DETAILED ACTION
Notice of Pre-AIA or AIA Status
1. The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
2. This Office Action is sent in response to Applicant’s Communication received 9/10/2024 for application number 18/830,314. The Office hereby acknowledges receipt of the following and placed of record in file: Specification, Drawings, Abstract, Oath/Declaration, claims.
3. Claims 2 – 22 are presented for examination.
Claim Rejections - 35 USC § 101
3. 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.
4. Claims 2 - 22 are directed to an abstract idea without significantly more. Independent claim 2 recites a method comprising: defining a set of software bots for processing a data set; identifying processing capacity of a software bot of the set of software bots; receiving a time limit to complete processing the data set; selecting a plurality of network clients, wherein the plurality of network clients include a predetermined number of network clients, and wherein the predetermined number is determined based on the processing capacity and the time limit; initiating processing of the data set, wherein the plurality of network clients execute the set of software bots to process the data set; detecting a processing error associated with a particular software bot, wherein the processing error is detected by a network client configured to execute the particular software bot; performing a correction process to fix the processing error by updating code of a corresponding software bot; and generating a notification associated with the data set, wherein the notification identifies the processing error associated with the particular software bot.
The limitations, as drafted, describe a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components. The abstract idea limitations are “defining a set of software bots for processing a data set,” “identifying processing capacity of a software bot of the set of software bots,” “selecting a plurality of network clients, wherein the plurality of network clients include a predetermined number of network clients, and wherein the predetermined number is determined based on the processing capacity and the time limit,” “detecting a processing error associated with a particular software bot, wherein the processing error is detected” and “performing a correction process to fix the processing error by updating code of a corresponding software bot” in Prong I step 2A. Other limitations including “receiving a time limit to complete processing the data set,” “initiating processing of the data set, wherein the plurality of network clients execute the set of software bots to process the data set,” “by a network client configured to execute the particular software bot” and “generating a notification associated with the data set, wherein the notification identifies the processing error associated with the particular software bot“ are considered as extra-activity solutions for gathering information which are insignificant and outputting information regarding the events is merely an applied application and insignificantly amounts to the judicial exception. Thus, these claims are directed to an abstract idea under 35 USC 101.
That is, other than reciting “receiving a time limit to complete processing the data set,” “initiating processing of the data set, wherein the plurality of network clients execute the set of software bots to process the data set,” “by a network client configured to execute the particular software bot” and “generating a notification associated with the data set, wherein the notification identifies the processing error associated with the particular software bot,“ the limitations are mental processes under Prong I of step 2A. If a claim limitation, under its broadest reasonable interpretation, covers performance of the limitation in the mind but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claims recite an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the components in the generate step are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function of receiving information, executing a function and making a decision) such that it amounts no more than mere instructions to apply the exception using a generic computer component.
Additionally, the steps of “receiving a time limit to complete processing the data set,” “initiating processing of the data set, wherein the plurality of network clients execute the set of software bots to process the data set,” “by a network client configured to execute the particular software bot” and “generating a notification associated with the data set, wherein the notification identifies the processing error associated with the particular software bot“ are pre/post-activity solutions as gathering data, initiating processing and generating notifications that are insignificant under Prong II step 2A and 2B. See buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network) as noted in MPEP 2106.05(d)(II)(i). Accordingly, these additional elements do not integrate the abstract idea into a practical application because it does not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea.
The claims do not include additional elements 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 element of using a computer to perform the noted steps amounts to no more than mere instructions to apply the exception using a generic computer component. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept. The claims are not patent eligible.
Independent claims 9 and 16 are rejected on the same basis as independent claim 2. Additionally, dependent claims 3 – 8, 10 – 15 and 17 - 22 are similarly rejected as being directed to an abstract idea since these claims are either further detailing the abstract idea by analyzing/processing the data or the elements are insignificant. More specifically, the dependent claims do not include additional elements, alone or in combination, that are sufficient to amount to significantly more than the judicial exception.
As per claims 3, 10 and 17, wherein the network client is configured to execute and monitor performance of a subset of software bots, and wherein the subset of software bots includes the particular software bot (additional element under Prong II step 2A).
As per claims 4, 11 and 18, wherein the notification includes a snapshot that visually indicates processing status of the data set (additional element of data gathering under Prong I step 2A).
As per claim 5, wherein the predetermined number of network clients is determined further based on a number of data records associated with the data set (abstract idea under mental process under Prong I step 2A).
As per claim 6, wherein the predetermined number is determined by applying a machine-learning model to the processing capacity and the time limit (abstract idea under mental process under Prong I step 2A).
As per claim 7, wherein processing of the data set includes generating a summary report associated with one or more portions of the data set that were processed by the set of software bots (additional element under Prong I step 2A).
As per claim 8, wherein the processing capacity is determined based on an amount of time used by the software bot to process one or more portions of the data set (abstract idea under mental process under Prong I step 2A.
Claim Rejections - 35 USC § 103
5. 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.
6. 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.
7. Claims 2, 5 – 9, 12 – 16 and 19 – 22 are rejected under 35 U.S.C. 103 as being unpatentable over Joseph (U.S. Publication 2019/0377605) (Joseph hereinafter) (Identified by Applicant in IDS), Seigel et al. (U.S. Publication 2018/0351902) (Seigel hereinafter), Hu et al. (U.S. Publication 2019/0347146) (Hu hereinafter) (Identified by Applicant in IDS), Patel et al. (U.S. Publication 2021/0173718) (Patel hereinafter) (Identified by Applicant in IDS), Dennis et al. (U.S. Patent 10,908,950) (Dennis hereinafter) (Identified by Applicant in IDS) and Ramasamy et al. (U.S. Patent 10,705,948) (Ramasamy hereinafter) (Identified by Applicant in IDS).
8. As per claim 2, Joseph teaches a method comprising:
defining a set of software bots for processing a data set [“At least part of the request is assigned to a coordinating bot of a processing subsystem of a computing system. A set of processing bots is generated by the coordinating bot to operate at the processing subsystem and to perform processing for the at least part of the request. Each processing bot of the set of processing bots is assigned one or more tasks of a set of tasks to perform. The set of tasks is defined such that performance of the set of tasks corresponds to processing of the at least part of the request.,” ¶ 0003; one or more tasks of a set of tasks mapped to data sets]; and
selecting a plurality of network clients, wherein the plurality of network clients include a predetermined number of network clients; and initiating processing of the data set, wherein the plurality of network clients execute the set of software bots to process the data set [“At least part of the request is assigned to a coordinating bot of a processing subsystem of a computing system. A set of processing bots is generated by the coordinating bot to operate at the processing subsystem and to perform processing for the at least part of the request. Each processing bot of the set of processing bots is assigned one or more tasks of a set of tasks to perform. The set of tasks is defined such that performance of the set of tasks corresponds to processing of the at least part of the request.,” ¶ 0003; processing subsystem mapped to network client, processing bot assignment mapped to selection].
Joseph does not explicitly disclose but Seigel discloses identifying processing capacity of a software bot of the set of software bots [“the weighted score of each of the software agents may be calculated based on an available drive space, an average peer latency, a processing capacity, an average ping latency to the coordinator, or some combination thereof of each of the software agents,” Cl. 7; software agent mapped to software bot].
It would have been obvious to one of ordinary skill in the art, having the teachings of Joseph and Siegel available before the effective filing date of the claimed invention, to modify the capability of management of high-volume concurrent processes as disclosed by Joseph to include the capability of evaluation of software bots as taught by Siegel, thereby providing a mechanism to enhance system efficiency by supporting the allocation of system resources.
Joseph and Siegel do not explicitly disclose but Hu discloses receiving a time limit to complete processing the data set [“The first server may further detect whether a current time exceeds a caching time limit corresponding to the obtained shared data. The caching time limit refers to a validity period of the shared data,” ¶ 0060; “When the current time does not exceed the caching time limit corresponding to the obtained shared data, it indicates that the shared data stored on the first server is valid shared data, and the first server may directly feed back the found shared data to the terminal,” ¶ 0061; shared data must be processed withing the caching time limit].
It would have been obvious to one of ordinary skill in the art, having the teachings of Joseph, Siegel and Hu available before the effective filing date of the claimed invention, to modify the capability of management of high-volume concurrent processes as disclosed by Joseph and Siegel to include the capability of time limited data processing as taught by Hu, thereby providing a mechanism to enhance system efficiency by enhancing the ability to manage processing of valid data.
Joseph, Siegel and Hu do not explicitly disclose but Patel discloses wherein the predetermined number is determined based on the processing capacity and the time limit [“The master bot of the DevOps virtual assistant platform may use natural language processing techniques and machine learning models to identify and assign tasks to worker bots, which may be scalable to automatically perform the tasks based on the size of the DevOps workflow request to be processed,” ¶ 0012; “the worker bots activated by the master bot may perform tasks associated with the DevOps workflow request in parallel to increase the efficiency of processing the DevOps workflow request, decrease the amount of time that the DevOps virtual assistant platform takes to process the DevOps workflow request, and/or the like. In this case, the master bot may scale worker bots by activating additional worker bots using containerization method of the same worker bot type or of different worker bot types in order to parallelize processing of the tasks,” ¶ 0046; increase in efficiency and decreasing processing times suggests a time limit; activation of additional worker bots suggests bot capacity being reached].
It would have been obvious to one of ordinary skill in the art, having the teachings of Joseph, Siegel, Hu and Patel available before the effective filing date of the claimed invention, to modify the capability of management of high-volume concurrent processes as disclosed by Joseph, Siegel and Hu to include the capability of resource assignment as taught by Patel, thereby providing a mechanism to enhance system efficiency by optimizing resource allocation.
Joseph, Siegel, Hu and Patel do not explicitly disclose but Dennis discloses detecting a processing error associated with a particular software bot, wherein the processing error is detected by a network client configured to execute the particular software bot; and generating a notification associated with the data set, wherein the notification identifies the processing error associated with the particular software bot [“To prevent overload when concurrently executing a large number of devices, the processing by the control room 104 of status update messages from bot runners 110 may preferably rate limited (i.e. process a certain number of status update messages within a certain time period) on a per-control room server basis. Messages that are rate limited are preferably discarded as they are just progress messages. Other messages, such as bot start, bot stop, and bot error are computer - executable instructions, such as those included in preferably not rate limited. Additionally, the rate limit may preferably be adjusted dynamically based on the number of unprocessed status update messages. If reactive rate-limiting is activated the progress reported on an activity page provided to a control room 104 user will be updated at a lower frequency than normal.” col. 11, line 57 – col. 12, line 3; status update messages (including errors) are initiated by bot runners; progress reporting mapped to notification generation].
It would have been obvious to one of ordinary skill in the art, having the teachings of Joseph, Siegel, Hu, Patel and Dennis available before the effective filing date of the claimed invention, to modify the capability of management of high-volume concurrent processes as disclosed by Joseph, Siegel, Hu and Patel to include the capability of status reporting as taught by Dennis, thereby providing a mechanism to enhance system efficiency by enhancing the ability to identify system performance.
Joseph, Siegel, Hu, Patel and Dennis do not explicitly disclose but Ramasamy discloses performing a correction process to fix the processing error by updating code of a corresponding software bot [“execute, via the first access RPA bot, the first set of actions within the testing application; detect a first error within the testing application, wherein the first error is caused at least in part by the first access RPA bot executing the first set of actions within the testing application; retrieve, via a monitor RPA bot, instantaneous performance data of the testing application at an instant that the first error has occurred and at regular intervals leading up to the instant that the first error has occurred, wherein the instantaneous performance data of the testing application comprises at least one of user load, user capacity, or rate of utilization; execute, via a remediation RPA bot, a remediation sequence to correct the first error, wherein the remediation sequence comprises at least one of loading additional modules or unloading problematic modules; and store, within an RPA database, an event entry associated with the first error,” cl. 1; loading/unloading modules mapped to updating code].
It would have been obvious to one of ordinary skill in the art, having the teachings of Joseph, Siegel, Hu, Patel, Dennis and Ramasamy available before the effective filing date of the claimed invention, to modify the capability of management of high-volume concurrent processes as disclosed by Joseph, Siegel, Hu, Patel and Dennis to include the capability of error detection and mitigation as taught by Ramasamy, thereby providing a mechanism to enhance system efficiency by implementing an automated error correction process.
9. As per claim 5, Joseph, Siegel, Hu, Patel, Dennis and Ramasamy teach the method of claim 2. Patel further teaches wherein the predetermined number of network clients is determined further based on a number of data records associated with the data set [“The master bot of the DevOps virtual assistant platform may use natural language processing techniques and machine learning models to identify and assign tasks to worker bots, which may be scalable to automatically perform the tasks based on the size of the DevOps workflow request to be processed,” ¶ 0012].
It would have been obvious to one of ordinary skill in the art, having the teachings of Joseph, Hu and Patel available before the effective filing date of the claimed invention, to modify the capability of management of high-volume concurrent processes as disclosed by Joseph and Hu to include the capability of resource assignment as taught by Patel, thereby providing a mechanism to enhance system efficiency by optimizing resource allocation.
10. As per claim 6, Joseph, Siegel, Hu, Patel, Dennis and Ramasamy teach the method of claim 2. Patel further teaches wherein the predetermined number is determined by applying a machine-learning model to the processing capacity and the time limit [“The master bot of the DevOps virtual assistant platform may use natural language processing techniques and machine learning models to identify and assign tasks to worker bots, which may be scalable to automatically perform the tasks based on the size of the DevOps workflow request to be processed,” ¶ 0012; “the worker bots activated by the master bot may perform tasks associated with the DevOps workflow request in parallel to increase the efficiency of processing the DevOps workflow request, decrease the amount of time that the DevOps virtual assistant platform takes to process the DevOps workflow request, and/or the like. In this case, the master bot may scale worker bots by activating additional worker bots using containerization method of the same worker bot type or of different worker bot types in order to parallelize processing of the tasks,” ¶ 0046 increase in efficiency and decreasing processing times suggests a time limit; activation of additional worker bots suggests bot capacity being reached].
It would have been obvious to one of ordinary skill in the art, having the teachings of Joseph, Hu and Patel available before the effective filing date of the claimed invention, to modify the capability of management of high-volume concurrent processes as disclosed by Joseph and Hu to include the capability of resource assignment as taught by Patel, thereby providing a mechanism to enhance system efficiency by optimizing resource allocation.
11. As per claim 7, Joseph, Siegel, Hu, Patel, Dennis and Ramasamy teach the method of claim 2. Dennis further teaches wherein processing of the data set includes generating a summary report associated with one or more portions of the data set that were processed by the set of software bots [“Each bot runner is programmed to update control room 104 upon completion of its tasks and upon receiving such update, workload processor 116 updates its status entries in a manner described in further detail in conjunction with FIG. 3.” col. 6, lines 4 – 8].
It would have been obvious to one of ordinary skill in the art, having the teachings of Joseph, Siegel, Hu, Patel and Dennis available before the effective filing date of the claimed invention, to modify the capability of management of high-volume concurrent processes as disclosed by Joseph, Siegel, Hu and Patel to include the capability of status reporting as taught by Dennis, thereby providing a mechanism to enhance system efficiency by enhancing the ability to identify system performance.
12. As per claim 8, Joseph, Siegel, Hu, Patel, Dennis and Ramasamy teach the method of claim 2. Siegel further teaches wherein the processing capacity is determined based on an amount of time used by the software bot to process one or more portions of the data set [“the weighted score of each of the software agents may be calculated based on an available drive space, an average peer latency, a processing capacity, an average ping latency to the coordinator, or some combination thereof of each of the software agents,” Cl. 7; software agent mapped to software bot].
It would have been obvious to one of ordinary skill in the art, having the teachings of Joseph and Siegel available before the effective filing date of the claimed invention, to modify the capability of management of high-volume concurrent processes as disclosed by Joseph to include the capability of evaluation of software bots as taught by Siegel, thereby providing a mechanism to enhance system efficiency by supporting the allocation of system resources.
13. As per claim 9, it is a system claim having similar limitations as cited in claim 2. Thus, claim 9 is also rejected under the same rationale as cited in the rejection of claim 2 above.
14. As per claim 12, it is a system claim having similar limitations as cited in claim 5. Thus, claim 12 is also rejected under the same rationale as cited in the rejection of claim 5 above.
15. As per claim 13, it is a system claim having similar limitations as cited in claim 6. Thus, claim 13 is also rejected under the same rationale as cited in the rejection of claim 6 above.
16. As per claim 14, it is a system claim having similar limitations as cited in claim 7. Thus, claim 14 is also rejected under the same rationale as cited in the rejection of claim 7 above.
17. As per claim 15, it is a system claim having similar limitations as cited in claim 8. Thus, claim 15 is also rejected under the same rationale as cited in the rejection of claim 8 above.
18. As per claim 16, it is a media claim having similar limitations as cited in claim 2. Thus, claim 16 is also rejected under the same rationale as cited in the rejection of claim 2 above.
19. As per claim 19, it is a media claim having similar limitations as cited in claim 5. Thus, claim 19 is also rejected under the same rationale as cited in the rejection of claim 5 above.
20. As per claim 20, it is a media claim having similar limitations as cited in claim 6. Thus, claim 20 is also rejected under the same rationale as cited in the rejection of claim 6 above.
21. As per claim 21, it is a media claim having similar limitations as cited in claim 7. Thus, claim 21 is also rejected under the same rationale as cited in the rejection of claim 7 above.
22. As per claim 22, it is a media claim having similar limitations as cited in claim 8. Thus, claim 22 is also rejected under the same rationale as cited in the rejection of claim 8 above.
23. Claims 3, 10 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Joseph, Seigel, Hu, Patel, Dennis and Ramasamy in further view of Ronge et al. (U.S. Publication 2020/0104111) (Ronge hereinafter).
24. As per claim 3, Joseph, Siegel, Hu, Patel, Dennis and Ramasamy teach the method of claim 2. Joseph, Siegel, Hu, Patel, Dennis and Ramasamy do not explicitly disclose but Ronge discloses wherein the network client is configured to execute and monitor performance of a subset of software bots, and wherein the subset of software bots includes the particular software bot [“wherein the automation engine comprises a set of work processes and a set of communication processes, wherein the set of work processes trigger performance of the software automation tasks on the set of agents and monitor performance of the software automation tasks, and the set of communication processes facilitate communication between the work processes and the set of agents.” Cl. 5].
It would have been obvious to one of ordinary skill in the art, having the teachings of Joseph, Siegel, Hu, Patel, Dennis, Ramasamy and Ronge available before the effective filing date of the claimed invention, to modify the capability of management of high-volume concurrent processes as disclosed by Joseph, Siegel, Hu, Patel, Dennis and Ramasamy to include the capability of performance monitoring as taught by Ronge, thereby providing a mechanism to enhance system efficiency by implementing an automated performance feedback capability.
25. As per claim 10, it is a system claim having similar limitations as cited in claim 3. Thus, claim 10 is also rejected under the same rationale as cited in the rejection of claim 3 above.
26. As per claim 17, it is a media claim having similar limitations as cited in claim 3. Thus, claim 17 is also rejected under the same rationale as cited in the rejection of claim 3 above.
27. Claims 4, 11 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Joseph, Seigel, Hu, Patel, Dennis and Ramasamy in further view of Fromherz et al. (U.S. Publication 2004/0225391) (Fromherz hereinafter).
28. As per claim 4, Joseph, Siegel, Hu, Patel, Dennis and Ramasamy teach the method of claim 2. Joseph, Siegel, Hu, Patel, Dennis and Ramasamy do not explicitly disclose but Fromherz discloses wherein the notification includes a snapshot that visually indicates processing status of the data set [“Reports are generated that reveal the status of the batch program in terms of the processing time of the dataset associated with the batch program,” ¶ 0004].
It would have been obvious to one of ordinary skill in the art, having the teachings of Joseph, Siegel, Hu, Patel, Dennis, Ramasamy and Fromherz available before the effective filing date of the claimed invention, to modify the capability of management of high-volume concurrent processes as disclosed by Joseph, Siegel, Hu, Patel, Dennis and Ramasamy to include the capability of status reporting as taught by Fromherz, thereby providing a mechanism to enhance system efficiency by implementing an automated performance status report.
29. As per claim 11, it is a system claim having similar limitations as cited in claim 4. Thus, claim 11 is also rejected under the same rationale as cited in the rejection of claim 4 above.
30. As per claim 18, it is a media claim having similar limitations as cited in claim 4. Thus, claim 118 is also rejected under the same rationale as cited in the rejection of claim 4 above.
Conclusion
31. Any inquiry concerning this communication or earlier communications from the examiner should be directed to WILLIAM C WOOD whose telephone number is (571)272-5285. The examiner can normally be reached Monday - Friday, 8:00 am - 4:30 pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Chat C Do can be reached at 571-272-3721. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/WILLIAM C WOOD/Examiner, Art Unit 2193
/Chat C Do/Supervisory Patent Examiner, Art Unit 2193
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