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 . Claims 1-20 are presented in the case.
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 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 of this title, 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 1-3, 5-6, 9, 12, 15, 17 and 19-20 are rejected under 35 U.S.C. 103 as being unpatentable over Anand et al. (US 20140129536 A1 hereinafter Anand) in view of Choudhary et al. (US 9158811 B1 hereinafter Choudhary).
As to independent claim 1, Anand teaches an apparatus [computer system ¶73] for outputting a past incident insight interface component in a software monitoring data management system, the apparatus comprising at least one processor, and at least one memory including program code, the at least one memory and the program code configured to, with the at least one processor, cause the apparatus to at least: [programs, processors and memory ¶73-74 for managing incidents ¶69]
detect a past incident insight interface component request in response to user interaction with a software monitoring data management system, [detects IT incident diagnosis request (query) with search software interface ¶24, ¶5 "a user interface operable to execute on a processor and issue a query. The system may also comprise a search engine operable to receive the query, transform the query into sub-queries comprising a structured search and a free-text search, and to search for co-occurring and reoccurring group of incidents"]
wherein the past incident insight interface component request is associated with a current incident data object; [related to a current incident data object (ticket or IT incident with ID, keywords and more) Fig. 1 102 ¶24-25"keywords are extracted from an incident ticket to classify the incident"]
identify a past incident candidate data object set based on the current incident data object;[Searches for co-occurring/similar incidents (set) based on first incident ID, keyworks or constraints Fig. 1 104 ¶35-38 "Relevant (co-occurring and reoccurring) incidents are searched for by keywords and constraints."…"To simplify its use, the search engine may require only an incident ID as an input""]
determine a primary ranking of the past incident candidate data object set or a subset thereof; [similarity score ranking (primary ranking) ¶24 "Use similarity score (e.g., Space vector model) to rank the returned results"]
determine one or more subsequent rankings of the primarily ranked past incident candidate data objects of the past incident candidate data object set or the subset thereof; [after similarity rank do a context relevance and final relevancy score for final results (subset) ¶47,¶24 "after the similarity score ranking, get a context relevancy weight by looking at account technology portfolio; 5) From the ranked list, return final search results"]
generate a past incident insight interface component comprising a listing of a past incident candidate data object suggestion set, the past incident candidate data object suggestion set listing one or more of the subsequently ranked past incident candidate data objects; and [dashboard interface ¶56, returns ranked and weighted list of results ¶4 "returning a top predetermined number of results from the ranked list of results."]
alerts [user views alerts ¶63 "When the system detects events satisfying the condition of the rules, the system generates and consolidates alerts; User views alerts and take actions."]
Anand does not specifically teach output the past incident insight interface component for rendering to an incident alert management user interface of a computing device associated with the past incident insight interface component request.
However, Choudhary teaches output the past incident insight interface component for rendering to an incident alert management user interface of a computing device associated with the past incident insight interface component request. [GUI for past events(incidents/alarms) including correlated results from filter request and actions for managing (Fig. 34O Col. 118 ln. 52-67 " results section 34570 of GUI 34550 displays one or more notable events that meet the filtering criteria entered in filtering controls section 34560, and displays certain information pertaining to those notable events. In one implementation, a corresponding entry for each notable event that satisfies the filtering criteria may be displayed in results section 34570. "]
Accordingly, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to modify the incident diagnosis by Anand by incorporating the output the past incident insight interface component for rendering to an incident alert management user interface of a computing device associated with the past incident insight interface component request disclosed by Choudhary because both techniques address the same field of event management and by incorporating Choudhary into Anand enables users to better understand the IT environment with improved monitoring and visualizations [Choudhary Col. 12 ln. 3-20].
As to dependent claim 2, the rejection of claim 1 is incorporated Anand and Choudhary further teach wherein the past incident insight interface component is configured to expose a first or summary level of information for at least a selected subsequently ranked past incident candidate data object of the past incident candidate data object suggestion set. [Choudhary description and event text (summary) of one event Fig. 34T 34605-34606 Col. 121 ln. 22-24 "notable event 34605 and the description of the notable event 34606 may display an explanation of how and why the notable event was generated"]
As to dependent claim 3, the rejection of claim 2 is incorporated Anand and Choudhary further teach wherein the first or summary level of information comprises one or more of an incident title, a team member identifier, a creation date, an incident identifier, or a visual emphasis element associated with a priority of the selected subsequently ranked past incident candidate data object. [Choudhary title Col. 118 ln. 62 "title 34573"]
As to dependent claim 5, the rejection of claim 1 is incorporated Anand and Choudhary further teach wherein the past incident insight interface component is configured to expose a second or detailed level of information for at least one of the subsequently ranked past incident candidate data objects of the past incident candidate data object suggestion set. [Choudhary detailed information Fig. 34T Col. 120 ln. 46-60 "GUI presenting detailed information pertaining to a notable event created as a result of a correlation search"]
As to dependent claim 6, the rejection of claim 5 is incorporated Anand and Choudhary further teach wherein the second or detailed level of information comprises one or more of a faulty service identifier, an affected product identifier, or a link to a post incident report associated with the at least one subsequently ranked past incident candidate data object. [Choudhary services (service identifier), link (34604 or investigation 34s 34596) Fig. 34T Col. 120 ln. 46-60 "possible affected services 34601, contributing KPIs 34602, a link to the correlation search that generated the notable event 34603, a history of activity for the notable event 34604, the original notable event 34605, a description of the notable event 34606, and/or other information"]
As to dependent claim 9, the rejection of claim 5 is incorporated Anand and Choudhary further teach wherein identifying the past incident candidate data object set based on the current incident data object comprises: identifying one or more incident categories of the current incident data object; [Anand extracts with categories ¶25]
accessing a plurality of past incident data objects; [Anand historical incident data ¶33, re-occurring data ¶20]
filtering the plurality of past incident data objects based on at least the identified one or more incident categories of the current incident data object; and [Anand search with classification keywords (filter) ¶34, ¶38 "search engine may use classification keywords as search terms"]
identifying the past incident data objects associated with the same incident category(ies) as the identified one or more incident categories of the current incident data object as the past incident candidate data object set. [Anand incidents are identified/returns accordingly ¶41]
As to dependent claim 12, the rejection of claim 1 is incorporated Anand and Choudhary further teach determining the primary ranking of the past incident candidate data object subset based on at least a relevance score of each past incident candidate data object of the past incident candidate data object subset. [Anand relevancy score ranking ¶70 "calculating relevancy score and ranking search results"]
As to dependent claim 15, the rejection of claim 1 is incorporated Anand and Choudhary further teach wherein determining the one or more subsequent rankings of the primarily ranked past incident candidate data objects comprises: extracting one or more incident attributes from each of the current incident data object and the primarily ranked past incident candidate data objects; [Anand analyzes incident information (attributes) like symptoms ¶20]
determining an updated relevance score for each of the primarily ranked past incident candidate data objects; and [Anand final relevancy score ¶47-48]
determining the one or more subsequent rankings of the primarily ranked past incident candidate data objects of the past incident candidate data object subset based on at least the updated relevance score of each past incident candidate data object. [Anand refines ranking via elimination for final/top results ¶24]
As to independent claim 17, Anand teaches a method for outputting a past incident insight interface component in a software monitoring data management system, the method comprising: [interfaces and software for managing incidents ¶69]
detecting a past incident insight interface component request in response to user interaction with a software monitoring data management system, [detects IT incident diagnosis request (query) with search software interface ¶24, ¶5 "a user interface operable to execute on a processor and issue a query. The system may also comprise a search engine operable to receive the query, transform the query into sub-queries comprising a structured search and a free-text search, and to search for co-occurring and reoccurring group of incidents"]
wherein the past incident insight interface component request is associated with a current incident data object; [related to a current incident data object (ticket or IT incident with ID, keywords and more) Fig. 1 102 ¶24-25"keywords are extracted from an incident ticket to classify the incident"]
identifying a past incident candidate data object set based on the current incident data object;[Searches for co-occurring/similar incidents (set) based on first incident ID, keyworks or constraints Fig. 1 104 ¶35-38 "Relevant (co-occurring and reoccurring) incidents are searched for by keywords and constraints."…"To simplify its use, the search engine may require only an incident ID as an input""]
determining a primary ranking of the past incident candidate data object set or a subset thereof; [similarity score ranking (primary ranking) ¶24 "Use similarity score (e.g., Space vector model) to rank the returned results"]
determining one or more subsequent rankings of the primarily ranked past incident candidate data objects of the past incident candidate data object set or the subset thereof; [after similarity rank do a context relevance and final relevancy score for final results (subset) ¶47,¶24 "after the similarity score ranking, get a context relevancy weight by looking at account technology portfolio; 5) From the ranked list, return final search results"]
generating a past incident insight interface component comprising a listing of a past incident candidate data object suggestion set, the past incident candidate data object suggestion set listing one or more of the subsequently ranked past incident candidate data objects; and [dashboard interface ¶56, returns ranked and weighted list of results ¶4 "returning a top predetermined number of results from the ranked list of results."]
alerts [user views alerts ¶63 "When the system detects events satisfying the condition of the rules, the system generates and consolidates alerts; User views alerts and take actions."]
Anand does not specifically teach outputting the past incident insight interface component for rendering to an incident alert management user interface of a computing device associated with the past incident insight interface component request.
However, Choudhary teaches outputting the past incident insight interface component for rendering to an incident alert management user interface of a computing device associated with the past incident insight interface component request. [GUI for past events(incidents/alarms) including correlated results from filter request and actions for managing (Fig. 34O Col. 118 ln. 52-67 " results section 34570 of GUI 34550 displays one or more notable events that meet the filtering criteria entered in filtering controls section 34560, and displays certain information pertaining to those notable events. In one implementation, a corresponding entry for each notable event that satisfies the filtering criteria may be displayed in results section 34570. "]
Accordingly, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to modify the incident diagnosis by Anand by incorporating the outputting the past incident insight interface component for rendering to an incident alert management user interface of a computing device associated with the past incident insight interface component request disclosed by Choudhary because both techniques address the same field of event management and by incorporating Choudhary into Anand enables users to better understand the IT environment with improved monitoring and visualizations [Choudhary Col. 12 ln. 3-20].
As to dependent claim 19, the rejection of claim 17 is incorporated Anand and Choudhary further teach wherein determining the one or more subsequent rankings of the primarily ranked past incident candidate data objects comprises: extracting one or more incident attributes from each of a current incident data object and the primarily ranked past incident candidate data objects; [Anand analyzes incident information (attributes) like symptoms ¶20]
determining an updated relevance score for each of the primarily ranked past incident candidate data objects; and [Anand final relevancy score ¶47-48]
determining the one or more subsequent rankings of the primarily ranked past incident candidate data objects of the past incident candidate data object subset based on at least the updated relevance score of each past incident candidate data object. [Anand refines ranking via elimination for final/top results ¶24]
As to independent claim 20, Anand teaches a computer program product for outputting a past incident insight interface component in a software monitoring data management system, the computer program product comprising at least one non-transitory computer-readable storage medium having computer-readable program code portions stored therein, the computer-readable program code portions comprising an executable portion configured to: [programs, processors and memory ¶73-74 for managing incidents ¶69]
detect a past incident insight interface component request in response to user interaction with a software monitoring data management system, [detects IT incident diagnosis request (query) with search software interface ¶24, ¶5 "a user interface operable to execute on a processor and issue a query. The system may also comprise a search engine operable to receive the query, transform the query into sub-queries comprising a structured search and a free-text search, and to search for co-occurring and reoccurring group of incidents"]
wherein the past incident insight interface component request is associated with a current incident data object; [related to a current incident data object (ticket or IT incident with ID, keywords and more) Fig. 1 102 ¶24-25"keywords are extracted from an incident ticket to classify the incident"]
identify a past incident candidate data object set based on the current incident data object;[Searches for co-occurring/similar incidents (set) based on first incident ID, keyworks or constraints Fig. 1 104 ¶35-38 "Relevant (co-occurring and reoccurring) incidents are searched for by keywords and constraints."…"To simplify its use, the search engine may require only an incident ID as an input""]
determine a primary ranking of the past incident candidate data object set or a subset thereof; [similarity score ranking (primary ranking) ¶24 "Use similarity score (e.g., Space vector model) to rank the returned results"]
determine one or more subsequent rankings of the primarily ranked past incident candidate data objects of the past incident candidate data object set or the subset thereof; [after similarity rank do a context relevance and final relevancy score for final results (subset) ¶47,¶24 "after the similarity score ranking, get a context relevancy weight by looking at account technology portfolio; 5) From the ranked list, return final search results"]
generate a past incident insight interface component comprising a listing of a past incident candidate data object suggestion set, the past incident candidate data object suggestion set listing one or more of the subsequently ranked past incident candidate data objects; and [dashboard interface ¶56, returns ranked and weighted list of results ¶4 "returning a top predetermined number of results from the ranked list of results."]
alerts [user views alerts ¶63 "When the system detects events satisfying the condition of the rules, the system generates and consolidates alerts; User views alerts and take actions."]
Anand does not specifically teach output the past incident insight interface component for rendering to an incident alert management user interface of a computing device associated with the past incident insight interface component request.
However, Choudhary teaches output the past incident insight interface component for rendering to an incident alert management user interface of a computing device associated with the past incident insight interface component request. [GUI for past events(incidents/alarms) including correlated results from filter request and actions for managing (Fig. 34O Col. 118 ln. 52-67 " results section 34570 of GUI 34550 displays one or more notable events that meet the filtering criteria entered in filtering controls section 34560, and displays certain information pertaining to those notable events. In one implementation, a corresponding entry for each notable event that satisfies the filtering criteria may be displayed in results section 34570. "]
Accordingly, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to modify the incident diagnosis by Anand by incorporating the output the past incident insight interface component for rendering to an incident alert management user interface of a computing device associated with the past incident insight interface component request disclosed by Choudhary because both techniques address the same field of event management and by incorporating Choudhary into Anand enables users to better understand the IT environment with improved monitoring and visualizations [Choudhary Col. 12 ln. 3-20].
Claim 4 is rejected under 35 U.S.C. 103 as being unpatentable over Anand in view of Choudhary as applied to the rejection of claim 3 above, and further in view of Chor (US 10868711 B2).
As to dependent claim 4, the combination of Anand and Choudhary teach all the limitations of claim 3 that is incorporated.
Anand and Choudhary do not specifically teach receive a team member data object associated with a selected subsequently ranked past incident candidate data object, wherein the team member data object is based on user interaction with the team member identifier rendered in association with the selected subsequently ranked past incident candidate data object; generate a notification in response to receiving the team member data object; and transmit the notification to a computing device associated with the team member identifier.
However, Chor teaches receive a team member data object associated with a selected subsequently ranked past incident candidate data object, [receive recipient (team member) associated with event (Fig. 22 2220 ) Col. 70 ln. 55-67 "recipient list component 2220, recipient add button interactive component 2222,"]
wherein the team member data object is based on user interaction with the team member identifier rendered in association with the selected subsequently ranked past incident candidate data object; [Col. 71 ln. 30-40 "Recipient list component 2220 is illustrated as a list box with a single entry indicating the name, “J. Nguyen,” and the phone number, “415-555-1234,” used to send or direct an actionable alert generated in accordance with the present definition"]
generate a notification in response to receiving the team member data object; and [generates alert to recipient Col. 71 ln. 30-40]
transmit the notification to a computing device associated with the team member identifier. [sends alert to recipient Col. 71 ln. 30-40]
Accordingly, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to modify the messaging disclosed by Anand and Choudhary by incorporating the receive a team member data object associated with a selected subsequently ranked past incident candidate data object, wherein the team member data object is based on user interaction with the team member identifier rendered in association with the selected subsequently ranked past incident candidate data object; generate a notification in response to receiving the team member data object; and transmit the notification to a computing device associated with the team member identifier disclosed by Chor because all techniques address the same field of event management and by incorporating Chor into Anand and Choudhary provides a more intelligent and efficient analysis of results for root cause analysis [Chor Col. 51 ln. 44-55]
Claims 7-8 are rejected under 35 U.S.C. 103 as being unpatentable over Anand in view of Choudhary as applied to the rejection of claim 1 above, and further in view of Madan et al. (US 11269901 B2 hereinafter Madan)
As to dependent claim 7, the combination of Anand and Choudhary teach all the limitations of claim 1 that is incorporated.
Anand and Choudhary do not specifically teach wherein the past incident insight interface component comprises one or more feedback actuator buttons associated with at least one of the subsequently ranked past incident candidate data objects, the one or more feedback actuator buttons configured for user interaction.
However, Madan teaches wherein the past incident insight interface component comprises one or more feedback actuator buttons associated with at least one of the subsequently ranked past incident candidate data objects, the one or more feedback actuator buttons configured for user interaction. [interface with buttons (Fig. 4 434/436) for feedback (thumbs up) Col. 9 ln. 19-30 " feedback is provided via the clicking or selecting of a thumbs up 434 or a thumbs down symbol 436"]
wherein the team member data object is based on user interaction with the team member identifier rendered in association with the selected subsequently ranked past incident candidate data object; [Col. 71 ln. 30-40 "Recipient list component 2220 is illustrated as a list box with a single entry indicating the name, “J. Nguyen,” and the phone number, “415-555-1234,” used to send or direct an actionable alert generated in accordance with the present definition"]
generate a notification in response to receiving the team member data object; and [generates alert to recipient Col. 71 ln. 30-40]
transmit the notification to a computing device associated with the team member identifier. [sends alert to recipient Col. 71 ln. 30-40]
Accordingly, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to modify the messaging disclosed by Anand and Choudhary by incorporating the receive a team member data object associated with a selected subsequently ranked past incident candidate data object, wherein the team member data object is based on user interaction with the team member identifier rendered in association with the selected subsequently ranked past incident candidate data object; generate a notification in response to receiving the team member data object; and transmit the notification to a computing device associated with the team member identifier disclosed by Madan because all techniques address the same field of event management and by incorporating Madan into Anand and Choudhary improve the repair actions for incidences while incorporating feedback [Madan Col. 4 ln. 4-12].
As to dependent claim 8, the rejection of claim 7 is incorporated Anand, Choudhary and Madan further teach wherein the program code is further configured to, with the at least one processor, cause the apparatus to at least: receive one or more user feedback data objects associated with the at least one of the subsequently ranked past incident candidate data objects, wherein the one or more user feedback objects are based on user interaction with at least one of the one or more feedback actuator buttons; [Madan selected feedback buttons (Fig. 4 434/436) Col. 9 ln. 19-30 " feedback is provided via the clicking or selecting of a thumbs up 434 or a thumbs down symbol 436"]
store the one or more user feedback data objects in a database; and [Madan feedback stored in database Col. 12 ln. 40-43 "The feedback is stored in the feedback storage database, which can be subsequently used via machine learning to improve the manner in which subsequent proposed solutions are identified by the system"]
continually refine one or more machine learning models via a positive feedback loop based on the stored one or more user feedback data objects. [Madan feedback used in machine learning algorithm (model) Col. 9 ln. 32-35 "The feedback can be incorporated into machine learning (e.g., deep machine learning supervised or unsupervised algorithms) to improve future recommendation results."]
Claims 10-11 are rejected under 35 U.S.C. 103 as being unpatentable over Anand in view of Choudhary as applied to the rejection of claim 9 above, and further in view of SACHAN et al. (US 20200293946 A1 hereinafter Sachan)
As to dependent claim 10, the combination of Anand and Choudhary teach all the limitations of claim 9 that is incorporated.
Anand and Choudhary do not specifically teach wherein identifying the one or more incident categories of the current incident data object comprises: causing input of the plurality of past incident data objects to an incident categorization machine learning model, the incident categorization machine learning model generating a plurality of incident categories based on the plurality of past incident data objects; extracting at least an incident title from the current incident data object; and associating one or more incident categories of the plurality of incident categories with the current incident data object based at least in part on the extracted incident title.
However, Madan teaches wherein identifying the one or more incident categories of the current incident data object comprises: causing input of the plurality of past incident data objects to an incident categorization machine learning model, the incident categorization machine learning model generating a plurality of incident categories based on the plurality of past incident data objects; [classification model based on historical incidents ¶29 "determination may be made by utilizing a machine learning based incident classification model that is trained on historical incident tickets"]
extracting at least an incident title from the current incident data object; and [short description (title) ¶34, ¶86]
associating one or more incident categories of the plurality of incident categories with the current incident data object based at least in part on the extracted incident title. [description used as input features by model to predict subcategory (associate) ¶127 " For example, a description of the incident, a short description of the incident, and a category of the incident may be utilized as input features to predict a subcategory of the incident."]
Accordingly, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to modify the messaging disclosed by Anand and Choudhary by incorporating the wherein identifying the one or more incident categories of the current incident data object comprises: causing input of the plurality of past incident data objects to an incident categorization machine learning model, the incident categorization machine learning model generating a plurality of incident categories based on the plurality of past incident data objects; extracting at least an incident title from the current incident data object; and associating one or more incident categories of the plurality of incident categories with the current incident data object based at least in part on the extracted incident title disclosed by Sachan because all techniques address the same field of event management and by incorporating Sachan into Anand and Choudhary improves routing of incidents and collects more data for better decisions like sentiment [Sachan ¶28]
As to dependent claim 11, the rejection of claim 10 is incorporated Anand, Choudhary and Sachan further teach wherein the incident categorization machine learning model comprises a clustering machine learning model in accordance with one or more clustering algorithms. [Sachan identify clusters ¶184]
Claims 13-14 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Anand in view of Choudhary as applied to the rejection of claim 12 above, and further in view of Liu et al. (US 20180276305 A1 hereinafter Liu).
As to dependent claim 13, the combination of Anand and Choudhary teach all the limitations of claim 3 that is incorporated.
Anand and Choudhary further teach wherein determining the primary ranking of the past incident candidate data object subset based on at least the relevance score of each past incident candidate data object of the past incident candidate data object subset comprises: determining a similarity score, as compared to the current incident data object, for each past incident candidate data object of the past incident candidate data object set; [Anand similarity score between incidents ¶46]
comparing the similarity score for each past incident candidate data object of the past incident candidate data object set to a predetermined threshold; [Anand similarity threshold ¶24]
determining the past incident candidate data object subset, wherein the past incident candidate data object subset comprises the past incident candidate data objects of the past incident candidate data object set having similarity scores that satisfy the predetermined threshold; [Anand top 10 based on similarity threshold ¶24]
determining the relevance score for each past incident candidate data object of the past incident candidate data object subset. [Anand final relevancy score ¶47-48]
Anand and Choudhary do not specifically teach determining a recency score for each past incident candidate data object of the past incident candidate data object subset.
However, Liu teaches determining a recency score for each past incident candidate data object of the past incident candidate data object subset; [recency score ¶132 " A recency score may be computed for recommended citations, for example to indicate how recent a recommended case is"]
Accordingly, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to modify the messaging disclosed by Anand and Choudhary by incorporating the determining a recency score for each past incident candidate data object of the past incident candidate data object subset disclosed by Liu because all techniques address the same field of event management and by incorporating Liu into Anand and Choudhary better identifies relevant information in a quicker way [Liu ¶4-5].
As to dependent claim 14, the rejection of claim 13 is incorporated Anand, Choudhary and Liu further teach wherein the relevance score for each past incident candidate data object is an aggregate of the similarity score and the recency score of the past incident candidate data object. [Liu relevant and/or recent ¶52 aggregation of sub scores ¶21 " relevancy score is based on an aggregation of two or more weighted sub scores, the sub scores including a jurisdiction score, an authority score, an issue similarity score, and a recency score."]
As to dependent claim 18, the combination of Anand and Choudhary teach all the limitations of claim 17 that is incorporated.
Anand and Choudhary further teach wherein determining the primary ranking of the past incident candidate data object subset based on at least the relevance score of each past incident candidate data object of the past incident candidate data object subset comprises: determining a similarity score, as compared to the current incident data object, for each past incident candidate data object of the past incident candidate data object set; [Anand similarity score between incidents ¶46]
comparing the similarity score for each past incident candidate data object of the past incident candidate data object set to a predetermined threshold; [Anand similarity threshold ¶24]
determining the past incident candidate data object subset, wherein the past incident candidate data object subset comprises the past incident candidate data objects of the past incident candidate data object set having similarity scores that satisfy the predetermined threshold; [Anand top 10 based on similarity threshold ¶24]
determining the relevance score for each past incident candidate data object of the past incident candidate data object subset. [Anand final relevancy score ¶47-48]
Anand and Choudhary do not specifically teach determining a recency score for each past incident candidate data object of the past incident candidate data object subset.
However, Liu teaches determining a recency score for each past incident candidate data object of the past incident candidate data object subset; [recency score ¶132 " A recency score may be computed for recommended citations, for example to indicate how recent a recommended case is"]
Accordingly, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to modify the messaging disclosed by Anand and Choudhary by incorporating the determining a recency score for each past incident candidate data object of the past incident candidate data object subset disclosed by Liu because all techniques address the same field of event management and by incorporating Liu into Anand and Choudhary better identifies relevant information in a quicker way [Liu ¶4-5].
Claim 16 is rejected under 35 U.S.C. 103 as being unpatentable over Anand in view of Choudhary as applied to the rejection of claim 15 above, and further in view of Mehta et al. (US 8788436 B2 hereinafter Mehta)
As to dependent claim 16, the combination of Anand and Choudhary teach all the limitations of claim 15 that is incorporated.
Anand and Choudhary do not specifically teach receive wherein determining the updated relevance score for each of the primarily ranked past incident candidate data object comprises inputting the extracted incident attributes to a decision tree-based ranker machine learning model that is trained to output the updated relevance scores.
However, Mehta teaches receive wherein determining the updated relevance score for each of the primarily ranked past incident candidate data object comprises inputting the extracted incident attributes to a decision tree-based ranker machine learning model that is trained to output the updated relevance scores. [Decision tree ranker and scoring for updated ranking Col. 6 ln. 50-55, Col. 12 ln. 1-2 " the ranker component 118 may be a decision tree based ranker."]
Accordingly, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention to modify the messaging disclosed by Anand and Choudhary by incorporating the receive wherein determining the updated relevance score for each of the primarily ranked past incident candidate data object comprises inputting the extracted incident attributes to a decision tree-based ranker machine learning model that is trained to output the updated relevance scores disclosed by Mehta because all techniques address the same field of event management and by incorporating Mehta into Anand and Choudhary enhances the accuracy of search results with improved rankings and relevancy [Mehta Col. 1 ln. 17-40].
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Applicant is required under 37 C.F.R. § 1.111(c) to consider these references fully when responding to this action.
Sukumaran et al. (US 20220276911 A1) teaches an interface that ranks notifications (see Fig. 5D and ¶28)
It is noted that any citation to specific pages, columns, lines, or figures in the prior art references and any interpretation of the references should not be considered to be limiting in any way. A reference is relevant for all it contains and may be relied upon for all that it would have reasonably suggested to one having ordinary skill in the art. In re Heck, 699 F.2d 1331, 1332-33, 216 U.S.P.Q. 1038, 1039 (Fed. Cir. 1983) (quoting In re Lemelson, 397 F.2d 1006, 1009, 158 U.S.P.Q. 275, 277 (C.C.P.A. 1968)).
Any inquiry concerning this communication or earlier communications from the examiner should be directed to Beau Spratt whose telephone number is 571 272 9919. The examiner can normally be reached 8:30am to 5:00pm (PST).
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/BEAU D SPRATT/Primary Examiner, Art Unit 2143
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