DETAILED ACTION
This communication is in response to the application filed on 06/20/2024 in which claims 1-21 are pending in the application. Claims 1, 8, and 17 are in independent form.
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
The information disclosure statement (IDS) submitted on July 10th, 2025 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 § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 3-4 rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
The term “near real-time” in claim 3-4 is a relative term which renders the claim indefinite. The term “near real-time” is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention.
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 AI*A 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.
Claims 1-4, 8, and 16-17 are rejected under 35 U.S.C. 103 as being unpatentable over Park (US 20180074856 A1) in view of You (WO 2020049489 A1) and Kumar (US 20060047464 A1).
As per claim 1 Park discloses a system comprising: at least one processor operatively connected to a memory, the at least one processor, when executing, is configured to receive event data from the data source [[0080] An event processing application is configured to listen to one or more input event streams];
process the event data from the data source [[0083] Continuous queries typically perform filtering and aggregation functions to discover and extract notable events from the input event streams.];
land the processed event data into the data sink [[0078] The notable events may then be sent to one or more event sinks (610, 212) in the form of one or more output event streams.];
However, Park does not explicitly teach wherein at least one processor, when executing, is configured to: receive data relating to a data source and data sink; establish, based on the received data relating to the data source and data sink, a connection between the data source and the data sink.
You teaches wherein at least one processor, when executing, is configured to: receive data relating to a data source and data sink [[0053] As illustrated in 411, the task processor 206 A transmits a stream data request to the stream registry 204. The stream data request may include a name of the stream, a type identifier associated with the stream, and a protocol associated with the stream. At 412, the stream registry 204 responds to the task processor with a endpoint.];
establish, based on the received data relating to the data source and data sink, a connection between the data source and the data sink [[0049] At 312, the stream registry 204 is configured to send a create message to the stream broker 208B. The create message may be configured to create a connection between the stream broker 208B and the sink 302.];
Park and You are in the same field of endeavor, and they are both in stream event processing and, therefore, are combinable/modifiable.
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention was made to modify the stream processing of data received by the source taught by Park with the establishment of connection between source and sink taught by You. You modifies Park’s teachings by first initiating the system to connect a data source to a data sink by selecting a connection string from a plurality of data provided by the registry before initiating the stream processing taught by Park.
Modification would optimize operation of the system to handle multiple sources and multiple sinks and establish connections between dynamically interchangeable sources and sinks thereby processing multiple streams of data efficiently as taught by You [0004].
However, Park does not explicitly teach wherein the processor is configured to perform one or more operations on the processed event data in the data sink and provide an output of the one or more operations as input to the data source.
Kumar teaches wherein the processor is configured to perform one or more operations on the processed event data in the data sink and provide an output of the one or more operations as input to the data source [[0085] It is to be appreciated that the event handler engine can process the event received and transmit the associated output to the logical source queue (e.g., work item queue) addressed to a parent logical source.].
Park and Kumar are in the same field of endeavor, and they are both in data event processing and, therefore, are combinable/modifiable.
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention was made to modify the stream processing of data received by the source taught by Park with the processing of data landed in the sink taught by Kumar. Kumar further modifies the real-time operations processed as soon as data is received from the source as taught by Park by teaching further processing to be executed on the data landed in the sink, and using the results of the processing as an input to the data source.
Modification would as optimize operation of the system by pipelining events landed in the sink to the source to configure processing dynamically as needed by user requirement taught by Kumar [0014].
As per claim 2, Park discloses the system of claim 1, wherein the one or more operations performed on the processed data is configured to monitor changes on the processed event data landed in the data sink. [0025] For events received via an event stream, the time information associated with an event may be used to ensure that the events in the event stream arrive in the order of increasing timestamp values. This may enable events received in the event stream to be ordered based upon their associated time information.]
As per claim 3. Park discloses the system of claim 2, wherein the data sink is a change stream configured to access real-time or near real-time changes in the processed event data landed in the change stream. [[0078] The notable events may then be sent to one or more event sinks (610, 212) in the form of one or more output event streams. [0082] The processing of event streams requires processing of the events in real-time as the events are received by EPS 202 without having to store all the received events data. Accordingly, EPS 202 provides a special querying mechanism that enables processing of events to be performed as the events are received by EPS 202 without having to store all the received events.].
As per claim 4, Park discloses the system of claim 3, wherein the data source is the change stream and the event data received from the data source include the real-time or near real-time changes in the processed event data landed in the change stream. [[0083] Continuous queries may be persisted to a data store and used for processing input streams of events and generating output streams of events. [0082] The processing of event streams requires processing of the events in real-time as the events are received by EPS 202 without having to store all the received events data. Accordingly, EPS 202 provides a special querying mechanism that enables processing of events to be performed as the events are received by EPS 202 without having to store all the received events.].
As per claim 8 Park discloses a system comprising: at least one processor operatively connected to a memory, the at least one processor, when executing, is configured:
wherein at least one of the plurality of data sources is a boundless data source [[0200] In certain embodiments, communications subsystem 924 may be configured to receive data in the form of continuous data streams, which may include event streams 928 of real-time events and/or event updates 930, that may be continuous or unbounded in nature with no explicit end.];
receive event data from the plurality of data sources [[0080] An event processing application is configured to listen to one or more input event streams];
process the event data by performing one or more aggregation operations on the event data received from the data source [[0083] Continuous queries typically perform filtering and aggregation functions to discover and extract notable events from the input event streams.];
and land the processed event data into the data sink [[0078] The notable events may then be sent to one or more event sinks (610, 212) in the form of one or more output event streams.];
However, Park does not explicitly teach wherein at least one processor, when executing, is configured to: receive data relating to a plurality of data sources and a data sink and establish, establish, based on the received data relating to the plurality of data sources and the data sinks, a connection between the plurality of data sources and the data sink.
You teaches wherein at least one processor, when executing, is configured to: receive data relating to a plurality of data sources and a data sink [[0053] As illustrated in 411, the task processor 206 A transmits a stream data request to the stream registry 204. The stream data request may include a name of the stream, a type identifier associated with the stream, and a protocol associated with the stream. At 412, the stream registry 204 responds to the task processor with a endpoint.].
establish, based on the received data relating to the plurality of data sources and the data sinks, a connection between the plurality of data sources and the data sink [[0049] At 312, the stream registry 204 is configured to send a create message to the stream broker 208B. The create message may be configured to create a connection between the stream broker 208B and the sink 302.].
Park and You are in the same field of endeavor, and they are both in stream event processing and, therefore, are combinable/modifiable.
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention was made to modify the stream processing of data received by the source taught by Park with the establishment of connection between source and sink taught by You. You modifies Park’s teachings by first initiating the system to connect a data source to a data sink by selecting a connection string from a plurality of data provided by the registry before initiating the stream processing taught by Park.
Modification would optimize operation of the system to handle multiple sources and multiple sinks and establish connections between dynamically interchangeable sources and sinks thereby processing multiple streams of data efficiently as taught by You [0004].
As per claim 16, Park teaches the method of claim 8 as detailed above. However, Park does not explicitly teach wherein the data relating to the data source and the data sink is received from a connection registry configured to store connection strings and metadata associated with the plurality of data sources and the data sink.
You discloses the system of claim 8, wherein the data relating to the data source and the data sink is received from a connection registry configured to store connection strings and metadata associated with the plurality of data sources and the data sink [[0046] The stream registry 204 may be embodied by an apparatus that may include memory to store the configurations and records of all registered streams for run-time querying (e.g., data look-up service), for example, by media processing functions. [0049] At 312, the stream registry 204 is configured to send a create message to the stream broker 208B. The create message may be configured to create a connection between the stream broker 208B and the sink 302. At 313, the stream registry 204 sends an endpoint address and parameters to the sink 302].
Park and You are in the same field of endeavor, and they are both in stream event processing and, therefore, are combinable/modifiable.
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention was made to modify the stream processing of data received by the source taught by Park with the receiving data from a registry containing connection strings and metadata regarding the data sources and sinks taught by You. You further modifies Park’s teachings by first initiating the system to connect a data source to a data sink by selecting a connection string from a plurality of data provided by the registry before initiating the stream processing taught by Park.
Modification would optimize operation of the system to handle multiple sources and multiple sinks and establish connections between dynamically interchangeable sources and sinks using connection strings and metadata stored in the registry efficiently as taught by You [0004].
As per claim 17, the claim is rejected using the same rationale as noted above for claim 8.
Claims 5-7 are rejected under 35 U.S.C. 103 as being unpatentable over Park (US 20180074856 A1) in view of You (WO 2020049489 A1) and Kumar (US 20060047464 A1), as applied to claim 1, in further view of Klaedtke (US 20210124746 A1).
As per claim 5, Park, You, and Kumar teach the method of claim 1 as detailed above. However, Park, You, and Kumar do not explicitly teach wherein the one or more operations are performed as a chaining of operations on the processed event data in the data sink.
Klaedtke discloses the system of claim 1, wherein the one or more operations are performed as a chaining of operations on the processed event data in the data sink [[0032] Each pipeline stage performs a certain operation on the stream elements and continuously produces output (i.e., another data stream), which is forwarded to a next pipeline stage].
Klaedtke, Park, You, and Kumar are in the same field of endeavor and they are both in the stream event processing and, therefore, are combinable/modifiable.
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention was made to modify the teachings of Park, You, and Kumar with the teachings of Klaedtke to specify that the processes executed on the event in the data sink are performed as a chaining of operations.
Modification would optimize the system by carrying out the processing steps as a set of pipeline stages, feeding each output into the input stream of the next stage and thus, allowing some stages to be executed in parallel and reduce potential bottlenecks as taught by Klaedtke [0032].
As per claim 6, Park, You, and Kumar teach the method of claim 1 as detailed above. However, Park, You, and Kumar do not explicitly teach the system of claim 5, wherein the chaining of operations is implemented in an aggregation pipeline.
Klaedtke discloses the system of claim 5, wherein the chaining of operations is implemented in an aggregation pipeline [[0032] After receiving the stream elements they are first sanitized before the data items of the relevant stream elements are aggregated in a separate stage.].
Klaedtke, Park, You, and Kumar are in the same field of endeavor and they are both in the stream event processing and, therefore, are combinable/modifiable.
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention was made to modify the teachings of Park, You, and Kumar with the teachings of Klaedtke to specify that the processes executed on the event in the data sink are performed in an aggregation pipeline.
Modification would optimize the system by carrying out the processing steps as a set of pipeline stages, feeding each output into the input stream of the next stage and thus, allowing some stages to be executed in parallel and reduce potential bottlenecks as taught by Klaedtke [0032].
As per claim 7, Park, You, and Kumar teach the method of claim 1 as detailed above. However, Park, You, and Kumar do not explicitly teach the system of claim 6, wherein the one or more operations are performed in different stages of the aggregation pipeline.
Klaedtke discloses the system of claim 6, wherein the one or more operations are performed in different stages of the aggregation pipeline [[0032] Each pipeline stage performs a certain operation on the stream elements].
Klaedtke, Park, You, and Kumar are in the same field of endeavor and they are both in the stream event processing and, therefore, are combinable/modifiable.
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention was made to modify the teachings of Park, You, and Kumar with the teachings of Klaedtke to specify that the processes executed on the event in the data sink are performed in different stages of an aggregation pipeline.
Modification would optimize the system by carrying out the processing steps as a set of pipeline stages, feeding each output into the input stream of the next stage and thus, allowing some stages to be executed in parallel and reduce potential bottlenecks as taught by Klaedtke [0032].
Claims 9-10, 12, 18, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Park (US 20180074856 A1) in view of You (WO 2020049489 A1) and Kumar (US 20060047464 A1), as applied to claim 8, in further view of Zenger (US 20180357266 A1).
As per claim 9, Park, You, and Kumar teach the method of claim 8 as detailed above. However, Park, You, and Kumar do not explicitly teach wherein the one or more aggregation operations include a plurality of data operations to be executed on first event data and second event data.
Zenger discloses the system of claim 8, wherein the one or more aggregation operations include a plurality of data operations to be executed on first event data and second event data. [[0133] To illustrate, the processor 104 may perform a first normalization operation 204 on the first source data 112 to generate the first normalized data 206. The processor 104 may perform the first event extraction operation 216 on the first normalized data 206 to extract events from the first normalized data 206 and generate the first event stream data 218. The processor 104 may perform the second normalization operation 222 on the second source data 114 to generate the second normalized data 224. The processor 104 may perform the second event extraction operation 226 on the second normalized data 224 to extract events from the second normalized data 224 and to generate the second event stream data 228.]
Zenger, Park, You, and Kumar are in the same field of endeavor, and they are both in the stream event processing and, therefore, are combinable/modifiable.
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention was made to modify the teachings of Park, You, and Kumar with the teachings of Zenger to specify that the aggregation operations performed on the data received from a plurality of sources may consist of a plurality of operations including normalization and event extraction operations as taught by Zenger.
Modification would optimize the system by carrying out a multitude of operations to aggregate data from different sources to format the data according to user specifications and further enable inputting data from various sources into analytics applications as taught by Zenger [0029].
As per claim 10, Park, You, and Kumar teach the method of claim 8 as detailed above. However, Park, You, and Kumar do not explicitly teach the system of claim 9, wherein the first event data is received from a first data source of the plurality of data sources and the second event data is received from a second data source of the plurality of data sources.
Zenger discloses the system of claim 9, wherein the first event data is received from a first data source of the plurality of data sources and the second event data is received from a second data source of the plurality of data sources. [[0133] For example, the processor 104 may generate the event stream data 140 based on the first source data 134 and the second source data 138. The processor 104 may output the event stream data 140 to the storage device 124 for storage. The event stream data represents a first event extracted from the first source data and a second event extracted form the second source data.].
Zenger, Park, You, and Kumar are in the same field of endeavor, and they are both in the stream event processing and, therefore, are combinable/modifiable.
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention was made to modify the teachings of Park, You, and Kumar with the teachings of Zenger to specify that the first event data is received from a data source separate to the second event data used for the aggregation operations done on a plurality of data sources.
Modification would optimize the system by carrying out a multitude of operations to aggregate data from different sources to format the data according to user specifications and further enable inputting data from various sources into analytics applications as taught by Zenger [0029].
As per claim 12, Park, You, and Kumar teach the method of claim 8 as detailed above. However, Park, You, and Kumar do not explicitly teach the system of claim 9, wherein performing one or more aggregation operations on the event data received from the plurality of data sources comprises: performing a first operation on the first event data to obtain a first data result; performing a second operation on the second event data to obtain a second data result; and combining the first data result and the second data result to produce the processed event data.
Zenger discloses the system of claim 9, wherein performing one or more aggregation operations on the event data received from the plurality of data sources comprises: performing a first operation on the first event data to obtain a first data result [[0133] To illustrate, the processor 104 may perform a first normalization operation 204 on the first source data 112 to generate the first normalized data 206. The processor 104 may perform the first event extraction operation 216 on the first normalized data 206 to extract events from the first normalized data 206 and generate the first event stream data 218.];
performing a second operation on the second event data to obtain a second data result [[0133] The processor 104 may perform the second normalization operation 222 on the second source data 114 to generate the second normalized data 224. The processor 104 may perform the second event extraction operation 226 on the second normalized data 224 to extract events from the second normalized data 224 and to generate the second event stream data 228.];
and combining the first data result and the second data result to produce the processed event data. [[0029] The processor 104 may perform the event stream combination operation 220 on the first event stream data 218 and the second event stream data 228 to generate the event stream data 140.]
Zenger, Park, You, and Kumar are in the same field of endeavor, and they are both in the stream event processing and, therefore, are combinable/modifiable.
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention was made to modify the teachings of Park, You, and Kumar with the teachings of Zenger to specify that one of the aggregation operations performed on the source data involves combining the first data result performed on event data from a first source with the second data result performed on event data from a second source.
Modification would optimize the system by carrying out a multitude of operations to aggregate data from different sources to format the data according to user specifications and further enable inputting data from various sources into analytics applications as taught by Zenger [0029].
As per claim 18, the claim is rejected using the same rationale as noted above for claim 9.
As per claim 20, the claim is rejected using the same rationale as noted above for claim 12.
Claim(s) 13-14 and 21 is/are rejected under 35 U.S.C. 103 as being unpatentable over Park (US 20180074856 A1) in view of You (WO 2020049489 A1) and Kumar (US 20060047464 A1) and Zenger (US 20180357266 A1), as applied to claim 8, in further view of Kercheville (US 20200177469 A1).
As per claim 13, Park, You, Kumar, and Zenger teach the method of claim 12 as detailed above. However, Park, You, Kumar, and Zenger do not explicitly teach wherein performing one or more aggregation operations on the event data received from the plurality of data sources comprises creating an output data structure including the first data result and the second data result.
Kercheville discloses wherein performing one or more aggregation operations on the event data received from the plurality of data sources comprises creating an output data structure including the first data result and the second data result [[0017] The operations also comprise collecting, for each of the plurality of events, first event data regarding first event dimensions, the first event dimensions comprising an event time and an event location; and collecting, for each of the plurality of events, second event data regarding second event dimensions, the second event dimensions determined at least in part by the event type. The operations further comprise generating, for each of the plurality of event types, an event data structure based on the first event data and the second event data, thereby generating a plurality of event data structures associated with the target user.].
Kercheville, Zenger, Park, You, and Kumar are in the same field of endeavor, and they are both in the stream event processing and, therefore, are combinable/modifiable.
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention was made to modify the teachings of Park, You, Kumar, and Zenger with the teachings of Kercheville to specify that one or more aggregation operations on the event data received from the plurality of data sources comprises creating an output data structure including the first data result and the second data result.
Modification would optimize the system by grouping event data streams into a data structure to generate analytics or graphs to serve as output for further analysis including for example, generating an event history flow to detect one or more causal events and thereby facilitating prediction of a future event as taught by Kercheville [0017].
As per claim 14, Park, You, Kumar, and Zenger teach the method of claim 12 as detailed above. However, Park, You, Kumar, and Zenger do not explicitly teach discloses the system of claim 13, wherein creating the output data structure comprises grouping the first event data and the second event data.
Kercheville discloses the system of claim 13, wherein creating the output data structure comprises grouping the first event data and the second event data [[0017] The operations also comprise concatenating the plurality of event data structures to generate an event history flow associated with the target user, and analyzing the event history flow to identify, for a detected event of the plurality of events, one or more causal events of the plurality of events.].
Kercheville, Zenger, Park, You, and Kumar are in the same field of endeavor, and they are both in the stream event processing and, therefore, are combinable/modifiable.
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention was made to modify the teachings of Park, You, Kumar, and Zenger with the teachings of Kercheville to specify that one or more aggregation operations on the event data received from the plurality of data sources comprises creating an output data structure including the first data result and the second data result.
Modification would optimize the system by grouping event data streams into a data structure to generate analytics or graphs to serve as output for further analysis including, for example, generating an event history flow to detect one or more causal events and thereby facilitating prediction of a future event as taught by Kercheville [0017].
As per claim 21, the claim is rejected using the same rationale as claim 13.
Claims 11, 15, and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Park (US 20180074856 A1) in view of You (WO 2020049489 A1), Kumar (US 20060047464 A1), and Zenger (US 20180357266 A1), as applied to claim 8, in further view of Dickey (US 11314737 B2). .
As per claim 11, Park, You, Kumar, and Zenger teach the method of claim 9 as detailed above. However, Park, You, Kumar, and Zenger do not explicitly teach wherein performing one or more aggregation operations on the first and second event data received comprises identifying a common field of the first event data and the second event data.
Dickey discloses the system of claim 9, wherein performing one or more aggregation operations on the first and second event data received comprises identifying a common field of the first event data and the second event data [(73) A rules comparison engine 208 in remote capture agent 250 may receive events from event generator 207 and compare one or more fields from the events to a set of filtering rules in the configuration information to determine whether to include the events in an event stream. For example, the configuration information may specify packet-level, protocol-level, and/or application-level filtering of event data from event streams generated by remote capture agent 250.].
Dickey, Zenger, Park, You, and Kumar are in the same field of endeavor, and they are both in the stream event processing and, therefore, are combinable/modifiable.
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention was made to modify the one or more aggregation operations on the first and second event data taught by Park, You, Kumar, and Zenger with the teachings of Dickey to specify that one of those aggregation operations comprises identifying a common field of the first event data and the second event data. The remote capture agents, as taught by Dickey, are processors configured to receive event stream and perform aggregation operations on them which include comparing and identifying common fields between events.
Modification would optimize the system by generating several event processing operations configured to filter which events will be included in the event data stream such as an interval between consecutive events or the inclusion of transactions or errors to further customize the event stream according to user input specifications as taught by Dickey (67).
As per claim 15, Park, You, Kumar, and Zenger teach the method of claim 9 as detailed above. However, Park, You, Kumar, and Zenger do not explicitly teach the system of 11, wherein the one or more aggregation operations include at least one of comparisons of the first and second event data, string manipulations of the first and second event data, expression matching of the first and second event data, and/or calculation of metrics of grouped data of the first and second event data.
Dickey discloses the system of 11, wherein the one or more aggregation operations include at least one of comparisons of the first and second event data, string manipulations of the first and second event data, expression matching of the first and second event data, and/or calculation of metrics of grouped data of the first and second event data [(50) The configuration information may also specify transformations of network data and/or events into transformed events. Such transformations may include, for example, aggregations of network data and/or events, generation of statistics and/or metrics from the network data or events, and/or cleaning and/or filtering of the network data and/or events.].
Dickey, Zenger, Park, You, and Kumar are in the same field of endeavor, and they are both in the stream event processing and, therefore, are combinable/modifiable.
It would have been obvious to a person of ordinary skill in the art before the effective filing date of the claimed invention was made to modify the one or more aggregation operations on the first and second event data taught by Park, You, Kumar, and Zenger with the teachings of Dickey to specify that one of those aggregation operations comprises calculation of metrics of grouped data of the first and second event data.
Modification would optimize the system by generating several event processing operations configured to filter which events will be included in the event data stream based on grouped data of the first and second event data such as an interval between consecutive events or the inclusion of transactions or errors to further customize the event stream according to user input specifications as taught by Dickey (67).
As per claim 19, the claim is rejected using the same rationale as noted above for claim 11.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
US 11650995 B2 to Kulkarni teaches a method of event data processing such that a particular processing pipeline can obtain data from a plurality of user defined data streams to more efficiently extract user defined events and queries [(62) During operation, the data intake and query system receives machine data from any type and number of sources (e.g., one or more system logs, streams of network packet data, sensor data, application program data, error logs, stack traces, system performance data, etc.). The system parses the machine data to produce events each having a portion of machine data associated with a timestamp. The system stores the events in a data store.].
US 20240411621 A1 to Dinkel teaches a method to route certain event data structures to certain event dispatchers based on a set of predefined event parameter rules for respective event processors of a set of event processors in order to improve performance [ [0091] In one or more embodiments, the event data structure analysis component 404 and/or the event processor selection component 406 perform routing and/or processing of the event data structure 306 to improve performance of one or more assets and/or one or more operational processes in an operational environment.].
US 20160182652 A1 to Bevilacqua teaches an apparatus to route certain event data structures to sinks through event connectors in a loosely-coupled manner in order to easily add new data sources and data sinks to the apparatus without modifying the whole landscape [[0024] According to certain example embodiments, events are used in combination with the data in that the events are created and intelligently routed to enable the correct parts of the data to reach the correct consumers in a loosely-coupled fashion such that it becomes easy to add new data sources and data sinks to the integration without an understanding of or modifications to the entire landscape)].
Any inquiry concerning this communication or earlier communications from the examiner should be directed to PHEBE TAN whose telephone number is (571)270-7591. The examiner can normally be reached Monday-Friday (9am-5pm).
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October 5, 2026
/PHEBE TAN/ Examiner, Art Unit 2198
/PIERRE VITAL/ Supervisory Patent Examiner, Art Unit 2198
