DETAILED ACTION
1. Claims 1-20 are pending.
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 .
Information Disclosure Statement
2. The information disclosure statement (IDS) submitted on 10/20/2023 is in compliance with the provisions of 37 CFR 1.97. Accordingly, the information disclosure statement is being considered by the examiner.
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.
3. Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention recites a judicial exception, is directed to that judicial exception, an abstract idea, as it has not been integrated into practical application and the claims further do not recite significantly more than the judicial exception. Examiner has evaluated the claims under the framework provided in the 2019 Patent Eligibility Guidance published in the Federal Register 01/07/2019 and has provided such analysis below.
4. Step 1:
Claims 1-7 are directed to a computer-implemented method and fall within the statutory category of a process; Claims 8-14 are directed to a non-transitory computer-readable medium and fall within the statutory category of machines; Claims 15-20 are directed to computer-implemented system and fall within the statutory category of machines. Therefore, “Are the claims to a process, machine, manufacture or composition of matter?” Yes.
In order to evaluate the Step 2A inquiry “Is the claim directed to a law of nature, a natural phenomenon or an abstract idea?” we must determine, at Step 2A Prong 1, whether the claim recites a law of nature, a natural phenomenon or an abstract idea and further whether the claim recites additional elements that integrate the judicial exception into a practical application.
5. Step 2A Prong 1:
Claims 1, 8, and 15: The limitations of “capturing, using an Application Memory Interface (AMIF) and to create captured data from one or more software applications, data related to user actions with the one or more software applications; enhancing, using the AMIF and to create enhanced data, the captured data with metadata, data, and semantic relations; filtering, using the AMIF and to create filtered data, the enhanced data”, as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, a person can think and observe, judge and evaluate that data relating to a user’s actions is collected. One can observe someone using an application and mentally observe that they access it a certain number of times, for example. Moreover, a person can mentally observe the enhancing and filtering of the data. For example, the data can be enhanced by observing the time of day the user accesses the data and filtered to only include times during the morning.
Therefore, Yes, claim 1 recites judicial exceptions.
The claims have been identified to recite judicial exceptions, Step 2A Prong 2 will evaluate whether the claims are directed to the judicial exception.
6. Step 2A Prong 2:
Claims 1, 8, and 15: The judicial exception is not integrated into a practical application. In particular, the claim recites the following additional elements – “A computer-implemented method, comprising:”; “A non-transitory, computer-readable medium storing one or more instructions executable by a computer system to perform one or more operations, comprising:”; and “A computer-implemented system, comprising: one or more computers; and one or more computer memory devices interoperably coupled with the one or more computers and having tangible, non-transitory, machine-readable media storing one or more instructions that, when executed by the one or more computers, perform one or more operations, comprising:”, which is merely recitations of generic computing components and functions merely being used as a tool to apply the abstract idea (see MPEP § 2106.05(f)) which does not integrate a judicial exception into practical application. Additionally, the claims recite, “capturing, using an Application Memory Interface (AMIF) and to create captured data from one or more software applications, data related to user actions with the one or more software applications; enhancing, using the AMIF and to create enhanced data, the captured data with metadata, data, and semantic relations; filtering, using the AMIF and to create filtered data, the enhanced data; and sending, by the AMIF, the filtered data to a personal application memory (PAM)”, which merely recites insignificant extra solution activity such as gathering, displaying, updating, transmitting and storing data which does not integrate the judicial exception into a practical application. See MPEP 2106.05(g). The courts have identified functions such as gathering, displaying, updating, transmitting and storing data as well-understood, routine, conventional activity, thus do not amount to significantly more than the judicial exception. See MPEP 2106.05(d).
Therefore, “Do the claims recite additional elements that integrate the judicial exception into a practical application? No, these additional elements do not integrate the abstract idea into a practical application and they do not impose any meaningful limits on practicing the abstract idea. The claim is directed to an abstract idea.
After having evaluating the inquires set forth in Steps 2A Prong 1 and 2, it has been concluded that the claim 1 not only recites a judicial exception but that the claim is directed to the judicial exception as the judicial exception has not been integrated into practical application.
7. Step 2B:
Claims 1, 8, and 15: The claims do not include additional elements, alone or in combination, that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional elements amount to no more than generic computing components and field of use/technological environment which do not amount to significantly more than the abstract idea.
Therefore, “Do the claims recite additional elements that amount to significantly more than the judicial exception? No, these additional elements, alone or in combination, do not amount to significantly more than the judicial exception.
Having concluded analysis within the provided framework, Claims 1, 8, and 15 do not recite patent eligible subject matter under 35 U.S.C. § 101.
8. With regard to claims 2, 9, and 16, they recite additional abstract idea recitations of “wherein the captured data comprises one or more of a user ID, actions performed by a user, an object ID of a viewed data object, changes to the viewed data object, and a predecessor UI display screen to a UI navigation”, as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, a person can think about and observe, judge and evaluate that the captured data includes one or more of a user ID, actions performed by a user, an object ID of a viewed data object, changes to the viewed data object, and a predecessor UI display screen to a UI navigation. Additionally, defining the data is no more than generic computing components and field of use/technological environment which do not amount to significantly more than the abstract idea. Moreover, acquiring data about the container merely recites insignificant extra solution activity such as gathering, displaying, updating, transmitting and storing data which does not integrate the judicial exception into a practical application. See MPEP 2106.05(g). The courts have identified functions such as gathering, displaying, updating, transmitting and storing data as well-understood, routine, conventional activity, thus do not amount to significantly more than the judicial exception. See MPEP 2106.05(d). Further, claims 2, 9, and 16 do not recite any further additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, claims 2, 9, and 16 also fail both Step 2A prong 2, thus the claims are directed to the judicial exception as it has not been integrated into practical application, and fails Step 2B as not amounting to significantly more than the abstract idea. Therefore, Claims 2, 9, and 16 do not recite patent eligible subject matter under 35 U.S.C. § 101.
9. With regard to claims 3, 10, and 17, they recite additional abstract idea recitations of “metadata includes application ID or application name, time information, navigation information, semantic organization of data on a UI display screen, semantic relations of UI display screens and data shown as used in processes, and UI graphics and graphic metadata; data includes master data information, software application internal information, and external content; and semantic relations include time aspects of UI display screens, guided procedure data, hierarchical operations, developer provided semantic descriptions for data on the UI display screens, and focus tags for the data on the UI display screens”, as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation in the mind. For example, a person can think about and observe, judge and evaluate that the metadata includes application ID or application name, time information, navigation information, semantic organization of data on a UI display screen, semantic relations of UI display screens and data shown as used in processes, and UI graphics and graphic metadata; data includes master data information, software application internal information, and external content; and semantic relations include time aspects of UI display screens, guided procedure data, hierarchical operations, developer provided semantic descriptions for data on the UI display screens, and focus tags for the data on the UI display screens. Additionally, defining the types of data is no more than generic computing components and field of use/technological environment which do not amount to significantly more than the abstract idea. Further, claims 3, 10, and 17 do not recite any further additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, claims 3, 10, and 17 also fail both Step 2A prong 2, thus the claims are directed to the judicial exception as it has not been integrated into practical application, and fails Step 2B as not amounting to significantly more than the abstract idea. Therefore, Claims 3, 10, and 17 do not recite patent eligible subject matter under 35 U.S.C. § 101.
10. With regard to claims 4, 11, and 18, they recite additional abstract idea recitations of “wherein filtering comprises programmed filtering by a software application developer and situational automatic filtering, and wherein filtering uses a filter configuration to remove data from being stored in the PAM”, as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation in the mind. This is merely reciting instructions to implement an abstract idea on a generic computer, or merely uses a generic computer or computer components as a tool to perform the abstract idea, thus is not a practical application and merely applying the judicial exception or abstract idea. Therefore, this additional element does not integrate the judicial exception into a practical application under. Further, claims 4, 11, and 18 do not recite any further additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, claims 4, 11, and 18 also fail both Step 2A prong 2, thus the claims are directed to the judicial exception as it has not been integrated into practical application, and fails Step 2B as not amounting to significantly more than the abstract idea. Therefore, Claims 4, 11, and 18 do not recite patent eligible subject matter under 35 U.S.C. § 101.
11. With regard to claims 5, 12, and 19, they recite additional abstract idea recitations of “wherein the PAM stores the filtered data in an encrypted format, provides authenticated access to the filtered data, and encapsulates the filtered data for each user.”, as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation in the mind. This is merely reciting instructions to implement an abstract idea on a generic computer, or merely uses a generic computer or computer components as a tool to perform the abstract idea, thus is not a practical application and merely applying the judicial exception or abstract idea. Therefore, this additional element does not integrate the judicial exception into a practical application under. Moreover, storing and accessing filtered data merely recites insignificant extra solution activity such as gathering, displaying, updating, transmitting and storing data which does not integrate the judicial exception into a practical application. See MPEP 2106.05(g). The courts have identified functions such as gathering, displaying, updating, transmitting and storing data as well-understood, routine, conventional activity, thus do not amount to significantly more than the judicial exception. See MPEP 2106.05(d). Further, claims 5, 12, and 19 do not recite any further additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, claims 5, 12, and 19 also fail both Step 2A prong 2, thus the claims are directed to the judicial exception as it has not been integrated into practical application, and fails Step 2B as not amounting to significantly more than the abstract idea. Therefore, Claims 5, 12, and 19 do not recite patent eligible subject matter under 35 U.S.C. § 101.
12. With regard to claims 6, 13, and 20, they recite additional abstract idea recitations of “receiving, using a PAM UI and a provided query prompt, a user query, wherein the user query includes filter criteria, and wherein the user query is applied to data specified by the filter criteria; processing the user query; and returning heterogenous query results of the user query to the PAM UI”, as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation in the mind. This is merely reciting instructions to implement an abstract idea on a generic computer, or merely uses a generic computer or computer components as a tool to perform the abstract idea, thus is not a practical application and merely applying the judicial exception or abstract idea. Therefore, this additional element does not integrate the judicial exception into a practical application under. Moreover, filtering and accessing data based on a query merely recites insignificant extra solution activity such as gathering, displaying, updating, transmitting and storing data which does not integrate the judicial exception into a practical application. See MPEP 2106.05(g). The courts have identified functions such as gathering, displaying, updating, transmitting and storing data as well-understood, routine, conventional activity, thus do not amount to significantly more than the judicial exception. See MPEP 2106.05(d). Further, claims 6, 13, and 20 do not recite any further additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, claims 6, 13, and 20 also fail both Step 2A prong 2, thus the claims are directed to the judicial exception as it has not been integrated into practical application, and fails Step 2B as not amounting to significantly more than the abstract idea. Therefore, Claims 6, 13, and 20 do not recite patent eligible subject matter under 35 U.S.C. § 101.
13. With regard to claims 7 and 14 they recite additional abstract idea recitations of “receiving, using a PAM UI, a user query; filtering, based on the user query and filter criteria and as filtered PAM data, the filtered data stored in the PAM; transmitting the user query and the filtered PAM data to a large language model for processing; and returning a natural language summary as query results of the user query to the PAM UI”, as drafted, is a process that, but for the recitation of generic computing components, under its broadest reasonable interpretation, covers performance of the limitation in the mind. This is merely reciting instructions to implement an abstract idea on a generic computer, or merely uses a generic computer or computer components as a tool to perform the abstract idea, thus is not a practical application and merely applying the judicial exception or abstract idea. Therefore, this additional element does not integrate the judicial exception into a practical application under. Moreover, filtering and accessing data based on a query merely recites insignificant extra solution activity such as gathering, displaying, updating, transmitting and storing data which does not integrate the judicial exception into a practical application. See MPEP 2106.05(g). The courts have identified functions such as gathering, displaying, updating, transmitting and storing data as well-understood, routine, conventional activity, thus do not amount to significantly more than the judicial exception. See MPEP 2106.05(d). Further, claims 7 and 14 do not recite any further additional elements and for the same reasons as above with regard to integration into practical application and whether additional elements amount to significantly more, claims 7 and 14 also fail both Step 2A prong 2, thus the claims are directed to the judicial exception as it has not been integrated into practical application, and fails Step 2B as not amounting to significantly more than the abstract idea. Therefore, Claims 7 and 14 do not recite patent eligible subject matter under 35 U.S.C. § 101.
14. Therefore, Claims 1-20 do not recite patent eligible subject matter under 35 U.S.C. § 101.
Claim Rejections - 35 USC § 103
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.
15. Claims 1-3, 5, 8-10, 12, 15-17, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Todirel et al. US 20220222047 A1 in view of Ligman et al. US 20190340093 A1.
16. With regard to claim 1, Todirel teaches:
A computer-implemented method, comprising:
capturing, using an Application Memory Interface (AMIF) and to create captured data from one or more software applications, data related to user actions with the one or more software applications (Fig. 2; 206 Development Tool; [0091] Some embodiments include intelligence gathering. Every action 220 performed by a user in the tool is tagged and recorded on a central place, and a mitigation graph 210 of such actions is built and maintained centrally for all tracked users. Each action is tagged and correlated with additional semantic metadata. The tool is modified to generate such data, e.g., by the authors of the tool who know which code corresponds to what actions. Some user actions that consume user input, e.g., as configuration files or code, will also be classified with their intelligence 226 uploaded as metadata to the actions; Examiner’s Note: The tool is the AMIF because every action performed by a user in the tool is tagged and recorded, which is analogous to creating captured data.);
enhancing, using the AMIF and to create enhanced data, the captured data with metadata, data, and semantic relations ([0044]; Internal action data 228 representing an internal tool action may include, e.g., automatic updates received, automatic culling of expired data, garbage collection or backups or other memory management actions, security handshakes or encryption protocol negotiations, communication retries, checksum calculations, and the like; Examiner’s Note: Internal action data includes internal took actions, which is data; [0084] In some embodiments, code and frequently used call sites in the developer tool 206 are instrumented manually or automatically, such that as a user interfaces with the developer tool, the instrumented code emits the data 226 onto the documentation service 438. As the developer tool is used, the graph database 210 in the documentation service keeps updating 836. Nodes 312 represent actions 220 taken by the user in the developer tool, with metadata 316 about where it originated from, how long it took, was the operation successful, did the action have a GUI or ran internally, if the operation failed, what was the cause of the error, etc.; Examiner’s Note: The metadata is analogous with metadata. [0091] Some embodiments include intelligence gathering. Every action 220 performed by a user in the tool is tagged and recorded on a central place, and a mitigation graph 210 of such actions is built and maintained centrally for all tracked users. Each action is tagged and correlated with additional semantic metadata; Examiner’s Note: The semantic metadata is analogous with semantic relations.);
filtering, using the AMIF and to create filtered data, the enhanced data ([0246] 702 obtain problem info from development tool; performed computationally; obtaining 702 may include, e.g., parsing, cleaning, filtering or similar data extraction operations on event data 226, 228 from logs or packet captures or telemetry to get problem info 214 from raw data 226 and 228); and
Although Todirel teaches of capturing, enhancing, and filtering data, Todirel fails to explicitly teach sending, by the AMIF, the filtered data to a personal application memory (PAM).
However, in analogous art, Ligman teaches:
sending, by the AMIF, the filtered data to a personal application memory (PAM) (Abstract, A method for tracking user interactions with an application includes: storing the application in a memory of a mobile device, the application being associated with an instrumented widget and a library, the widget including an event logger; executing the application and the widget; receiving, through a user interface of the mobile device, an input corresponding to the event logger of the widget; logging, by the library, the input corresponding to the event logger of the widget in the memory of the mobile device; filtering a plurality of events, including the input corresponding to the event logger of the widget, to manage what data is reported to a monitor; and transmitting the input corresponding to the event logger of the widget to a server as monitored data.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Todirel with the teachings of Ligman wherein sending, by the AMIF, the filtered data to a personal application memory (PAM). Todirel teaches of capturing user action data; enhancing it with metadata, additional data, and semantic relations; and filtering the enhanced data to obtain filtered data. Similarly, Ligman teaches of tracking user interactions with an application by logging the events, filtering the events, and transmitting the filtered data to a server. By doing so, consistent monitoring and management functionality can be implanted; therefore, enabling insight into user activity ([0013]; [0026]). Together, Todirel and Ligman teach of capturing user action data; enhancing it with metadata, additional data, and semantic relations; filtering the enhanced data to obtain filtered data; and transmitting it to an application memory.
17. With regard to claim 2, Todirel further teaches:
wherein the captured data comprises one or more of a user ID, actions performed by a user, an object ID of a viewed data object, changes to the viewed data object, and a predecessor UI display screen to a UI navigation (Fig. 2; 206 Development Tool; [0044] User action data 226 representing a user action 220 may include, e.g., interaction events such as clicks received, pages displayed, commands selected, input received through dialogs, and the like, extracted from raw data 308 such as logs or packets that are created automatically during tool usage sessions 310; [0091] Some embodiments include intelligence gathering. Every action 220 performed by a user in the tool is tagged and recorded on a central place, and a mitigation graph 210 of such actions is built and maintained centrally for all tracked users. Each action is tagged and correlated with additional semantic metadata. The tool is modified to generate such data, e.g., by the authors of the tool who know which code corresponds to what actions. Some user actions that consume user input, e.g., as configuration files or code, will also be classified with their intelligence 226 uploaded as metadata to the actions;).
18. With regard to claim 3, Todirel further teaches:
wherein:
metadata includes application ID or application name, time information, navigation information, semantic organization of data on a UI display screen, semantic relations of UI display screens and data shown as used in processes, and UI graphics and graphic metadata ([0084] In some embodiments, code and frequently used call sites in the developer tool 206 are instrumented manually or automatically, such that as a user interfaces with the developer tool, the instrumented code emits the data 226 onto the documentation service 438. As the developer tool is used, the graph database 210 in the documentation service keeps updating 836. Nodes 312 represent actions 220 taken by the user in the developer tool, with metadata 316 about where it originated from, how long it took, was the operation successful, did the action have a GUI or ran internally, if the operation failed, what was the cause of the error, etc.);
data includes master data information, software application internal information, and external content ([0044]; Internal action data 228 representing an internal tool action may include, e.g., automatic updates received, automatic culling of expired data, garbage collection or backups or other memory management actions, security handshakes or encryption protocol negotiations, communication retries, checksum calculations, and the like.); and
semantic relations include time aspects of UI display screens, guided procedure data, hierarchical operations, developer provided semantic descriptions for data on the UI display screens, and focus tags for the data on the UI display screens ([0091] Some embodiments include intelligence gathering. Every action 220 performed by a user in the tool is tagged and recorded on a central place, and a mitigation graph 210 of such actions is built and maintained centrally for all tracked users. Each action is tagged and correlated with additional semantic metadata. The tool is modified to generate such data, e.g., by the authors of the tool who know which code corresponds to what actions. Some user actions that consume user input, e.g., as configuration files or code, will also be classified with their intelligence 226 uploaded as metadata to the actions.).
19. With regard to claim 5, Todirel further teaches:
wherein the PAM stores the filtered data in an encrypted format, provides authenticated access to the filtered data, and encapsulates the filtered data for each user ([0043] Some embodiments include a filter 318 which excludes or anonymizes personally identifiable information 320 that is in the action data 226, 228 so that vulnerable PII 320 is not part of the action metadata 316; [0069] Accordingly, some data may be anonymized, excluded, or otherwise constrained 828 from use as action metadata 316. Network addresses may be hashed, and email addresses may be used as metadata 316 only internally within an organization, for example. Some embodiments anonymize, hash, or exclude personally identifiable information which is accessible to the development tool, thereby securing 832 the mitigation graph against inclusion of unprotected personally identifiable information.).
Todirel fails to explicitly teach that the data is stored in the PAM.
However, in analogous art, Ligman teaches:
wherein the PAM stores (Abstract, A method for tracking user interactions with an application includes: storing the application in a memory of a mobile device, the application being associated with an instrumented widget and a library, the widget including an event logger; executing the application and the widget; receiving, through a user interface of the mobile device, an input corresponding to the event logger of the widget; logging, by the library, the input corresponding to the event logger of the widget in the memory of the mobile device; filtering a plurality of events, including the input corresponding to the event logger of the widget, to manage what data is reported to a monitor; and transmitting the input corresponding to the event logger of the widget to a server as monitored data.),
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Todirel with the teachings of Ligman data is stored in the PAM. Todirel teaches of capturing user action data; enhancing it with metadata, additional data, and semantic relations; and filtering the enhanced data to obtain filtered data. Similarly, Ligman teaches of tracking user interactions with an application by logging the events, filtering the events, and transmitting the filtered data to a server. By doing so, consistent monitoring and management functionality can be implanted; therefore, enabling insight into user activity ([0013]; [0026]). Together, Todirel and Ligman teach of capturing user action data; enhancing it with metadata, additional data, and semantic relations; filtering the enhanced data to obtain filtered data; and transmitting it to an application memory.
20. Regarding claim 8, it is rejected under the same reasoning as claim 1 above. Therefore, it is rejected under the same rationale.
21. Regarding claim 9, it is rejected under the same reasoning as claim 2 above. Therefore, it is rejected under the same rationale.
22. Regarding claim 10, it is rejected under the same reasoning as claim 3 above. Therefore, it is rejected under the same rationale.
23. Regarding claim 12, it is rejected under the same reasoning as claim 5 above. Therefore, it is rejected under the same rationale.
24. Regarding claim 15, it is rejected under the same reasoning as claim 1 above. Therefore, it is rejected under the same rationale.
25. Regarding claim 16, it is rejected under the same reasoning as claim 2 above. Therefore, it is rejected under the same rationale.
26. Regarding claim 17, it is rejected under the same reasoning as claim 3 above. Therefore, it is rejected under the same rationale.
27. Regarding claim 19, it is rejected under the same reasoning as claim 5 above. Therefore, it is rejected under the same rationale.
28. Claims 4, 6, 11, 13, 18, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Todirel et al. US 20220222047 A1 and Ligman et al. US 20190340093 A1, as applied in claim 1, in further view of Mavinakuli US 20160267090 A1.
29. With regard to claim 4, Todirel and Ligman teach the computer-implemented method of claim 1 but fails to explicitly teach wherein filtering comprises programmed filtering by a software application developer and situational automatic filtering, and wherein filtering uses a filter configuration to remove data from being stored in the PAM.
However, in analogous art, Mavinakuli teaches:
wherein filtering comprises programmed filtering by a software application developer and situational automatic filtering, and wherein filtering uses a filter configuration to remove data from being stored in the PAM ([0008] Solutions to achieve these results can include, for example, implementing a software solution in which users, based on their role (e.g., as a client, a company executive, or a system administrator) are presented with recommendations based on their most relevant actions. For example, user transactions can be registered and stored in a database. Based on the stored information, suggestions can be provided to help the user save time on lengthy but routine activities. For example, instead of having to manually filter the data, an extension can enable users to directly select the required operations and parameters based on the choices they had used the previous time. Specifically, while representing and sharing the final data, the software can suggest the user's previously favored choices. Examiner’s Note: The filtering is done based on user role and required operations and parameters. This process can be automated based on the choices the user had made before.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Todirel and Ligman with the teachings of Mavinakuli wherein filtering comprises programmed filtering by a software application developer and situational automatic filtering, and wherein filtering uses a filter configuration to remove data from being stored in the PAM. Together, Todirel and Ligman teach of capturing user action data; enhancing it with metadata, additional data, and semantic relations; filtering the enhanced data to obtain filtered data; and transmitting it to an application memory. Similarly, Mavinakuli teaches of using user action transaction information, along with other pertinent data, in order to make relevant suggestions to the user. The suggestions are made by identifying pertinent transactions through filtering. This filtering can be user defined and automated. For example, instead of having to manually filter the data, an extension can enable users to directly select the required operations and parameters based on the choices they had used the previous time. Specifically, while representing and sharing the final data, the software can suggest the user's previously favored choices. Knowing which features are most relevant and automating them, businesses can prioritize and speed up their workflows and deprioritize the little used features to keep them out of the way, as discussed in Mavinakuli ([0008]). Therefore, ensuring efficient and streamlined workflows for users.
30. With regard to claim 6, Todirel and Ligman teach the computer-implemented method of claim 1 but fail to explicitly teach receiving, using a PAM UI and a provided query prompt, a user query, wherein the user query includes filter criteria, and wherein the user query is applied to data specified by the filter criteria.
However, in analogous art, Mavinakuli further teaches:
comprising:
receiving, using a PAM UI and a provided query prompt, a user query, wherein the user query includes filter criteria, and wherein the user query is applied to data specified by the filter criteria ([0078] At 314, a category is defined. For example, the suggestion module 129 can identify a category based on the user identifier associated with User A and a current stage that User A is in. The identified category can also depend on other factors, such as the type of data that User A is working with. The identified category in this example can be along the lines of User=User A, Stage=Visualization, Data=Marketing. In some implementations, the type of data that is being used can be identified, for example, by the names of one or more tables in a database or in other ways.);
processing the user query ([0079] At 316, transactions in the repository are filtered by category. For example, the suggestion module 129 can identify transactions in the transaction repository 111 that match User=User A, Stage=Visualization, Data=Marketing. Filtering by stage can include, for example, including transactions for stages that are compatible with the current stage.); and
returning heterogenous query results of the user query to the PAM UI ([0081] At 320, the ranked suggestions are published. As an example, the interface module 116 can provide the ranked transactions to client application 114 for presentation to the user.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Todirel and Ligman with the teachings of Mavinakuli receiving, using a PAM UI and a provided query prompt, a user query, wherein the user query includes filter criteria, and wherein the user query is applied to data specified by the filter criteria; processing the user query; and returning heterogenous query results of the user query to the PAM UI. Together, Todirel and Ligman teach of capturing user action data; enhancing it with metadata, additional data, and semantic relations; filtering the enhanced data to obtain filtered data; and transmitting it to an application memory. Similarly, Mavinakuli teaches of using user action transaction information, along with other pertinent data, in order to make relevant suggestions to the user. The suggestions are made by identifying pertinent transactions through filtering. This filtering includes filter criteria and returns the suggestions through an interface for the user. For example, the user interface includes a campaign analysis screen in which a user can display and work with data in a data area, as discussed in Mavinakuli ([0086]). This allows users to easily interact with their filtered data, ensuring efficient and streamlined workflows for users.
31. Regarding claim 11, it is rejected under the same reasoning as claim 4 above. Therefore, it is rejected under the same rationale.
32. Regarding claim 13, it is rejected under the same reasoning as claim 6 above. Therefore, it is rejected under the same rationale.
33. Regarding claim 18, it is rejected under the same reasoning as claim 4 above. Therefore, it is rejected under the same rationale.
34. Regarding claim 20, it is rejected under the same reasoning as claim 6 above. Therefore, it is rejected under the same rationale.
35. Claims 7 and 14 are rejected under 35 U.S.C. 103 as being unpatentable over Todirel et al. US 20220222047 A1 and Ligman et al. US 20190340093 A1, as applied in claim 1, in further view of Chandrashekar et al. US 11900320 B2.
36. With regard to claim 7, Todirel and Ligman teach the computer-implemented method of claim 1 but fail to explicitly teach receiving, using a PAM UI, a user query; filtering, based on the user query and filter criteria and as filtered PAM data, the filtered data stored in the PAM; transmitting the user query and the filtered PAM data to a large language model for processing; and returning a natural language summary as query results of the user query to the PAM UI.
However, in analogous art, Chandrashekar teaches:
comprising:
receiving, using a PAM UI, a user query (Col. 4, lines 7-9, Alternatively, and/or additionally, the management system may receive the query via a user interface associated with the management system.);
filtering, based on the user query and filter criteria and as filtered PAM data, the filtered data stored in the PAM (Col. 4, lines 18-31, In some implementations, the user may select the query from a list of queries accessed via a menu or a selectable option provided by the user interface. The management system may determine one or more parameters associated with the user. For example, the management system may determine a role of the user (e.g., a customer, an employee, a technician, a service executive, an agent, an underwriter, a manager, an insurance adjuster, and/or the like), a set of actions (e.g., navigating from a first screen to a second screen, inputting data into a particular field of a user interface, and/or the like) performed prior to submitting the query, a function frequently performed by the user, and/or the like.);
transmitting the user query and the filtered PAM data to a large language model for processing (Col. 5, lines 41-47, The management system may determine the subject of the query based on performing natural language processing (NLP). For example, the management system may perform one or more NLP techniques on the query to determine a set of key words associated with the query. The management system may determine the subject based on the set of key words.); and
returning a natural language summary as query results of the user query to the PAM UI (Col. 16, lines 55-59, Alternatively, and/or additionally, the device may provide a user interface to the user device. The user may provide the query to the user interface via a text input to the user device and the device may receive the query for information via the user interface.).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to combine the teachings of Todirel and Ligman with the teachings of Mavinakuli receiving, using a PAM UI, a user query; filtering, based on the user query and filter criteria and as filtered PAM data, the filtered data stored in the PAM; transmitting the user query and the filtered PAM data to a large language model for processing; and returning a natural language summary as query results of the user query to the PAM UI. Together, Todirel and Ligman teach of capturing user action data; enhancing it with metadata, additional data, and semantic relations; filtering the enhanced data to obtain filtered data; and transmitting it to an application memory. Similarly, Chandrashekar teaches of receiving data related to a user. The data can be queried and processed by a language processing model in order to determine a decision for a user. This decision is displayed to the user via an interface. By using NLP, or any other language processing model, to filter data, key words associated with the query can be determined, as discussed in Mavinakuli (Col. 5, lines 44-45). Therefore, further filtering the data for a user.
37. Regarding claim 14, it is rejected under the same reasoning as claim 7 above. Therefore, it is rejected under the same rationale.
Conclusion
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/AN-AN NGOC NGUYEN/Examiner, Art Unit 2195
/Aimee Li/Supervisory Patent Examiner, Art Unit 2195