherein the multi-dimensional safety indicator comprises a plurality of scores that were determined by the machine learning model and are associated with a respective plurality of dimensions.
Claim 16 further recites output a representation of a map to a user of the device; and detect an interaction with the representation of the map by the user of the device, wherein the indication of the property is transmitted based on the interaction.
Claim 17 further recites output a representation of the plurality of possible locations to a user of the device; and detect an interaction with the representation of the plurality of possible locations from the user of the device, wherein the indication of the selected location is transmitted based on the interaction.
Claim 18 further recites wherein the respective plurality of dimensions includes an academic dimension, a social safety dimension, and a staff safety dimension.
Claim 19 further recites receive, from the analysis system, a decision associated with the property that was determined, at least in part, using the multi-dimensional safety indicator.
Claim 20 further recites receive, from the analysis system, an indication of a valuation for the property that was calculated, at least in part, using the multi-dimensional safety indicator.
The claims above recite the following limitations that are understood to recite an abstract idea with the additional limitations in bold.
Regarding independent claims 1, 9 and 17, the claimed concept falls into the category of functions of performing mental processes such as concepts performed in the human mind (including an observation, evaluation, judgment, opinion) and a mathematical process. The claims are directed to a certain method of organizing human activity. The dependent claims (claims 2-8, 10-16 and 18-20) are directed to a certain method of organizing human activity.
Step 2A, Prong Two of the eligibility analysis evaluates whether the claim as a whole integrates the recited judicial exception(s) into a practical application of the exception. This evaluation is performed by (a) identifying whether there are any additional elements recited in the claim beyond the judicial exception, and (b) evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application.2019 PEG Section III(A)(2), 84 Fed. Reg. at 54-55.
The claims recite the following limitations that are understood to recite an abstract idea with the bolded limitations to be the additional elements.
Representative claim 1 recites:
one or more memories; and
one or more processors, communicatively coupled to the one or more memories, configured to:
receive, from a user device, an indication of a property;
determine, using the indication of the property, a location of a school associated with the property;
receive, from a first data source, statistical information associated with the location;
receive, from a second data source, a set of feedback associated with the location, where the set of feedback originated from a set of verified sources;
receive, from a third data source, background information associated with a set of staff for the location;
provide the statistical information, the set of feedback, and the background information to the machine learning model in order to receive the multi-dimensional safety indicator, wherein the multi-dimensional safety indicator comprises a plurality of scores associated with a respective plurality of dimensions; and
output, to the user device, instructions for a user interface (UI) including a representation of the multi-dimensional safety indicator.
Claim 2 further recites wherein the one or more processors are configured to: output, to the user device, instructions for a map of a geographic area that includes the property, wherein the indication of the property comprises an indication of an interaction with the map.
Claim 3 further wherein the indication of the property comprises an address or a set of coordinates.
Claim 4 further recites wherein the one or more processors, to determine the location of the school, are configured to: map, using a data structure, a location of the property to the location of the school.
Claim 5 further recites wherein the one or more processors, to map the location of the property to the location of the school, are configured to: transmit, to a database, a query indicating the location of the property; and receive, from the database, a response indicating the location of the school.
Claim 6 further recites wherein the one or more processors are configured to:
transmit, to a database, a query indicating a set of sources associated with the set of feedback; and receive, from the database, a response indicating that the set of sources are verified.
Claim 7 further recites wherein each feedback, in the set of feedback, includes an indication of verification for a corresponding source in the set of verified sources.
Claim 8 further recites indicates a valuation for the property that was calculated, at least in part, using the multi-dimensional safety indicator.
Claim 9 further recites receiving, at an analysis system and from a user device, an indication of a property;
mapping, by the analysis system, the indication of the property to a plurality of possible locations of a plurality of possible schools associated with the property;
outputting, from the analysis system and to the user device, an indication of the plurality of possible locations;
receiving, at the analysis system and from the user device, an indication of a selected location from the plurality of possible locations;
providing a representation of the selected location to the machine learning model in order to receive the multi-dimensional safety indicator, wherein the multi-dimensional safety indicator comprises a plurality of scores associated with a respective plurality of dimensions; and
outputting, from the analysis system and to the user device, a data structure encoding the multi-dimensional safety indicator.
Claim 10 further recites wherein outputting the indication of the plurality of possible locations comprises:
transmitting, from the analysis system and to the user device, instructions for a user interface (UI) indicating the plurality of possible locations.
Claim 11 further recites wherein receiving the indication of the selected location comprises:
receiving an indication of an interaction with the UI, wherein the indication of the interaction comprises the indication of the selected location.
Claim 12 further recites outputting, from the analysis system and to the user device, an indication of a valuation for the property that was calculated, at least in part, using the multi-dimensional safety indicator.
Claim 13 further recites wherein the data structure encoding the multi-dimensional safety indicator comprises an array of scores.
Claim 14 further recites wherein the respective plurality of dimensions includes an academic dimension, a social safety dimension, and a staff safety dimension.
Claim 15 recites a non-transitory computer-readable medium storing a set of instructions for receiving a multi-dimensional safety indicator determined by a machine learning model, the set of instructions comprising: one or more instructions that, when executed by one or more processors of a device, cause the device to:
transmit, to an analysis system, an indication of a property; receive, from the analysis system and in response to the indication of the property, an indication of a plurality of possible locations of a plurality of possible schools associated with the property;
transmit, to the analysis system, an indication of a selected location from the plurality of possible locations; and
receive, from the analysis system and in response to the indication of the selected location, a data structure encoding the multi-dimensional safety indicator associated with the selected location, wherein the multi-dimensional safety indicator comprises a plurality of scores that were determined by the machine learning model and are associated with a respective plurality of dimensions.
Claim 16 further recites output a representation of a map to a user of the device; and detect an interaction with the representation of the map by the user of the device, wherein the indication of the property is transmitted based on the interaction.
Claim 17 further recites output a representation of the plurality of possible locations to a user of the device; and detect an interaction with the representation of the plurality of possible locations from the user of the device, wherein the indication of the selected location is transmitted based on the interaction.
Claim 18 further recites wherein the respective plurality of dimensions includes an academic dimension, a social safety dimension, and a staff safety dimension.
Claim 19 further recites receive, from the analysis system, a decision associated with the property that was determined, at least in part, using the multi-dimensional safety indicator.
Claim 20 further recites receive, from the analysis system, an indication of a valuation for the property that was calculated, at least in part, using the multi-dimensional safety indicator.
In addition to the abstract ideas recited in the claims, the claims recite additional elements including a generic data collecting step using a processor and memory. The claimed “one or more memories”, “one or more processors” “a device”, “a first data source”, “a second data source”, “a third data source”, “machine learning model” and a “a user interface (UI)”, are similarly understood in light of applicant's specification as mere usage of any arrangement of computer software or hardware intermediate components potentially using networks to communicate with instructions are properly understood to be mere instructions to apply the abstraction using a computer processor. Performing steps or functions by a processor merely limits the abstraction to a computer field by execution by generic computers to process data (i.e. determine a quality score for the school data). The claimed limitations pertaining to the machine learning amount merely to the very definition of the training aspect of the machine learning. As such, the independent claims do not reflect any improvement in machine learning (or in another technology/functioning of a computer), and the machine learning limitations are merely generic computer elements. Performing steps by a generic machine, or server computing device merely limit the abstraction to a computer field by execution by generic computers. See MPEP 2106.05 (1).
As noted in MPEP 2106.04(d), limitations which amount to instructions to implement an abstract idea on a computer or merely using a computer as a tool, limitations which amount to insignificant extra-solution activity, and limitations which amount to generally linking to a particular technological environment do not integrate a practical exception into a practical application.
Performance of the claimed steps or functions technologically may present a meaningful limit to the scope of the claims does not reasonably integrate the abstraction into a practical application.
Accordingly, the 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. Thus the claims are directed to an abstract idea.
Step 2B: The elements discussed above with respect to the practical application in Step 2A, prong 2 are equally applicable to consideration of whether the claims amount to significantly more. Accordingly, the clams fail to recite additional elements which, when considered individually and in combination, amount to significantly more.
Reconsideration of these elements identified as insignificant extra-solution activity as part of Step 2B does not change the analysis.
Positively reciting a “one or more memories”, “one or more processors” “a device”, “a first data source”, “a second data source”, “a third data source”, “machine learning model” and a “a user interface (UI)”, does not change the analysis as these aspects are properly considered as additional elements which amount to instructions to apply it with a computer.
These claimed elements also as found in the dependent claims are also recited at a high level of generality such that they amount to no more than mere instructions to apply the exception using a generic component.
In processing the claims, it is noted that the recitation of these additional elements does not impact the analysis of the claims because these elements in combination are noted only to be one or more of a general purpose computer for performing basic or routine computer functions. The claimed online system, machine learning model and graphical user interface are noted to a generic computer.
These additional elements do not overcome the analysis as these elements are merely considered as additional elements which amount to instructions to be applied to the generic computer.
The judicial exception is not integrated into a practical application. In particular, the claimed online system, machine learning model and a graphical user interface are recited at a high level of generality such they amount to no more than mere instructions to apply the exception using generic components. Accordingly, the 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. Accordingly, claim 10 is directed to an abstract idea.
Accordingly, claims 1, 9 and 17 are directed to an abstract idea.
Dependent claims 2-8 include additional elements beyond those recited by independent claim 1. Dependent claims 10-16 include additional elements beyond those recited by independent claim 9, and dependent claims 18-20 include additional elements beyond those recited by independent claim 17. The provision of additional details of a generic computer element does not render the element any less generic. The claimed steps do not amount to significantly more than the abstract idea, because they are well-understood, routine, and conventional computer functions in view of MPEP 2106 .05(d)(11). The recited computer elements do not amount to significantly more than the abstract idea because the computer elements are generic computer elements that are merely used as a tool to perform the recited abstract idea. As a result, claims 1-20 do not include additional elements that amount to significantly more than the abstract idea under Step 2B.
Therefore, the claims are directed to an abstract idea without additional elements amounting to significantly more than the abstract idea. Accordingly, claims 1-20 are rejected under 35 USC. 101 as being directed to non-statutory subject matter.
6. NOTE: Currently there are no outstanding prior art rejections under 35 USC § 102 or 35 USC§ 103.
7. The claims would be allowable if overcome the 35 USC § 101 rejection.
Conclusion
8. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. As per attached PTO 892 form.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ROMAIN JEANTY whose telephone number is (571) 272-6732. The examiner can normally be reached M-F 9:00AM to 5:30PM.
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, Jerry O'Connor can be reached at 571 272-6787. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
Information regarding the status of published or unpublished applications may be obtained from Patent Center. Unpublished application information in Patent Center is available to registered users. To file and manage patent submissions in Patent Center, visit: https://patentcenter.uspto.gov. Visit https://www.uspto.gov/patents/apply/patent-center for more information about Patent Center and https://www.uspto.gov/patents/docx for information about filing in DOCX format. For additional questions, contact the Electronic Business Center (EBC) at 866-217-9197 (toll-free). If you would like assistance from a USPTO Customer Service Representative, call 800-786-9199 (IN USA OR CANADA) or 571-272-1000.
/RJ/
/ROMAIN JEANTY/Primary Examiner, Art Unit 3624