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 .
The following is a Final Office Action in response to communications received on 1/20/2026. Claims 1-20 are currently pending and have been examined. Claims 1-12, 14-16 and 18-20 have been amended.
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.
Step 1: The claims 1-8 are a method, claims 9-14 are a system, and claims 15-20 are a computer readable medium. Thus, each independent claim, on its face, is directed to one of the statutory categories of 35 U.S.C. §101. However, the claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 2A Prong 1: The independent claims (1, 9 and 15, taking claim 1 as a representative claim) recite:
receiving, at a computing device in a network, a user input from a user computing device;
extracting, by the computing device, a query from the user input, the query being representative of an objective defined based on the user input;
identifying, by the computing device, at least one category of services of a plurality of categories of services based on the query;
generating, by the computing device, a user profile representative of the query and one or more preferences of the user;
refining the query based on the one or more preferences of the user profile;
retrieving, by the computing device, data corresponding to services in the identified at least one category from corresponding data sources based on the refined query and generating a service profile for each respective service based on the retrieved data;
determining, by the computing device, a match between the user profile and each of the service profiles;
generating, by the computing device in response to the query, an output dataset comprising one or more service profiles from the generated service profiles based on the matching;
and sending the one or more service profiles of the output dataset to the user computing device responsive to the query, wherein the refined query is configured to close a gap between the user profile and the services in the at least one category by refining the data retrieved from the corresponding data sources.
These limitations, except for the italicized portions, under their broadest reasonable interpretations, recite certain methods of organizing human activity for managing personal behavior or relationships or interactions between people (including social activities, teaching, and following rules or instructions) as well as commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations). The claimed invention recites steps for generating a profile for a user based on their specific tastes and preferences derived from inputs received from the user. Matches between the user and service profiles are determined. From applicant’s specification, the claimed invention is implemented to improve the recommendations returned a user (see at least [0011-15] of the instant application). The steps under its broadest reasonable interpretation specifically fall under sales/marketing activities. The Examiner notes that although the claim limitations are summarized, the analysis regarding subject matter eligibility considers the entirety of the claim and all of the claim elements individually, as a whole, and in ordered combination.
Prong 2: This judicial exception is not integrated into a practical application. In particular, the claims recite the additional elements of
at a computing device in a network (claim 1)
user computing device (claim 1)
A system comprising: a processor; and a non-transitory computer readable media having stored thereon instructions that are executable by the processor to perform operations comprising: (claim 9)
A non-transitory computer readable media having stored thereon instructions that are executable by a system to perform operations comprising: (claim 15)
The additional elements above are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function of processing data) such that it amounts no more than mere instructions to apply the exception using a generic computer component. The limitations do not impose any meaningful limits on practicing the abstract idea, and therefore do not integrate the abstract idea into a practical application – MPEP 2106.05(f).
Accordingly, these additional elements when considered individually or as a whole do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The independent claims are directed to an abstract idea.
Step 2B: The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception. As discussed with respect to Step 2A Prong two, the additional elements in the claims amount to no more than mere instructions to apply the judicial exception using a generic computer component.
Even when considered as an ordered combination, the additional elements of claim 1, 9, and 15 do not add anything that is not already present when they are considered individually. Therefore, under Step 2B, there are no meaningful limitations in claims 1, 9, and 15 that transform the judicial exception into a patent eligible application such that the claims amount to significantly more than the judicial exception itself (see MPEP 2106.05).
As such, independent claims 1, 9, and 15 are ineligible.
Dependent claims 2-8, 10-14, and 16-20 when analyzed as a whole, are held to be patent ineligible under 35 U.S.C. §101 because the additional recited limitations fail to establish that the claims are not directed to the same abstract idea of Independent Claims 1, 9 and 15 without significantly more.
Claim 2 recites wherein generating the user profile representative of the query and the one or more preferences of the user further comprises: retrieving, by the computing device, data including the one or more preferences of the user from a first data store; and wherein the extracted query is representative of a defined objective of the user to retrieve relevant data used to populate the service profile of each respective service, wherein the one or more preferences of the user are based on at least one of: the user inputs or inferred from historical data of the user. The limitation merely further limits the abstract idea. While the limitation recites the additional element of a data store, it is recited at a high level of generality and does not integrate the judicial exception into a practical application.
Claim 3 recites further comprising: determining, by a machine learning model, a first set of embeddings representative of the user profile, extracting, by the computing device, a second set of embeddings representative of the respective service profile based on the retrieved data, and applying, by the computing device, a distance metric to determine a match between the first set of embeddings representative of the user profile and the second set of embeddings representative of the respective service profile.The limitation merely further limits the abstract idea. While the limitation recites the additional element of a machine learning model, it is recited at a high level of generality and does not integrate the judicial exception into a practical application.
Claim 4 recites wherein the distance metric is a similarity score calculatedbased on the first set of embeddings representative of the user profile and the second set of embeddings representative of the respective service profile. The limitation merely further limits the abstract idea and does not integrate the judicial exception into a practical application.
Claim 5 recites wherein retrieving the data corresponding to the services in the identified at least one category from the corresponding data sources further comprises: determining, by the computing device, a status of the retrieved data corresponding to the services, wherein the status is determined based on timestamp data representative of a most recent update to the retrieved data. The limitation merely further limits the abstract idea and does not integrate the judicial exception into a practical application.
Claim 6 recites wherein the services correspond to at least one of service of a third party service provider, a location, or an objective. The limitation merely further limits the abstract idea and does not integrate the judicial exception into a practical application.
Claim 7 recites wherein the user input corresponds to a request for services in the at least one category. The limitation merely further limits the abstract idea and does not integrate the judicial exception into a practical application.
Claim 8 recites wherein the corresponding data source are located in one or more other networks external to the network of the computing device. The limitation merely further limits the abstract idea. While the limitation recites one or more other networks, it is recited at a high level of generality and does not integrate the judicial exception into a practical application.
Claims 10-14 and 16-20 recite parallel claim language and therefore are rejected for the reasons set forth above. Claims 1-20 are therefore rejected under 35 USC 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, 2, 6, 7, 9, and 13 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Catino (US 20230360099).
Regarding claims 1 and 9, Catino discloses:
A method (claim 1)
A system comprising: a processor; and a non-transitory computer readable media having stored thereon instructions that are executable by the processor to perform operations comprising: (claim 9) [Figure 1 element 100]
receiving, at a computing device in a network (communications device 120 and communications network 130), a user input from a user computing device; (service user interface 120 with search area 1200 for entering keyword search in Figure 12 and [0080] a search executed by the service user 142)
extracting, by the computing device, a query from the user input, the query being representative of an objective defined based on the user input; [0079] FIG. 12 depicts an example search screen 1200 through which a service user 142 can search for service providers 144. In the illustrated embodiment, a variety of different search options are provided through the search screen 1200, including a keyword search 1202 and a category search 1204. A search history 1206 can allow the service user 142 to recall previously executed searches and re-run the search or modify one or more of the search parameters prior to re-running the search. Since service providers 144 can update skills and preferences in real-time and may be traveling, the same search executed at two different points in time can yield much different results. and see [0051-0052]
identifying, by the computing device, at least one category of services of a plurality of categories of services based on the query;[0051] The quick search module 202 can be configured to allow a service user 142 to repeat a service request they made in the past with the same preferences (e.g., a quick search), thus creating a repeat search for providers based on recent searches. Another feature of the quick search can allow for the service user 142 to select a previous request and edit the preferences, thus creating a new search with similar but not identical preferences as the previous search. Another feature of the quick search can allow for the selection of specific service providers and subsequently, scheduling service requests in the coming days. [0052] The request new services module 204 can be configured to generate an interactive search bar that gives suggestions for specific labor types, by category, as the service user types based on popular searches and past user search history. This module can also include a category list with multiple sub-categories that can assist with a service user 142 narrowing their search down to a specific labor type. Once a service user 142 has selected the desired type of labor, they can answer job-specific questions.
generating, by the computing device, a user profile representative of the query and one or more preferences of the user; [0020] As described in more detail below, an LME in accordance with the presently disclosed systems, methods, and apparatuses can enable users, both commercial and/or non-commercial, in need of a service to quickly and conveniently match with a service provider on either a scheduled or an on-demand basis. Matches between a service user and a service provider can be based on any number of factors and/or parameters, such as service user preferences, job details, and preferences and background of the service providers. [0048] In some embodiments, to further build the profile of the service user 142, the service user 142 can then be asked to answer general preference questions or otherwise provide additional information to provide the LME computing system 102 with additional data to aid in the subsequent matching of service providers 144.
refining the query based on the one or more preferences of the user profile; [0020] As described in more detail below, an LME in accordance with the presently disclosed systems, methods, and apparatuses can enable users, both commercial and/or non-commercial, in need of a service to quickly and conveniently match with a service provider on either a scheduled or an on-demand basis. Matches between a service user and a service provider can be based on any number of factors and/or parameters, such as service user preferences, job details, and preferences and background of the service providers. [0048] In some embodiments, to further build the profile of the service user 142, the service user 142 can then be asked to answer general preference questions or otherwise provide additional information to provide the LME computing system 102 with additional data to aid in the subsequent matching of service providers 144. and see [0086] The service query comprises a plurality of query parameters, wherein the query parameters can comprise a geolocation parameter and a service type parameter. At block 1906, at least one of the service providers is identified to the service user. The identification can be based on the service provider profile data, the query parameters, and a geolocation position associated with the at least one service provider.
retrieving, by the computing device, data corresponding to services in the identified at least one category from corresponding data sources based on the refined query and generating a service profile for each respective service based on the retrieved data; [0072] The skills section 506 can include, without limitation, selections of particular skills or abilities possessed by the service provider 144. These skills can be used by the LME computing system 102 when matching particular service providers 144 to search queries. The certifications section 508 can include, for example, licenses (e.g., commercial driver's license (CDL)) or other certifications (e.g., home inspector certification, OSHA certification). The preferences section 510 can include, for example, labor preferences that have been provided by the service provider 144 to the LME computing system 102. These preferences can be updated in real time by the service provider 144 and can be used by the LME computing system 102 when matching particular service providers 144 to search queries.
determining, by the computing device, a match between the user profile and each of the service profiles; [0020] As described in more detail below, an LME in accordance with the presently disclosed systems, methods, and apparatuses can enable users, both commercial and/or non-commercial, in need of a service to quickly and conveniently match with a service provider on either a scheduled or an on-demand basis. Matches between a service user and a service provider can be based on any number of factors and/or parameters, such as service user preferences, job details, and preferences and background of the service providers.
generating, by the computing device in response to the query, an output dataset comprising one or more service profiles from the generated service profiles based on the matching; [0086] FIG. 19 is a simplified flow diagram 1900 of at least one embodiment of a method for matching a service provider to a service user that can be executed by the LME computing system 102 of FIGS. 1 and 2. At block 1902, service provider profile data is received from each of a plurality of service providers. The service provider profile data can comprise at least one type of service offering. At block 1904, a service query is received from a service user. The service query comprises a plurality of query parameters, wherein the query parameters can comprise a geolocation parameter and a service type parameter. At block 1906, at least one of the service providers is identified to the service user. The identification can be based on the service provider profile data, the query parameters, and a geolocation position associated with the at least one service provider. At block 1908, a selection of one of the identified service providers is received from the service user. At block 1910, a service request is transmitted to the selected service provider. At block 1912, an acceptance of the service request is received from the selected service provider. At 1914, it is determined whether the current time is within the pre-appointment time window. When the current time is determined to be within the pre-appointment time window, at block 1916, real-time geolocation information of the identified service provider is received and provided to the service user at block 1918. and see [0024]
and sending the one or more service profiles of the output dataset to the user computing device responsive to the query, wherein the refined query is configured to close a gap between the user profile and the services in the at least one category by refining the data retrieved from the corresponding data sources. [0080] FIG. 13 depicts an example search results screen 1300 resulting from a search executed by the service user 142. A list of identified service providers 1302 can be graphically presented on the search results screen 1300.
The examiner notes that the language "wherein the refined query is configured to close a gap between the user profile and the services in the at least one category by refining the data retrieved from the corresponding data sources. " is merely intended use language and therefore given little patentable weight. However, the language has been addressed in the prior art rejection.
Regarding claim 2, Catino discloses the limitations set forth above. Catino further discloses:
wherein generating the user profile representative of the query and the one or more preferences of the user further comprises: retrieving, by the computing device,[0038] Data used by the marketplace exchange engine 112 can be from various data sources 110, such as a user profiles database 132 and [0048] In some embodiments, to further build the profile of the service user 142, the service user 142 can then be asked to answer general preference questions or otherwise provide additional information to provide the LME computing system 102 with additional data to aid in the subsequent matching of service providers 144. wherein the extracted query is representative of a defined objective of the user to retrieve relevant data [0079] FIG. 12 depicts an example search screen 1200 through which a service user 142 can search for service providers 144. In the illustrated embodiment, a variety of different search options are provided through the search screen 1200, including a keyword search 1202 and a category search 1204. A search history 1206 can allow the service user 142 to recall previously executed searches and re-run the search or modify one or more of the search parameters prior to re-running the search. Since service providers 144 can update skills and preferences in real-time and may be traveling, the same search executed at two different points in time can yield much different results. and see [0051-0052] used to populate the service profile of each respective service, [0072] The skills section 506 can include, without limitation, selections of particular skills or abilities possessed by the service provider 144. These skills can be used by the LME computing system 102 when matching particular service providers 144 to search queries. The certifications section 508 can include, for example, licenses (e.g., commercial driver's license (CDL)) or other certifications (e.g., home inspector certification, OSHA certification). The preferences section 510 can include, for example, labor preferences that have been provided by the service provider 144 to the LME computing system 102. These preferences can be updated in real time by the service provider 144 and can be used by the LME computing system 102 when matching particular service providers 144 to search queries. wherein the one or more preferences of the user are based on at least one of: the user inputs or inferred from historical data of the user. [0048] In some embodiments, to further build the profile of the service user 142, the service user 142 can then be asked to answer general preference questions or otherwise provide additional information to provide the LME computing system 102 with additional data to aid in the subsequent matching of service providers 144.
Regarding claim 6, Catino discloses the limitations set forth above. Catino further discloses:
wherein the services correspond to at least one of: a service of a third party service provider, a location, or an objective. [0086] FIG. 19 is a simplified flow diagram 1900 of at least one embodiment of a method for matching a service provider to a service user that can be executed by the LME computing system 102 of FIGS. 1 and 2. At block 1902, service provider profile data is received from each of a plurality of service providers. The service provider profile data can comprise at least one type of service offering. At block 1904, a service query is received from a service user. The service query comprises a plurality of query parameters, wherein the query parameters can comprise a geolocation parameter and a service type parameter. At block 1906, at least one of the service providers is identified to the service user. and see [0024]
Regarding claims 7 and 13, Catino discloses the limitations set forth above. Catino further discloses:
wherein the user input corresponds to a request for services in the at least one category. [0052] The request new services module 204 can be configured to generate an interactive search bar that gives suggestions for specific labor types, by category, as the service user types based on popular searches and past user search history. This module can also include a category list with multiple sub-categories that can assist with a service user 142 narrowing their search down to a specific labor type. Once a service user 142 has selected the desired type of labor, they can answer job-specific questions.
Claim Rejections - 35 USC § 103
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 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, 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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 3, 15, 16, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Catino (US 20230360099) in view of Minaudo (US 20230075116).
Regarding claim 3, Catino discloses the limitations set forth above. While Catino discloses the user profile for the service user and profile of the service provide and determining a match between the service user and service provider, the reference does not expressly disclose:
determining, by a machine learning model, a first set of embeddings representative of the user profile,
extracting, by the computing device, a second set of embeddings representative of the respective service profile based on the retrieved data, and
applying, by the computing device, a distance metric to determine a match between the first set of embeddings representative of the user profile and the second set of embeddings representative of the respective service profile.
However Minaudo teaches:
determining, by a machine learning model, a first set of embeddings representative of the user profile, [0060] Machine learning processor 130 is configured to generate at least one node embedding. A node embedding is generated based on one or more NER entities from the input received from the requester's request. And see [0027]
extracting, by the computing device, a second set of embeddings representative of the respective service profile based on the retrieved data, and [0061] Requestee parameters (e.g., attributes related to the requestee) represented in a node or node embeddings are combined by machine learning processor 130 under at least one node embedding.
applying, by the computing device, a distance metric to determine a match between the first set of embeddings representative of the user profile and the second set of embeddings representative of the respective service profile.[0065] determines a probability determined by neural network that the requester's request matches the requestees parameters
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the query data of Catino to include determining, by a machine learning model, a first set of embeddings representative of the user profile, extracting, by the computing device, a second set of embeddings representative of the respective service profile based on the retrieved data, andapplying, by the computing device, a distance metric to determine a match between the first set of embeddings representative of the user profile and the second set of embeddings representative of the respective service profile, as taught in Minaudo, in order to optimize the returned results through implementation of the probability calculation (see paragraph 0027).
Regarding claim 15, Catino discloses:
A non-transitory computer readable media having stored thereon instructions that are executable by a system to perform operations comprising: [0038]
receive a user input from a user computing device; (service user interface 120 with search area 1200 for entering keyword search in Figure 12 and [0080] a search executed by the service user 142; (communications device 120 and communications network 130)
extract a query based on data from the user input; [0079] FIG. 12 depicts an example search screen 1200 through which a service user 142 can search for service providers 144. In the illustrated embodiment, a variety of different search options are provided through the search screen 1200, including a keyword search 1202 and a category search 1204. A search history 1206 can allow the service user 142 to recall previously executed searches and re-run the search or modify one or more of the search parameters prior to re-running the search. Since service providers 144 can update skills and preferences in real-time and may be traveling, the same search executed at two different points in time can yield much different results. and see [0051-0052]
identify at least one category of services of a plurality of service categories based on the user input; [0051] The quick search module 202 can be configured to allow a service user 142 to repeat a service request they made in the past with the same preferences (e.g., a quick search), thus creating a repeat search for providers based on recent searches. Another feature of the quick search can allow for the service user 142 to select a previous request and edit the preferences, thus creating a new search with similar but not identical preferences as the previous search. Another feature of the quick search can allow for the selection of specific service providers and subsequently, scheduling service requests in the coming days. [0052] The request new services module 204 can be configured to generate an interactive search bar that gives suggestions for specific labor types, by category, as the service user types based on popular searches and past user search history. This module can also include a category list with multiple sub-categories that can assist with a service user 142 narrowing their search down to a specific labor type. Once a service user 142 has selected the desired type of labor, they can answer job-specific questions.
[…] the user profile including preferences of the user and the query; [0020] As described in more detail below, an LME in accordance with the presently disclosed systems, methods, and apparatuses can enable users, both commercial and/or non-commercial, in need of a service to quickly and conveniently match with a service provider on either a scheduled or an on-demand basis. Matches between a service user and a service provider can be based on any number of factors and/or parameters, such as service user preferences, job details, and preferences and background of the service providers. [0048] In some embodiments, to further build the profile of the service user 142, the service user 142 can then be asked to answer general preference questions or otherwise provide additional information to provide the LME computing system 102 with additional data to aid in the subsequent matching of service providers 144.
refine the query based on the preferences of the user in the user profile; [0020] As described in more detail below, an LME in accordance with the presently disclosed systems, methods, and apparatuses can enable users, both commercial and/or non-commercial, in need of a service to quickly and conveniently match with a service provider on either a scheduled or an on-demand basis. Matches between a service user and a service provider can be based on any number of factors and/or parameters, such as service user preferences, job details, and preferences and background of the service providers. [0048] In some embodiments, to further build the profile of the service user 142, the service user 142 can then be asked to answer general preference questions or otherwise provide additional information to provide the LME computing system 102 with additional data to aid in the subsequent matching of service providers 144. and see [0086] The service query comprises a plurality of query parameters, wherein the query parameters can comprise a geolocation parameter and a service type parameter. At block 1906, at least one of the service providers is identified to the service user. The identification can be based on the service provider profile data, the query parameters, and a geolocation position associated with the at least one service provider.
retrieve data corresponding to services in the identified at least one category of services from at least one data source and generating a service profile for each respective service based on the retrieved data; [0072] The skills section 506 can include, without limitation, selections of particular skills or abilities possessed by the service provider 144. These skills can be used by the LME computing system 102 when matching particular service providers 144 to search queries. The certifications section 508 can include, for example, licenses (e.g., commercial driver's license (CDL)) or other certifications (e.g., home inspector certification, OSHA certification). The preferences section 510 can include, for example, labor preferences that have been provided by the service provider 144 to the LME computing system 102. These preferences can be updated in real time by the service provider 144 and can be used by the LME computing system 102 when matching particular service providers 144 to search queries.
determine a match between the user profile and each service profile; and [0020] As described in more detail below, an LME in accordance with the presently disclosed systems, methods, and apparatuses can enable users, both commercial and/or non-commercial, in need of a service to quickly and conveniently match with a service provider on either a scheduled or an on-demand basis. Matches between a service user and a service provider can be based on any number of factors and/or parameters, such as service user preferences, job details, and preferences and background of the service providers.
sending an output dataset comprising one or more service profiles to the user computing device responsive to the query, wherein the refined query is configured to close a gap between the user profile and the services in the at least one category by refining the data retrieved from the corresponding data sources. [0080] FIG. 13 depicts an example search results screen 1300 resulting from a search executed by the service user 142. A list of identified service providers 1302 can be graphically presented on the search results screen 1300.
The examiner notes that the language "wherein the refined query is configured to close a gap between the user profile and the services in the at least one category by refining the data retrieved from the corresponding data sources. " is merely intended use language and therefore given little patentable weight. However, the language has been addressed in the prior art rejection.
While Catino discloses the user profile for the service user and profile of the service provide and determining a match between the service user and service provider, the reference does not expressly disclose:
determine a first set of embeddings representative of a user profile,
However Minaudo teaches:
determine a first set of embeddings representative of a user profile, [0060] Machine learning processor 130 is configured to generate at least one node embedding. A node embedding is generated based on one or more NER entities from the input received from the requester's request. And see [0027]
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the query data of Catino to include determine a first set of embeddings representative of a user profile, as taught in Minaudo, in order to optimize the returned results through implementation of the probability calculation (see paragraph 0027).
Regarding claim 16, Catino in view of Minaudo teaches the limitations set forth above.
Catino further discloses:
wherein the preferences of the user are based on at least one of: the user input or inferred from historical data of the user. [0048] In some embodiments, to further build the profile of the service user 142, the service user 142 can then be asked to answer general preference questions or otherwise provide additional information to provide the LME computing system 102 with additional data to aid in the subsequent matching of service providers 144.
While Catino discloses the user profile for the service user and profile of the service provide and determining a match between the service user and service provider, the reference does not expressly disclose:
executable by the system further comprises: extract a second set of embeddings representative of a respective service profile, and
apply a distance metric to determine a match between the user profile and the respective service profile based on the first set of embeddings and the second set of embeddings
However Minaudo teaches:
executable by the system further comprises: extract a second set of embeddings representative of a respective service profile, and [0061] Requestee parameters (e.g., attributes related to the requestee) represented in a node or node embeddings are combined by machine learning processor 130 under at least one node embedding.
apply a distance metric to determine a match between the user profile and the respective service profile based on the first set of embeddings and the second set of embeddings [0065] determines a probability determined by neural network that the requester's request matches the requestees parameters
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the query data of Catino to include executable by the system further comprises: extract a second set of embeddings representative of a respective service profile, and apply a distance metric to determine a match between the user profile and the respective service profile based on the first set of embeddings and the second set of embeddings, as taught in Minaudo, in order to optimize the returned results through implementation of the probability calculation (see paragraph 0027).
Regarding claim 20, Catino in view of Minaudo teaches the limitations set forth above.
Catino further discloses:
wherein the services correspond to at least one of: a service of a third party service provider, a location, or an objective. [0086] FIG. 19 is a simplified flow diagram 1900 of at least one embodiment of a method for matching a service provider to a service user that can be executed by the LME computing system 102 of FIGS. 1 and 2. At block 1902, service provider profile data is received from each of a plurality of service providers. The service provider profile data can comprise at least one type of service offering. At block 1904, a service query is received from a service user. The service query comprises a plurality of query parameters, wherein the query parameters can comprise a geolocation parameter and a service type parameter. At block 1906, at least one of the service providers is identified to the service user. and see [0024]
Claims 4, 12, and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Catino (US 20230360099) in view of Minaudo (US 20230075116) in further view of Liu (US 20190325081).
Regarding claim 4, Catino in view of Minaudo teaches the limitations set forth above. While Catino discloses the user profile for the service user and profile of the service provide and determining a match between the service user and service provider and Minaudo teaches requestee parameters (e.g., attributes related to the requestee) represented in a node or node embeddings are combined by machine learning processor under at least one node embedding, the reference combination does not expressly disclose:
wherein the distance metric is a similarity score calculated based on the first set of embeddings representative of the user profile and the second set of embeddings representative of the respective service profile.
However Liu teaches:
wherein the distance metric is a similarity score calculated based on the first set of embeddings representative of the user profile and the second set of embeddings representative of the respective service profile. [0082] In particular embodiments, the social-networking system 160 may calculate a similarity metric of vectors in vector space 700. A similarity metric may be a cosine similarity, a Minkowski distance, a Mahalanobis distance, a Jaccard similarity coefficient, or any suitable similarity metric. […] A similarity metric of two vectors may represent how similar the two objects or n-grams corresponding to the two vectors, respectively, are to one another, as measured by the distance between the two vectors in the vector space 700. As an example and not by way of limitation, vector 710 and vector 720 may correspond to objects that are more similar to one another than the objects corresponding to vector 710 and vector 730, based on the distance between the respective vectors.
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the query data of Catino in view of the embedding techniques of Minaudo to wherein the distance metric is a similarity score calculated based on the first set of embeddings representative of the user profile and the second set of embeddings representative of the respective service profile, as taught in Liu, in order to generate a personalized set of content objects to display to a user, such as a newsfeed of aggregated stories of other users connected to the user (see paragraph 005).
Claim 10 recites substantially parallel claim language to claims 1, 3, and 4 and therefore is rejected under Catino in view of Minaudo in further view of Liu.
Claim 12 recites substantially parallel claim language to claim 6 and depends from claim 10 and therefore is rejected under Catino in view of Minaudo in further view of Liu.
Claim 17 recites substantially parallel claim language to claim 4 and therefore is rejected under Catino in view of Minaudo in further view of Liu.
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Catino (US 20230360099) in view of Duan (US 20210224750).
Regarding claim 5, Catino discloses the limitations set forth above. While Catino discloses the retrieving of data corresponding to service providers, the reference does not expressly disclose:
wherein retrieving the data corresponding to the services in the identified at least one category from the corresponding data sources further comprises:
determining, by the computing device, a status of the retrieved data corresponding to the services, wherein the status is determined based on timestamp data representative of a most recent update to the retrieved data.
However Duan teaches:
wherein retrieving the data corresponding to the services in the identified at least one category from the corresponding data sources further comprises: determining, by the computing device, a status of the retrieved data corresponding to the services, wherein the status is determined based on timestamp data representative of a most recent update to the retrieved data. [0052] To control for confounding factors represented by job segments 228, the component calculates labels 212 based on user activity 220 associated with jobs in different job segments 228. For example, the component determines impression volumes, CTRs, application rates, response rates, and/or other measures of user engagement for a job at different points after the job has been posted (e.g., one week after posting, two weeks after posting, etc.). Such measures can be calculated by aggregating different types of user activity 220 over various time periods (e.g., daily, weekly, the first week after a job is posted, the second week after the job is posted, etc.)
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the retrieving of data regarding the service providers of Catino to include wherein retrieving the data corresponding to the services in the identified at least one category from the corresponding data sources further comprises: determining, by the computing device, a status of the retrieved data corresponding to the services, wherein the status is determined based on timestamp data representative of a most recent update to the retrieved data, as taught in Duan, in order to connect and enhance an online network of individuals through the user of improved data and features (paragraph 003).
Claim 11 is rejected under 35 U.S.C. 103 as being unpatentable over Catino (US 20230360099) in view of Minaudo (US 20230075116) in view of Liu (US 20190325081) in further view of Duan (US 20210224750).
Regarding claim 11, Catino in view of Minaudo in view of Liu teaches the limitations set forth above. While Catino discloses the retrieving of data corresponding to service providers, the reference does not expressly disclose:
wherein retrieving the data corresponding to the services of the identified category from the at least one data source further comprises:
determine a status of the retrieved data corresponding to the services, wherein the status is determined based on timestamp data representative of a most recent update to the retrieved data.
However Duan teaches:
wherein retrieving the data corresponding to the services of the identified category from the at least one data source further comprises: determine a status of the retrieved data corresponding to the services, wherein the status is determined based on timestamp data representative of a most recent update to the retrieved data. [0052] To control for confounding factors represented by job segments 228, the component calculates labels 212 based on user activity 220 associated with jobs in different job segments 228. For example, the component determines impression volumes, CTRs, application rates, response rates, and/or other measures of user engagement for a job at different points after the job has been posted (e.g., one week after posting, two weeks after posting, etc.). Such measures can be calculated by aggregating different types of user activity 220 over various time periods (e.g., daily, weekly, the first week after a job is posted, the second week after the job is posted, etc.)
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the retrieving of data regarding the service providers of Catino in view of Minaudo in view of Liu to include wherein retrieving the data corresponding to the services in the identified at least one category from the corresponding data sources further comprises: determining, by the computing device, a status of the retrieved data corresponding to the services, wherein the status is determined based on timestamp data representative of a most recent update to the retrieved data, as taught in Duan, in order to connect and enhance an online network of individuals through the user of improved data and features (paragraph 003).
Claims 8 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Catino (US 20230360099) in view of Pingol (US 20210049220).
Regarding claim 8 and 14, Catino discloses the limitations set forth above. While Catino discloses data sources corresponding to the service providers, the reference does not expressly disclose:
wherein the corresponding data sources are located in one or more other networks external to the network of the computing device.
However Pingol teaches:
wherein the corresponding data sources are located in one or more other networks external to the network of the computing device. [0058] In embodiments, profile inputs 402 can be received via manually entry, or programmatically from one or more external data sources 202. In embodiments, profile creation engine 400 can provide one or more assessments, questionnaires or forms that can be presented to a user via user interface engine 102 for entry of inputs 402. Profile creation engine 400 can, in embodiments, comprise hardware and software configured to automatically scrape or crawl one or more network accessible sources of input data such as government websites, business profiles, job posting services third-party intelligence sources, or other external data sources 302, and the like in order to discover inputs 402. In an embodiment, a profile creation application programming interface API can be presented by profile creation engine 400. The profile creation API can comprise software and/or hardware interfaces enabling programmatic input of profile inputs 402.
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the data sources corresponding to the service providers of Catino to include wherein the corresponding data sources are located in one or more other networks external to the network of the computing device, as taught in Pingol, in order to provide consistent references to identifying goods and services for service providers and service seekers (paragraph 003).
Claim 18 is rejected under 35 U.S.C. 103 as being unpatentable over Catino (US 20230360099) in view of Minaudo (US 20230075116) in further view of Pingol (US 20210049220).
Regarding claim 18, Catino in view of Minaudo teaches the limitations set forth above. While Catino discloses data sources corresponding to the service providers, the combination of references does not expressly disclose:
obtain the data corresponding to the services in the identified at least one category from one or more other networks externally located relative to a network of the system, and store the service profiles in the identified at least one category in a data store.
However Pingol teaches:
obtain the data corresponding to the services in the identified at least one category from one or more other networks externally located relative to a network of the system, [0058] In embodiments, profile inputs 402 can be received via manually entry, or programmatically from one or more external data sources 202. In embodiments, profile creation engine 400 can provide one or more assessments, questionnaires or forms that can be presented to a user via user interface engine 102 for entry of inputs 402. Profile creation engine 400 can, in embodiments, comprise hardware and software configured to automatically scrape or crawl one or more network accessible sources of input data such as government websites, business profiles, job posting services third-party intelligence sources, or other external data sources 302, and the like in order to discover inputs 402. In an embodiment, a profile creation application programming interface API can be presented by profile creation engine 400. The profile creation API can comprise software and/or hardware interfaces enabling programmatic input of profile inputs 402.
and store the service profiles in the identified at least one category in a data store. [0044] Data store 200 can comprise one or more database, file systems, memories, or other data storage systems known in the art. Data store 200 can comprise a single data store, present on a single computing device in an embodiment. In other embodiments, data store 200 may be present on one or more database systems physically separate from other components of system 100. In other embodiments, data store 200 may be present distributed across multiple separate computing devices, each with associated data stores. In embodiments, data store 200 may comprise one or more relational databases with tabular structure, NoSQL, or other non-relational databases with key-value, grid, or other structures. Data store 200 may comprise one or more flat files such as text files, binary files, image files, or any other file type.
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the data sources corresponding to the service providers of Catino in view of Minaudo to include obtain the data corresponding to the services in the identified at least one category from one or more other networks externally located relative to a network of the system, and store the service profiles in the identified at least one category in a data store, as taught in Pingol, in order to provide consistent references to identifying goods and services for service providers and service seekers (paragraph 003).
Claim 19 is rejected under 35 U.S.C. 103 as being unpatentable over Catino (US 20230360099) in view of Minaudo (US 20230075116) in view of Pingol (US 20210049220) in further view of Duan (US 20210224750).
Regarding claim 19, Catino in view of Minaudo in view of Pingol teaches the limitations set forth above. While Catino discloses data sources corresponding to the service providers, the combination of references does not expressly disclose:
determine a status of the retrieved data corresponding to the services;
update the data of the service profiles in the data store in response to determining the status exceeds a threshold value;
and wherein the status is determined based on timestamp data representative of a most recent update to the data, wherein the data store is located in the network of the system.
However Duan teaches:
determine a status of the retrieved data corresponding to the services; update the data of the service profiles in the data store in response to determining the status exceeds a threshold value; and wherein the status is determined based on timestamp data representative of a most recent update to the data, [0052] To control for confounding factors represented by job segments 228, the component calculates labels 212 based on user activity 220 associated with jobs in different job segments 228. For example, the component determines impression volumes, CTRs, application rates, response rates, and/or other measures of user engagement for a job at different points after the job has been posted (e.g., one week after posting, two weeks after posting, etc.). Such measures can be calculated by aggregating different types of user activity 220 over various time periods (e.g., daily, weekly, the first week after a job is posted, the second week after the job is posted, etc.) wherein the data store is located in the network of the system. [0051]
Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the retrieving of data regarding the service providers of Catino in view of Minaudo to include determine a status of the retrieved data corresponding to the services; update the data of the service profiles in the data store in response to determining the status exceeds a threshold value; and wherein the status is determined based on timestamp data representative of a most recent update to the data, wherein the data store is located in the network of the system, as taught in Duan, in order to connect and enhance an online network of individuals through the user of improved data and features (paragraph 003).
Response to Arguments
Applicant's arguments filed 1/20/2026 have been fully considered but they are not persuasive.
With respect to the remarks directed to 35 USC 101, “The claim as a whole integrated the abstract idea into a practical application under Step 2A, Prong 2, the examiner first asserts the consideration as to whether the claims are directed to an abstract idea and whether the claims are integrated into a practical application are separation considerations. Under prong 1, the examiner has determined the claims are directed to an abstract idea. As shown in the analysis above, the claimed invention recites steps for generating a profile for a user based on their specific tastes and preferences derived from inputs received from the user. Matches between the user and service profiles are determined. From applicant’s specification, the claimed invention is implemented to improve the recommendations returned a user (see at least [0011-15] of the instant application). The steps under its broadest reasonable interpretation specifically fall under sales/marketing activities. The claims as amended still are directed to this abstract idea.
Under prong 2 considerations, the examiner asserts that alleged improvement of providing service profiles as an output recommendation based on the provided query input at most recites an alleged improvement to the abstract idea, not the technology itself. The data described in [0012] at most is improved data that is fed into the determination and thereby the abstract idea is improved, not the technology. If the data is improved the recommendation is improved by consequence of the improved dataset. This is part of the abstract idea.
With respect to the remarks directed to 35 USC 101, “The additional limitations recited significantly more than the abstract idea under step 2B”, the examiner asserts that neither the analysis above nor the analysis of the amended claims consider the additional elements to be well understood, routine, and conventional. Thereby, the remarks directed to this type of Berkheimer analysis are considered moot. The examiner did consider the claim limitations as a whole under step 2B and concluded the claims still do not integrate the judicial exception into a practical application.
For at least these reasons the claims remain rejected under 35 USC 101.
With respect to the remarks directed to 35 USC 103, the examiner first asserts that the prior art reference Duan is no longer relied upon for the teaching of the independent claims. The reference is only applied to claim 5 (and parallel claims) as an additional reference in the newly applied 35 USC 103 rejection. Therefore, the remarks directed to Duan with respect to the independent claims are considered moot. With respect to Minaudo, the reference is no longer applied to the limitation of refining the query based on the one or more preferences of the user profile and therefore the remarks directed to this limitation are considered moot. The independent claims remain rejected under the newly cited prior art Citano and Pingol. While Minaudo, Duan, and Liu are still relied upon, the previous prior art rejection is no longer relied upon to teach the claims as amended nor relied upon of the argued limitations.
Relevant Art Not Cited
Oretega (US 20200401908) personalize content based on created user profile embeddings
VIJAYARAGHAVAN (US 20140207622) identifying user intent of searches and returning personalized results.
“Search Personalization with Embeddings” which discloses an embedding approach to learning user profiles, where users are embedded on a topical interest space. We then directly utilize the user profiles for search personalization. Experiments on query logs from a major commercial web search engine demonstrate that our embedding approach improves the performance of the search engine and also achieves better search performance than other strong baselines. (Abstract)
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 VICTORIA E. FRUNZI whose telephone number is (571)270-1031. The examiner can normally be reached Monday- Friday 7-4 (EST).
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, Marissa Thein can be reached at (571) 272-6764. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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VICTORIA E. FRUNZI
Primary Examiner
Art Unit TC 3689
/VICTORIA E. FRUNZI/Primary Examiner, Art Unit 3689 3/26/2026