DETAILED ACTION
Status of the Application
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA . This communication is a non-final action in response to application filed on 10/30/2023. Claims 1-20 are currently pending and have been considered below.
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.
Claims 1-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to non-statutory subject matter. Claims 1-20 are determined to be directed to an abstract idea.
The claims 1-20 are directed to a judicial exception (i.e., law of nature, natural phenomenon, or abstract idea), without providing a practical application integration and without providing significantly more.
As per Step 1 of the subject matter eligibility analysis, Claims 1-14 are directed to a method and system (i.e., apparatus) which are within the four statutory categories of invention. Claims 15-20 include signals per se and fail Step 1 of the analysis (MPEP 2106.03). Applicants may amend the claims to clearly state computer readable storage medium being “non-transitory”. Further note that claim term “computer readable storage medium” does not match the term in para. 0072 which attempts to define a medium excluding transitory signals.
As per Step 2A-Prong 1 of the subject matter eligibility analysis, Claims 1, 8, and 15 are directed specifically to the abstract idea of receiving a selection of a filtering condition from among a plurality of filtering conditions based on input [by] user; in response to receipt of the selection, filtering a plurality of data records based on the filtering condition to identify a subset of data records that satisfy the filtering condition from among the plurality of data records; identifying a subset of filtering conditions from among the plurality of filtering conditions that are available for the subset of data records; and displaying an identifier of the subset of data records and identifiers of the subset of filtering conditions that are available for the subset of data records [to] the user; which include mental processes (observing and evaluating and judgment for data using conditions/filters), and certain methods of organizing human activity based on fundamental economic practice (managing business/organization data or metrics via user selected filters), and managing personal behavior and interactions between people (following rules and instructions to filter data or metrics via user selected filters). Claims 2-7, 9-14, and 16-20 are directed to the abstract idea of claim 1, 8, or 15 with further details on the parameters/attributes of the abstract idea which includes mental processes and certain methods of organizing human activity for similar reasons as provided above for claim 1, 8, or 15. After considering all claim elements, both individually and in combination and in ordered combination, it has been determined that the claims do not amount to significantly more than the abstract idea itself.
As per Step 2A-Prong 2 of the subject matter eligibility analysis, while the claims 1-20 recite additional limitations which are hardware or software elements, such as computing system comprising: a data store configured to store a plurality of data records; and a processor configured to display a user interface comprising interactive controls, user interface, computer-readable storage medium comprising instructions which when executed by a processor cause a computer to perform: displaying a user interface comprising interactive controls; these limitations are not enough to qualify as a practical application being recited in the claims along with the abstract idea since these elements are merely invoked as a tool to apply instructions of an abstract idea in a particular technological environment, and mere application of an abstract idea in a particular technological environment and merely limiting the use of an abstract idea to a particular technological field do not integrate an abstract idea into a practical application (MPEP 2106.05(f)&(h)). The claims do not amount to "practical application" for the abstract idea because they neither (1) recite any improvements to another technology or technical field; (2) recite any improvements to the functioning of the computer itself; (3) apply the judicial exception with, or by use of, a particular machine; (4) effect a transformation or reduction of a particular article to a different state or thing; (5) provide other meaningful limitations beyond generally linking the use of the judicial exception to a particular technological environment.
As per Step 2B of the subject matter eligibility analysis, while the claims 1-20 recite additional limitations which are hardware or software elements, such as a computing system comprising: a data store configured to store a plurality of data records; and a processor configured to display a user interface comprising interactive controls, user interface, computer-readable storage medium comprising instructions which when executed by a processor cause a computer to perform: displaying a user interface comprising interactive controls; these limitations are not enough to qualify as “significantly more” being recited in the claims along with the abstract idea since these elements are merely invoked as a tool to apply instructions of an abstract idea in a particular technological environment, and mere application of an abstract idea in a particular technological environment and merely limiting the use of an abstract idea to a particular technological field do provide significantly more to an abstract idea (MPEP 2106.05 (f) & (h)). The claims do not amount to "significantly more" than the abstract idea because they neither (1) recite any improvements to another technology or technical field; (2) recite any improvements to the functioning of the computer itself; (3) apply the judicial exception with, or by use of, a particular machine; (4) effect a transformation or reduction of a particular article to a different state or thing; (5) add a specific limitation other than what is well-understood, routine and conventional in the field; (6) add unconventional steps that confine the claim to a particular useful application; nor (7) provide other meaningful limitations beyond generally linking the use of the judicial exception to a particular technological environment.
Therefore, since there are no limitations in the claims 1-20 that transform the exception into a patent eligible application such that the claims amount to significantly more than the exception itself, and looking at the limitations as an ordered combination adds nothing that is not already present when looking at the elements taken individually, the claims are rejected under 35 USC § 101 as being directed to non-statutory subject matter.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
Claims 1-20 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by TANKERSLEY et al (US 20180024901 A1).
As per Claim 1, TANKERSLEY teaches a computing system (claim 21) comprising:
a data store configured to store a plurality of data records; and a processor configured to (claim 21, “system, comprising: a memory that includes an update module; and a processor that is coupled to the memory and, when executing the update module, performs the steps of: retrieving a set of item definitions stored to a data store”)
display a user interface comprising interactive controls (Fig. 10AD-10AE, para. 0549, “FIG. 10AD-10AE illustrate examples of GUIs facilitating user input for filtering entity definitions using informational field-value data, in accordance with one or more implementations of the present disclosure. In FIG. 10AD, GUI 35400 includes a search field 35410. Search field 35410 can receive user input including a search query command (e.g., “getentity” or “getentity generate”).”; also see Figs. 70B-70F and Figs. 17K-17Q);
receive a selection of a filtering condition from among a plurality of filtering conditions based on input on an interactive control on the user interface (Fig. 10AD-10AE, para. 0549, “FIG. 10AD-10AE illustrate examples of GUIs facilitating user input for filtering entity definitions using informational field-value data, in accordance with one or more implementations of the present disclosure. In FIG. 10AD, GUI 35400 includes a search field 35410. Search field 35410 can receive user input including a search query command (e.g., “getentity” or “getentity generate”).”, para. 0550, “Referring to FIG. 10AE, GUI 35500 also includes a search field 35510. Search field 35510 can receive user input including a search query command (e.g., “getentity” or “getentity generate”) as well as selection criteria including a first-field value pair. As described above, execution of the “getentity” or “getentity generate” command” returns all or a subset of all entity definitions that have been created. The inclusion of the selection criteria (e.g., “search os=linux”) further filters the results of the “getentity” or “getentity generate” command to limit the returned entity definitions to those having an informational field-value pair that matches the selection criteria. A corresponding entry for each filtered entity definition may be displayed in search results region 35520 of GUI 35500.”; Figs. 70B-70F and Figs. 17K-17Q);
in response to receipt of the selection, filter the plurality of data records based on the filtering condition to identify a subset of data records that satisfy the filtering condition from among the plurality of data records (Fig. 10AD-10AE, para. 0549, “FIG. 10AD-10AE illustrate examples of GUIs facilitating user input for filtering entity definitions using informational field-value data, in accordance with one or more implementations of the present disclosure. In FIG. 10AD, GUI 35400 includes a search field 35410. Search field 35410 can receive user input including a search query command (e.g., “getentity” or “getentity generate”).”, para. 0550, “Referring to FIG. 10AE, GUI 35500 also includes a search field 35510. Search field 35510 can receive user input including a search query command (e.g., “getentity” or “getentity generate”) as well as selection criteria including a first-field value pair. As described above, execution of the “getentity” or “getentity generate” command” returns all or a subset of all entity definitions that have been created. The inclusion of the selection criteria (e.g., “search os=linux”) further filters the results of the “getentity” or “getentity generate” command to limit the returned entity definitions to those having an informational field-value pair that matches the selection criteria. A corresponding entry for each filtered entity definition may be displayed in search results region 35520 of GUI 35500.”; Figs. 70B-70F and Figs. 17K-17Q);
identify one or more additional filtering conditions for the subset of data records from among the plurality of filtering conditions (Fig. 10AD-10AE, para. 0549, “FIG. 10AD-10AE illustrate examples of GUIs facilitating user input for filtering entity definitions using informational field-value data, in accordance with one or more implementations of the present disclosure. In FIG. 10AD, GUI 35400 includes a search field 35410. Search field 35410 can receive user input including a search query command (e.g., “getentity” or “getentity generate”).”, para. 0550, “Referring to FIG. 10AE, GUI 35500 also includes a search field 35510. Search field 35510 can receive user input including a search query command (e.g., “getentity” or “getentity generate”) as well as selection criteria including a first-field value pair. As described above, execution of the “getentity” or “getentity generate” command” returns all or a subset of all entity definitions that have been created. The inclusion of the selection criteria (e.g., “search os=linux”) further filters the results of the “getentity” or “getentity generate” command to limit the returned entity definitions to those having an informational field-value pair that matches the selection criteria. A corresponding entry for each filtered entity definition may be displayed in search results region 35520 of GUI 35500.”; Figs. 70B-70F and Figs. 17K-17Q), and
display an identifier of the subset of data records and identifiers of the one or more additional filtering conditions for the subset of data records on the user interface (Fig. 10AD-10AE, para. 0549, “FIG. 10AD-10AE illustrate examples of GUIs facilitating user input for filtering entity definitions using informational field-value data, in accordance with one or more implementations of the present disclosure. In FIG. 10AD, GUI 35400 includes a search field 35410. Search field 35410 can receive user input including a search query command (e.g., “getentity” or “getentity generate”).”, para. 0550, “Referring to FIG. 10AE, GUI 35500 also includes a search field 35510. Search field 35510 can receive user input including a search query command (e.g., “getentity” or “getentity generate”) as well as selection criteria including a first-field value pair. As described above, execution of the “getentity” or “getentity generate” command” returns all or a subset of all entity definitions that have been created. The inclusion of the selection criteria (e.g., “search os=linux”) further filters the results of the “getentity” or “getentity generate” command to limit the returned entity definitions to those having an informational field-value pair that matches the selection criteria. A corresponding entry for each filtered entity definition may be displayed in search results region 35520 of GUI 35500. In one implementation, various columns are displayed for each entry in search results region 35520, including for example, informational field column 35521 and alias columns 35522 and 35523. In the illustrated example, there is only one entry in search results region 35520 indicating that only one entity definition included an informational field-value pair that matched the selection criteria entered in search field 35510. As shown, the entry includes an information field column 25521 named “os” which includes the value of “linux.” This metadata field name and metadata value match the query field name and query value (i.e., “os=linux”) from the event selection criteria. In the illustrated example, the entry also includes at least two alias columns 35522 and 35523. These alias columns “dest_mac” 35522 and “src_mac” 35523 include alias values (e.g., “10:10:10:10:40:40”) that can be used to locate events in a machine data store that satisfy the event selection criteria. By having the information field and aliases stored as part of the entity definition, the informational field values can be associated with the events that are determined to correspond to the entity using an alias. Upon having identified the entity definition, the computing machine can locate and return events from the machine data store that satisfy the event selection criteria. As such, the user can filter events using the information fields.”; Figs. 70B-70F and Figs. 17K-17Q).
As per Claim 2, TANKERSLEY teaches a method as recited above for Claim 1. TANKERSLEY further teaches wherein the processor is configured to display a bubble with an identifier of the subset of data records inside the bubble, and display one or more additional bubbles with identifiers of the one or more additional filtering conditions inside a plurality of bubbles, respectively (Fig. 10AD-10AE, para. 0549, “FIG. 10AD-10AE illustrate examples of GUIs facilitating user input for filtering entity definitions using informational field-value data, in accordance with one or more implementations of the present disclosure. In FIG. 10AD, GUI 35400 includes a search field 35410. Search field 35410 can receive user input including a search query command (e.g., “getentity” or “getentity generate”).”, para. 0550, “Referring to FIG. 10AE, GUI 35500 also includes a search field 35510. Search field 35510 can receive user input including a search query command (e.g., “getentity” or “getentity generate”) as well as selection criteria including a first-field value pair. As described above, execution of the “getentity” or “getentity generate” command” returns all or a subset of all entity definitions that have been created. The inclusion of the selection criteria (e.g., “search os=linux”) further filters the results of the “getentity” or “getentity generate” command to limit the returned entity definitions to those having an informational field-value pair that matches the selection criteria. A corresponding entry for each filtered entity definition may be displayed in search results region 35520 of GUI 35500. In one implementation, various columns are displayed for each entry in search results region 35520, including for example, informational field column 35521 and alias columns 35522 and 35523. In the illustrated example, there is only one entry in search results region 35520 indicating that only one entity definition included an informational field-value pair that matched the selection criteria entered in search field 35510. As shown, the entry includes an information field column 25521 named “os” which includes the value of “linux.” This metadata field name and metadata value match the query field name and query value (i.e., “os=linux”) from the event selection criteria. In the illustrated example, the entry also includes at least two alias columns 35522 and 35523. These alias columns “dest_mac” 35522 and “src_mac” 35523 include alias values (e.g., “10:10:10:10:40:40”) that can be used to locate events in a machine data store that satisfy the event selection criteria. By having the information field and aliases stored as part of the entity definition, the informational field values can be associated with the events that are determined to correspond to the entity using an alias. Upon having identified the entity definition, the computing machine can locate and return events from the machine data store that satisfy the event selection criteria. As such, the user can filter events using the information fields.”; also see figs. 70B-70J, regarding series of graphical elements (bubbles) to enter user selection, and further display of resulting data in graph with various bubbles (i.e., areas enclosed with/within different color shade or border)).
As per Claim 3, TANKERSLEY teaches a method as recited above for Claim 2. TANKERSLEY further teaches wherein the processor is configured to display the one or more additional bubbles with the identifiers of the one or more additional filtering conditions in parallel to the bubble with the identifier of the subset of data records on the user interface (Fig. 10AD-10AE, para. 0549, “FIG. 10AD-10AE illustrate examples of GUIs facilitating user input for filtering entity definitions using informational field-value data, in accordance with one or more implementations of the present disclosure. In FIG. 10AD, GUI 35400 includes a search field 35410. Search field 35410 can receive user input including a search query command (e.g., “getentity” or “getentity generate”).”, para. 0550, “Referring to FIG. 10AE, GUI 35500 also includes a search field 35510. Search field 35510 can receive user input including a search query command (e.g., “getentity” or “getentity generate”) as well as selection criteria including a first-field value pair. As described above, execution of the “getentity” or “getentity generate” command” returns all or a subset of all entity definitions that have been created. The inclusion of the selection criteria (e.g., “search os=linux”) further filters the results of the “getentity” or “getentity generate” command to limit the returned entity definitions to those having an informational field-value pair that matches the selection criteria. A corresponding entry for each filtered entity definition may be displayed in search results region 35520 of GUI 35500. In one implementation, various columns are displayed for each entry in search results region 35520, including for example, informational field column 35521 and alias columns 35522 and 35523. In the illustrated example, there is only one entry in search results region 35520 indicating that only one entity definition included an informational field-value pair that matched the selection criteria entered in search field 35510. As shown, the entry includes an information field column 25521 named “os” which includes the value of “linux.” This metadata field name and metadata value match the query field name and query value (i.e., “os=linux”) from the event selection criteria. In the illustrated example, the entry also includes at least two alias columns 35522 and 35523. These alias columns “dest_mac” 35522 and “src_mac” 35523 include alias values (e.g., “10:10:10:10:40:40”) that can be used to locate events in a machine data store that satisfy the event selection criteria. By having the information field and aliases stored as part of the entity definition, the informational field values can be associated with the events that are determined to correspond to the entity using an alias. Upon having identified the entity definition, the computing machine can locate and return events from the machine data store that satisfy the event selection criteria. As such, the user can filter events using the information fields.”; also see figs. 70B-70J, regarding series of graphical elements (bubbles) to enter user selection, and further display of resulting data in graph with various bubbles (i.e., areas enclosed with/within different color shade or border)).
As per Claim 4, TANKERSLEY teaches a method as recited above for Claim 1. TANKERSLEY further teaches wherein the processor is further configured to determine an amount of data records within the subset of data records that satisfy an additional filtering condition, and display an identifier of the additional filtering condition and the determined amount of data records that satisfy the additional filtering condition next to the identifier of the subset of data records within the user interface (Figs. 17K-17Q, especially regarding fig. 17L for displaying the count of results satisfying the conditions; para. 0753 “FIG. 17L depicts a user interface display related to service and entity discovery processing in one embodiment including a presentation of discovered items. Interface 17502 may represent a scrolled down version of interface display 17501 of FIG. 17K after certain user interaction. Interface 17502 of FIG. 17L is shown to include grouping options section 17576, previously described, and discovered entities display area 17620. Discovered entities display area 17620 is shown to include header row 17622, and a service entities display table that includes column header row 17630 and service entity entry rows 17632a to 17632j. Header row 17622 is shown to include a count of the discovered entities 17624, a display options selection element 17626, and display table page navigation elements 17628. Column header row 17630 is shown to include a column title or heading of “IP” for column 17642, “Port” for column 17644, “Hostname” for column 17646, and “Application” for column 17648. Each of service entity entry rows 17632a to 17632j displays information for a respective service entity identified by an execution of the search query. The search query result may include information in fields with names corresponding to the column headings appearing in row 17630. Each of the service entry rows additionally includes a result number in column 17640. A user may advantageously utilize the interface display 17502 to get immediate feedback on the propriety or effectiveness of the currently established service discovery session parameters. If the feedback is favorable and acceptable to the user, the user may interact with an action button such as “Next” button 17584 of interface 17501 of FIG. 17K to proceed with service discovery processing workflow.”; para. 0754 “FIG. 17M depicts a user interface display related to editing and confirmation of discovered items. User interface display 17503 is such as might be useful during the processing of blocks 17558, 17560, and/or 17562 of FIG. 17J. User interface display 17503 of FIG. 17M is shown to include workflow header 17570, workflow segment header 17650, and service association results display table 17660. Workflow segment header 17650 is shown to include segment title “Edit Discovery Results”, user prompting information, “Select entity import type and Edit Discovered Entities and Services”, import-type element 17652, bulk action element 17654, and filter element 17656. Import-type element 17652 is shown as a drop-down selection box containing the default or most-recently-selected value of “Always Append to Data store.” User interaction with import-type element 17652 may result in the appearance of a drop-down selection list of import types from which a user may make a selection, and may include options for incorporating the service discovery results into the service and entity definitional data of the CCC data store of the SMS such as “Always Append to Data store”, “Update existing and Add New”, “Retain existing and Add New”, and “Replace all contents of Data store”, for example. User interaction with bulk action element 17654 is shown as a drop-down selection box. User interaction with bulk action element 17654 may result in the appearance of a drop-down selection list of available bulk actions from which a user may make a selection, and may include options such as “Delete Selected”, “Edit Selected Entities”, and “Edit Selected Services”, for example. A bulk action may be an action that is specified and/or initiated once for iteration over some set of one or more objects, such as the logical set of all of the service entities represented in the service entity entry rows of a results display table such as 17660 that are in the selected state. Filter element 17656 is shown as a text box. Filter element 17656 is interactive and enables a user to enter and/or edit text representing filter criteria by which to qualify discovered service entities appearing in service association results display table 17660.”).
As per Claim 5, TANKERSLEY teaches a method as recited above for Claim 1. TANKERSLEY further teaches wherein the plurality of data records correspond to a plurality of organizations, and the plurality of filtering conditions correspond to a plurality of organizational metrics (Figs. 70B-70F, regarding the KPI CPU utilization).
As per Claim 6, TANKERSLEY teaches a method as recited above for Claim 1. TANKERSLEY further teaches wherein the processor is further configured to display a sub-menu with identifiers of the plurality of filtering conditions and a plurality of controls for selecting the plurality of filtering conditions, respectively, and receive a selection of a control within the sub-menu which selects a filtering condition from among the plurality of filtering conditions (Fig. 10AD-10AE, para. 0549, “FIG. 10AD-10AE illustrate examples of GUIs facilitating user input for filtering entity definitions using informational field-value data, in accordance with one or more implementations of the present disclosure. In FIG. 10AD, GUI 35400 includes a search field 35410. Search field 35410 can receive user input including a search query command (e.g., “getentity” or “getentity generate”).”, para. 0550, “Referring to FIG. 10AE, GUI 35500 also includes a search field 35510. Search field 35510 can receive user input including a search query command (e.g., “getentity” or “getentity generate”) as well as selection criteria including a first-field value pair. As described above, execution of the “getentity” or “getentity generate” command” returns all or a subset of all entity definitions that have been created. The inclusion of the selection criteria (e.g., “search os=linux”) further filters the results of the “getentity” or “getentity generate” command to limit the returned entity definitions to those having an informational field-value pair that matches the selection criteria. A corresponding entry for each filtered entity definition may be displayed in search results region 35520 of GUI 35500. In one implementation, various columns are displayed for each entry in search results region 35520, including for example, informational field column 35521 and alias columns 35522 and 35523. In the illustrated example, there is only one entry in search results region 35520 indicating that only one entity definition included an informational field-value pair that matched the selection criteria entered in search field 35510. As shown, the entry includes an information field column 25521 named “os” which includes the value of “linux.” This metadata field name and metadata value match the query field name and query value (i.e., “os=linux”) from the event selection criteria. In the illustrated example, the entry also includes at least two alias columns 35522 and 35523. These alias columns “dest_mac” 35522 and “src_mac” 35523 include alias values (e.g., “10:10:10:10:40:40”) that can be used to locate events in a machine data store that satisfy the event selection criteria. By having the information field and aliases stored as part of the entity definition, the informational field values can be associated with the events that are determined to correspond to the entity using an alias. Upon having identified the entity definition, the computing machine can locate and return events from the machine data store that satisfy the event selection criteria. As such, the user can filter events using the information fields.”; also see figs. 70B-70J, regarding series of graphical elements (bubbles) to enter user selection, and further display of resulting data in graph with various bubbles (i.e., areas enclosed with/within different color shade or border)).
As per Claim 7, TANKERSLEY teaches a method as recited above for Claim 1. TANKERSLEY further teaches wherein the processor is configured to receive a selection of a sequence of filtering conditions, and execute the sequence of filtering conditions in sequence on the plurality of data records to identify the subset of data records (Fig. 10AD-10AE, para. 0549, “FIG. 10AD-10AE illustrate examples of GUIs facilitating user input for filtering entity definitions using informational field-value data, in accordance with one or more implementations of the present disclosure. In FIG. 10AD, GUI 35400 includes a search field 35410. Search field 35410 can receive user input including a search query command (e.g., “getentity” or “getentity generate”).”, para. 0550, “Referring to FIG. 10AE, GUI 35500 also includes a search field 35510. Search field 35510 can receive user input including a search query command (e.g., “getentity” or “getentity generate”) as well as selection criteria including a first-field value pair. As described above, execution of the “getentity” or “getentity generate” command” returns all or a subset of all entity definitions that have been created. The inclusion of the selection criteria (e.g., “search os=linux”) further filters the results of the “getentity” or “getentity generate” command to limit the returned entity definitions to those having an informational field-value pair that matches the selection criteria. A corresponding entry for each filtered entity definition may be displayed in search results region 35520 of GUI 35500. In one implementation, various columns are displayed for each entry in search results region 35520, including for example, informational field column 35521 and alias columns 35522 and 35523. In the illustrated example, there is only one entry in search results region 35520 indicating that only one entity definition included an informational field-value pair that matched the selection criteria entered in search field 35510. As shown, the entry includes an information field column 25521 named “os” which includes the value of “linux.” This metadata field name and metadata value match the query field name and query value (i.e., “os=linux”) from the event selection criteria. In the illustrated example, the entry also includes at least two alias columns 35522 and 35523. These alias columns “dest_mac” 35522 and “src_mac” 35523 include alias values (e.g., “10:10:10:10:40:40”) that can be used to locate events in a machine data store that satisfy the event selection criteria. By having the information field and aliases stored as part of the entity definition, the informational field values can be associated with the events that are determined to correspond to the entity using an alias. Upon having identified the entity definition, the computing machine can locate and return events from the machine data store that satisfy the event selection criteria. As such, the user can filter events using the information fields.”; also see figs. 70B-70J, regarding series of graphical elements (bubbles) to enter user selection, and further display of resulting data in graph with various bubbles (i.e., areas enclosed with/within different color shade or border)).
As per claims 8-14, claims 8-14 recite substantially similar limitations as claim 1-7, respectively; therefore, claims 8-14 are rejected with the same reasoning, rationale and motivation as recited above for claims 1-7, respectively.
As per claims 15-20, claims 15-20 recite substantially similar limitations as claim 1-6, respectively; therefore, claims 15-20 are rejected with the same reasoning, rationale and motivation as recited above for claims 1-6, respectively.
As per claim 15, TANKERSLEY further teaches apparatus comprising: a computer-readable storage medium comprising instructions which when executed by a processor cause a computer to perform… (Claim 11).
Conclusion
Additional relevant art not relied upon includes:
Tankersley et al (US 20170147681 A1, US 20170083572 A1) and Fletcher et al (US 20170046374 A1, US 20170046127 A1, US 20160103887 A1, US 20160103888 A1, US 20160104091 A1, US 20160104093 A1, US 20160105325 A1, US 20160103908 A1), and Maheshwari et al (US 20170017368 A1, US 20170019487 A1, US 20160103559 A1, US 20160104076 A1) and Raghavan et al (US 20170004433 A1) and Gupta et al (US 20160366036 A1) and Boe et al (US 20160292611 A1) and Puri et al (US 20160294606 A1) and Sainani et al (US 20160103838 A1) and Ramani et al (US 20160103883 A1) and Alekseyev et al (US 20160103918 A1, US 20160104090 A1) regarding “FIG. 10AD-10AE illustrate examples of GUIs facilitating user input for filtering entity definitions using informational field-value data, in accordance with one or more implementations of the present disclosure. In Figure LOAD, GUI 35400 includes a search field 35410. Search field 35410 can receive user input including a search query command (e.g., “getentity” or “getentity generate”). In one implementation, execution of the command identifies one or more entity definitions. The specific “getentity” or “getentity generate” command may return all or a subset of all entity definitions that have been created, without using any specific filtering criteria. Additional filtering may be performed (e.g., using information fields), as shown in FIG. 10AE. A corresponding entry for each entity definition may be displayed in search results region 35420 of GUI 35400. In one implementation, various columns are displayed for each entry in search results region 35420, including for example, informational field names 35421, informational field values 35422, particular informational field names 35423 and 35424, alias names 35425, alias values 35426 and particular alias names 35427… In one example, GUI 34300 may receive a first user selection that identifies a subset of services from a list of services within an IT environment. In response to the first selection, GUI 34300 may display a list of KPIs associated with the one or more selected services within KPI display component 34320. GUI 34300 may then receive a second user selection of a subset of the KPIs in the KPI display component 34320. In response to the second selection, GUI 34300 may display one or more user-selected KPIs and graphical control elements in the weight adjustment display component 34330.”
Narechania et al (Arpit Narechania, Fan Du, Atanu R Sinha, Ryan A. Rossi, Jane Hoffswell, Shunan Guo, Eunyee Koh, Shamkant B. Navathe, Alex Endert; “DataPilot: Utilizing Quality and Usage Information for Subset Selection during Visual Data Preparation”, 2 March 2023, https://doi.org/10.48550/arXiv.2303.01575)
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MEHMET YESILDAG whose telephone number is (571)272-3257. The examiner can normally be reached M-F 8:30 am - 5:00 pm.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Jerry O'Connor can be reached on (571) 272-6787. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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Sincerely,
/MEHMET YESILDAG/Primary Examiner, Art Unit 3624
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